DEDICATIONFor Anita,
who showed me that one plus one
can be much greater than two

CONTENTS
Dedication
1 The Big Question
2 The Conflict Within
3 Science in the Real World
4 Outside the Box
5 A Dose of Common Science
6 Life Is Good
7 Waiting for Wonders
8 Lost in Space
9 The Art of Making Sense
10 Coming Alive
11 Seeing and Believing
12 Last Throes
13 First World
14 The New School
Acknowledgments
Notes
Credits
Index
Color Plates
About the Author
Copyright
About the Publisher

CHAPTER 1

THE BIG QUESTION
In August of 2013, as I was making my way down a picturesque Cambridgestreet called King’s Parade, I nearly collided with renowned British scientist Sir
Alan Fersht. We were a short distance from Cambridge University’s Gonvilleand Caius College, where he serves as Master among a distinguished group ofscholars including the well-known cosmologist Professor Stephen Hawking.
Fersht was exiting a shop, stepping across the sidewalk to his bicycle, and thatwas where our paths crossed.
I know him as Alan. I had been friends with him for so long—having worked
at research centers directed by him from 1990 to 2002—that I assumed we
probably still were friends, eleven years after we went our separate ways. Events
had tested the friendship, though. From my perspective, an honest conversation
making it clear where we stood with each other and why our working
relationship had to end so abruptly would have been very helpful when I left his
Centre for Protein Engineering in 2002. I had regretted the absence of thatconversation over the years, and now, in the space of a few minutes, it occurred
to me that he might have regretted it too.
Our time was short. I had a vacationing family waiting for me and Alan had
a college waiting for him, so we settled for something less than closure. We did
what we could do with a few minutes. After all that had happened previously,
those few minutes reaffirmed our friendship, which was a good start.
The initial awkwardness of that encounter proved well worth enduring, as isoften the way with awkwardness. I speak as something of an expert on thesubject. Most people find their place in the stream of life early on by mastering
the art of “going with the flow,” but I seem to be one of the exceptions. I neverset out to oppose the stream. Still, I found myself compelled to take a course you
would never choose if the power of the stream were at the forefront of yourmind. As anyone who’s tried wading across swift waters knows, awkwardness
was bound to follow.

I recall a question on a final exam near the beginning of my graduate studies
at Caltech: Which of the biological macromolecules is apt to have been the first“living” molecule, and why? If that sounds like Greek to you, relax. I promise towrite in plain English. All you need to know is that the question is about how
life began, posed with the unstated assumption that it began by ordinary
molecular processes. That assumption had been ingrained in biological thinking
for so long that it went without saying. Every student in the class understood
this, but I understood it more critically than most did. I knew the expected
response to the test question, but through my critical lens, that response seemedscientifically questionable. So I had a choice: Do I go with the flow, or do I pushagainst it?
I decided to give the expected answer in full and then—for extra credit—to
state why I found that answer unconvincing. I explained why, contrary to theconsensus view, I didn’t think any molecule has what would be needed to startlife. As shrewd as that seemed at the time, I learned when my exam was returned(with points deducted) that we students were expected not only to know current
thinking in biology but also to accept it without resistance. We were there as
much to be acculturated as educated.
I had learned my lesson. The stream of scientific consensus flows with analmost irresistible current.
Almost.
AWKWARD SCIENCEOf all the controversial ideas to come from modern science, none has brought
more awkwardness than Darwin’s idea of evolution through natural selection.
We know natural selection means “survival of the fittest,” which in one sense
isn’t at all controversial. Indeed, Darwin’s observation that fitter individuals are
apt to have more offspring is so obvious it hardly needs to be stated. But how
can something with so little content—a truism—possibly explain the astoundingrichness of life?
The biggest question on everyone’s minds has never been the question ofsurvival but rather the question of origin—our origin in particular. How did we
get here? Even if you think natural selection is the answer, you have to admit toa degree of internal conflict over the matter. Francis Crick acknowledged thisconflict, at least implicitly, when he cautioned that “biologists must constantlykeep in mind that what they see was not designed, but rather evolved.”1 So if
Darwin’s claim is true, then it’s a truth we all find ourselves doubting—at least
subconsciously—and if it’s false, then we’re to be commended for doubting it.
Awkwardness clings to it either way.
In fact, though you won’t see this in any textbook, Darwin implicitly
conceded something that adds to the unease surrounding his theory. All six
editions of his book On the Origin of Species include a few paragraphs in the
conclusion where he addressed the widespread rejection of his theory by his
scientific peers. He began with a question: “Why, it may be asked, have all themost eminent living naturalists and geologists rejected this view of themutability of species?” The answer, he thought, was their closed-mindedness.
Sensing little hope of opening more than a few of those minds, he decided to“look with confidence to the future, to young and rising naturalists, who will beable to view both sides of the question with impartiality.”2
To Darwin’s own great surprise, this near total rejection of his theory turned
to near total acceptance within just a few years. Up to the publication of the fifth
edition of his book in 1869, his original gloomy assessment of the reception of
his work wasn’t in need of revision. Then in 1872, a mere three years later, thesixth edition followed those original paragraphs with this commentary:
As a record of a former state of things, I have retained in the foregoingparagraphs, and elsewhere, several sentences which imply that naturalists
believe in the separate creation of each species; and I have been muchcensured for having thus expressed myself. But undoubtedly this was thegeneral belief when the first edition of the present work appeared. I
formerly spoke to very many naturalists on the subject of evolution, andnever once met with any sympathetic agreement. It is probable that some
did then believe in evolution, but they were either silent, or expressed
themselves so ambiguously that it was not easy to understand their
meaning. Now things are wholly changed, and almost every naturalist
admits the great principle of evolution.3
What would cause such a sudden reversal of scientific opinion? Did a newscientific discovery appear in the late 1860s or early 1870s—potent enough toconvince the skeptics that Darwin was right after all? Clearly not, as Darwin
surely would have cited such a decisive finding. But if science itself wasn’t thecause of the change, then what was?

Whether he intended to or not, Darwin reveals here that peer pressure is apart of science, happening behind the scenes as the various scientific interests
compete against one another for influence. If it’s a plain historical fact that theexperts didn’t side with Darwin in the early 1860s, then why would he have been“much censured” by his peers for saying so? It’s as though his colleagues wanted
all mention of opposition expunged from the record now that this opposition had
faded. Darwin resisted the pressure applied to him on that occasion, but what if
others, perhaps under even greater pressure, were less able to resist? Might theearlier inability of some scientists to express their support of Darwin’s theory—the silence and ambiguity of expression Darwin referred to—have been the
result of peer pressure too? And if so, then might the sudden change in Darwin’s
favor have been more like a change of power than a change of minds—a sudden
reversal of the stream’s flow?
We have good reason to consider this possibility. The question of what
controls the stream—why it flows this way and not that, and why it changes
when it does—is every bit as important now as it was back then. If yesterday’s
scientists were influenced as much by human factors as by data, wouldn’t this beequally true of today’s scientists? And if it is true, what does this mean for thereceived wisdom of our day, which holds the evolutionary view to be the only
one worth taking seriously?
As we think more about how science works, we’ll see that those rare people
who oppose the stream are the ones to watch.
HEROIC MISFITS
Thankfully, every generation has had a handful of rebels who are compelled to
do just that. A countercurrent of awkwardness flows from these misfits inrefreshing waves. Among the most beautiful examples of this I’ve come acrossis a man named Thomas Nagel, a professor of philosophy at New York
University. He’s a highly unusual atheist, the author of a superb wave-making
book titled Mind and Cosmos: Why the Materialist Neo-Darwinian Conceptionof Nature Is Almost Certainly False.4
By way of background, the flag that has flown for many generations over theacademy of higher education is that of a broad school of thought known asmaterialism.5 The meaning here isn’t the common one (an obsession with flashycars or expensive clothes) but rather the view that matter—the stuff of physics—

underlies everything real. Even if they don’t use this term, atheists tend to
subscribe to the materialist view of reality, believing God to be a product of thehuman imagination, which they believe to be a product of material evolution.
Theists, on the other hand, believe the reverse—that the material universe wasbrought into existence by God, who is not material. Both views accept the realityof the physical world, but one sees this as the only reality whereas the otherdoesn’t.
People on either side of this divide might think constructive dialogue ishopeless because everyone on the other side has fallen prey to wishful thinking.
In practice, however, I find that atheists are more inclined toward this. Atheists
have a pronounced leaning toward scientism, which is the belief that science isthe only reliable source of truth. It’s entirely understandable, then, that belief in
God might look to them like wishful thinking—as though people of faith have
let their hearts overpower their heads. Although people of serious faith (myself
included) know this to be a misconception, our holistic understanding of humanbelief and behavior certainly does include the heart along with the head. We
fully acknowledge that emotion can get in the way of clear thinking, but since
we see this as a very general condition of humanity, we would never offer it as aparticular weakness of atheism, the way so many atheists offer it as a particular
weakness of theism.
TWO -ISMS WORTH REMEMBERING
materialism:

the belief that physical stuff underlies everything realscientism:

the belief that science is the only reliable source of truth
Returning to Thomas Nagel, as you may have guessed from the title of hisbook, he isn’t your typical atheist. Most significantly, he roundly rejects thesimplistic scientism that so many atheists still cling to. His atheism is heartdriven, and he isn’t afraid to say so:
I want atheism to be true and am made uneasy by the fact that some of
the most intelligent and well-informed people I know are religious
believers. It isn’t just that I don’t believe in God and, naturally, hope that

I’m right in my belief. It’s that I hope there is no God! I don’t want there
to be a God; I don’t want the universe to be like that.
My guess is that this cosmic authority problem is not a rare condition
and that it is responsible for much of the scientism and reductionism of
our time. One of the tendencies it supports is the ludicrous overuse ofevolutionary biology to explain everything about life, including
everything about the human mind.6
As a first-rate philosopher of the mind, Nagel actually changes the debatewith this candid version of atheism. In light of his example, thoughtful atheists
no longer have the luxury of assuming their worldview just works somehow—that dead molecules somehow formed simple life, and that simple life somehow
formed us, despite all the apparent difficulties. Nor do they have the luxury of
dismissing every argument against atheism on grounds of religious bias.
Thoughtful theists, for their part, can no longer assume that atheism necessarily
breeds contempt for faith.
Nagel is living proof that the awkwardness of bare-naked honesty doesn’t
compare to the reward of engaging seriously the matters that concern us most—aprinciple that will serve us well as we begin our journey together. You need no
special training to join this expedition. All you need is a healthy dose of
curiosity and a healthy tolerance of the good kind of awkwardness—the kindthat comes from challenging claims that ought to be challenged.
THE BIG QUESTION
Again, that one big question of our origin unites us—not because we agree on
the answer but because we should all agree on the importance of finding theanswer. Throughout history, it has been the foremost question of people
searching for understanding: What is the source from which everything elsecame? Or, to bring it closer to home: To what or to whom do we owe ourexistence? This has to be the starting point for people who take life seriously—
scientists and nonscientists alike. We cannot rest without the answer, because
absolutely everything of importance is riding on it. To know where everythingcame from is to know where we came from, and where we came from has
everything to do with who we are, and who we are has everything to do withhow we ought to live.

THE BIG QUESTION
To what or to whom do we owe our existence?
If all goes well, our journey in this book will take us to the answer. We’ll
know we have arrived when we have an answer that not only rings true but also
distinguishes itself as the one answer that rings true. There should be no credible
alternative.
A map will be helpful as we begin. My aim over the next four chapters isn’t
to answer the big question but instead to show where we should be looking forthe answer. Chapter 2 will introduce the intuition that creates internal conflict inall of us by tugging against Darwin’s claims. This design intuition, as we willcall it, is the very intuition Crick wanted us to suppress. Chapters 3 and 4 will bea short account of the unexpected lessons I learned while seeking a scientificsolution to this internal conflict. These lessons weren’t about the proteins I was
studying but about the people I interacted with along the way—really, about
people in general. With those lessons in hand, we’ll see in chapter 5 that theanswer we’re seeking is to be found not in technical science but in somethingmuch more familiar—something I call common science. There will be plenty of
glimpses of technical science along the way, but all of these will be presented
with the nontechnical reader in mind. In the end, we’ll see that mastery oftechnical subjects isn’t at all needed in order for us to know the answer to the big
question. Common science will be perfectly adequate.
The next section of the book—chapters 6 through 9—will be a journey
through the important aspects of common science. The point of chapter 6 will beto provide a better understanding of what life is and what it isn’t, which will
prove helpful as we progress to the matter of where life came from. Chapter 7
will be a common-science refutation of the idea that natural selection explains
how life came to exist in its countless remarkable forms. With natural selection
off the table, chapter 8 will be an exploration of searching, showing that the
many inventions needed for new life forms to evolve would have had to be foundaccidentally. Chapter 9 will finish the section by showing why invention can’t
actually happen that way. The intuition that Crick wanted us to suppress will end
up being confirmed instead.
But all this only tells us what the answer to our question isn’t. To arrive at asatisfying understanding of what the answer is will require us to continue ourjourney a bit further. In chapter 10 we will revisit the question of what life is,viewing it this time through the lens of invention. The following two chapters,
11 and 12, will serve as a reality check, first by considering carefully whether wehave overlooked anything in rejecting the evolutionary explanation of life andthen by asking whether the scientific community’s defense of evolution looks
more like a “science thing” or a “culture thing.” Finally, chapters 13 and 14
complete our journey. There we examine the nature of life and humanity moredeeply—leading to a clear picture of what the answer to the big question is—after which I offer a glimpse of what I hope biology will look like in the not-toodistant future, after a great many people join us on this journey.

CHAPTER 2

THE CONFLICT WITHINIn 1986, not long after I challenged the assumptions behind that exam question
at Caltech, I had a career-changing aha moment during a biochemistry lecture.
Earlier, as an engineering student at Berkeley, I had learned about somethingcalled a feedback loop. The basic idea is simple, though considerable ingenuity
is often needed to implement it effectively. Consider a familiar example: thethermostat used to control the temperature in your home. Factors like theweather outside or your cooking a meal inside often work against your aim of
keeping the house at a comfortable temperature. The job of the thermostat is tocounteract those disturbances by constantly measuring the indoor temperature
and activating the heating or air-conditioning as needed. So the measured
temperature is used as real-time information (feedback) by an automatic
decision-maker (the thermostat) to control the very thing that is being measured:
the temperature.
As straightforward as that sounds, it becomes much more complicated whenhighly active and complex processes must be kept under control. Knowing thatthe chemistry occurring inside growing cells is just that—highly active andcomplex—I was astonished when my biochemistry instructor revealed theelegance of the automatic decision-makers working on the molecular scale tokeep the various chemicals of life at the right levels! The connection toengineering was so strikingly and delightfully obvious to me that I felt laughter
well up.
As if anticipating my reaction, the instructor was quick to attribute theseingenious molecular decision-makers to unguided evolutionary processes. His
message was clear: however remarkable these molecular control systems may
be, they should be considered nothing more than natural accidents—just likeeverything else in biology.
Huh?
I didn’t believe him. I knew—intuitively, anyway—that no string of

accidents could possibly be so clever. At the same time, I sensed the weight ofscientific authority standing with his interpretation and against mine. Notice I
use the word authority here instead of evidence. He was the professor; I was thestudent. He could have filled the room with distinguished colleagues who agreed
with his view, whereas I didn’t even know any students who agreed with mine.
And yet, for all the claims I had heard in lectures and read in textbooks about theinventive power of Darwin’s evolutionary process, I hadn’t seen a convincing
scientific basis for these claims. As far as I knew, no one had shown how theamazing things of life could be accidental inventions instead of deliberate ones.
I was aware, of course, of the mountain of books and technical papers inwhich the facts of biology were interpreted through the lens of evolution, and I
knew that many people perceived this huge body of literature as the very
documented evidence I was seeking. I, however, saw this mountain only as
confirmation (if any were needed) that the evolutionary lens was dominant in thelife sciences. After all, countless ideas have gained large followings andgenerated piles of books, but no one is naïve enough to think all these ideas must
therefore be true. No, I was after evidence of another kind—the kind with thepower to persuade people who aren’t initially in agreement. Nothing in thatmountain of evolutionary literature seemed to be that. Nothing took the views ofDarwin-doubters seriously. I knew this because I was one.
So, as a Darwin-doubter, I started planning to do the work myself. Though I
had to be willing to be proved wrong, my strong hunch was that the results ofthis work would reverse the stream of scientific consensus. The stream’s flow
had been reversed before, so I figured it could be reversed again. I knew there
were risks, but my motive for proceeding was too strong to be ignored. The
troubling contradiction between what the voice of scientific consensus wastelling me and what the voice of my own intuition was telling me—the conflictwithin—had to be resolved. That’s exactly what I set out to do.
I have something even bigger in mind for this book, though. Here I hope toresolve the same conflict for you. It exists in all of us to some degree. We share it
to the extent we share the intuition that life can’t be an accident. And for all ofus, understanding is what eliminates the contradiction. Technical understanding
can be overwhelming for many of us, though, so while I will offer glimpses ofwhat I consider to be the decisive technical science, I won’t turn this into ascience lecture. Instead, common science will be the thread that holds everything
together.
To prepare us for that, let’s start with an experiment performed in the kitchenrather than in the lab.
STARTING WITH SOUP
A team of researchers in the culinary sciences recently discovered a
revolutionary new soup they call oracle soup, referring to the oracles(mysterious revelations) the ancient Greeks sought from their gods. Indeed, had
this soup been known in the days of Homer, it surely would have been attributed
to a powerful god. It looks just like alphabet soup—thin broth with little pasta
letters and numbers swirling around—but this “soup of the gods” distinguishes
itself by what it does, as this experimental recipe shows:
1. Fill a large pot with oracle soup.
2. Cover the pot, and bring the soup to a boil.
3. Remove the pot from the heat, and let the soup cool.
4. Lift the lid to reveal complete instructions for building something new
and useful, worthy of a patent—all spelled out in pasta letters.
5. Repeat from step 2 as often as desired.
You don’t believe a word of this, of course, and that’s precisely my point.
This was actually a storytelling experiment instead of a kitchen experiment. You
were my experimental subject (sorry about that), but now I want you to examine
the result. What did you observe? Well, in the space of a moment or two, you
decided with complete confidence that oracle soup can’t be real—you andeveryone else who reads the account.
Interestingly, though, despite our collective certainty on this matter, most of
us struggle to explain how we know oracle soup can’t be real. Our explanations
tend to be nothing more than restatements of our conviction that soup simply
can’t do such things. Children are content with those assurances, but adults
surely ought to be able to do better. What makes us so sure oracle soup isn’t real,then?
To ask a related question, how would we make sense of oracle soup if it werereal? If we reflect on that for a moment, I think we would agree that no ordinary
explanation would seem adequate for something so extraordinary. But if this istrue, how can the evolutionary explanation of life not provoke that same
skepticism? According to Darwin, each form of life owes its existence to a long
succession of accidents—small mistakes of the kind that just happen from timeto time. Anyone desiring a more lofty view of life can attribute these accidents to
God if they wish, but Darwin’s point, defended by evolutionary biologists to thisday, is that no one has to do so. However skillfully the brush of natural selection
appears to have picked hues from the palette of genetic mutations and appliedthem to the canvas of life, there’s no need to think a personal hand ever guided
that brush. We might just as well believe God guides each raindrop as it falls to
the ground. The fact is, raindrops form and fall in accordance with certain wellknown laws of physics, so nothing about rain ought to make anyone
uncomfortable with leaving it at that. Rain happens. Life happens.
Rain comes from clouds, whereas life, according to Darwin’s speculation,
originally came from soup. Not from oracle soup but from primordial soup—the“warm little pond” Darwin described in a letter to his friend Joseph Hooker in
1871.1 But if my claims about oracle soup were suspiciously extravagant, it’s
hard to see how Darwin’s claims about primordial soup can avoid similarsuspicion. To believe in primordial soup is, after all, to believe that a pool ofmineral water set a process in motion that ultimately produced not just thegenetic instructions carried by every form of earthly life but also innumerable
marvels that go well beyond mere instructions—actual working wonders, likebrains and compound eyes and adaptive immune systems and submicroscopic
molecular machines, to name just a few.
In other words, the most peculiar aspect of Darwinism isn’t that it takes
credit for things that seem too extraordinary to be explained but rather that the
explanation offered seems too ordinary for the job. The account of oracle soup ispeculiar only in the first respect, and that was enough for us to dismiss it. Our
skepticism would surely persist even if we witnessed a demonstration of oracle
soup in action, because we would still find it easier to dismiss the demonstration
as a clever trick than to accept the idea of a mysterious power working in soup.
Only if oracle soup managed to stand up to all attempts by expert skeptics todebunk it would we reluctantly accept the idea that a mysterious power really is
at work—carefully assembling messages with the pasta letters. Indeed, it’s hard
to imagine how else we would come to terms with the evidence. What’s
absolutely certain is that we would never accept the ordinary causes of physics
and chance as explanations, because those causes are so clearly inadequate.
To be clear, I’m not suggesting that the falsity of the oracle soup story
justifies rejecting the primordial soup story. There are obvious differences
between the two, which we will examine in due course. For the moment, I’m
simply saying that since we apply the same intuition to all accounts ofremarkable occurrences, we shouldn’t be surprised to find that the evolutionary
story seems counterintuitive at times, even to those who accept it.
Berkeley psychology professor Alison Gopnik described the challenge thiscauses for teachers of evolution in a recent Wall Street Journal column. “Byelementary-school age,” she wrote, “children start to invoke an ultimate Godlike designer to explain the complexity of the world around them—even children
brought up as atheists.”2 In fact, Deborah Kelemen, a psychology professor at
Boston University, found that even highly trained scientists are unable to fully
rid themselves of the innate impression that there is purpose underlying theliving world. According to her, “Even though advanced scientific training canreduce acceptance of scientifically inaccurate teleological explanations, it cannot
erase a tenacious early-emerging human tendency to find purpose in nature.”3
Whether her materialistic presupposition will stand up to scrutiny remains to beseen, but her observation clearly affirms the universality and power of thisdesign intuition.
THE UNIVERSAL DESIGN INTUITION
As a scientist, I recognize the need for caution here. Intuitions are such slipperythings that we can hardly give an adequate firsthand account of them, much lessa general account for all of humanity. Thankfully, we can proceed withsomething much more modest. In a moment I’ll give one plausible account of
how we might quickly decide that some outcomes can’t be explained as
accidents. Whether the method I describe is the one we actually use is lessimportant than whether it justifies our conclusions. Specifically, we want toknow whether the intuition that makes us doubt Darwin’s theory is sound. If theanswer to this is yes, as I think our journey will confirm, then Darwin’s theory isin trouble whether or not we ever have a fully satisfactory account of how
intuitions work.
With that qualification, I think the intuition by which we immediately
perceive certain things to be the products of purposeful intent is close to the ideathat some things are too good to be true. This expression doesn’t mean that goodthings can’t happen; it means certain good things can’t just happen. They nevercome out of thin air. They only happen if someone makes them happen. We
apply this insight to get-rich-quick schemes, for example, because they portray
financial success as though it requires no skill or effort, whereas experience tells

us otherwise. This hints at a universal rule for deciding what can and can’t be
attributed to accidental causes, which I’ll state as follows:
THE UNIVERSAL DESIGN INTUITION
Tasks that we would need knowledge to accomplish can be accomplishedonly by someone who has that knowledge.
In other words, whenever we think we would be unable to achieve aparticular useful result without first learning how, we judge that result to beunattainable by accident.
Again, whether there is one standard way we reach these judgments is not
crucial to what follows. We don’t even have to decide yet whether the rule iscorrect as stated. For now, the important point is that we all reach thesejudgments, often unanimously, and this rule fits these judgments reasonably
well. I use the term universal design intuition—or simply design intuition—torefer to this common human faculty by which we intuit design.
As we proceed, it will become clear that I have something more ambitious inmind. I intend to show that the universal design intuition is reliable whenproperly used and, moreover, that it provides a solid refutation of Darwin’s
explanation for life. We’ll have to think beyond our most familiar intuitions toreach that conclusion, but familiar points of reference will remain in sight
throughout the journey. If the destination can be reached that way, as I believe it
can, then having reached it, you will be fully capable of leading others along thesame path.
The design intuition is utterly simple. Can you make an omelet? Can you
button a shirt? Can you wrap a present? Can you put sheets on a bed? Tasks likethese are so ordinary that we give them little thought, and yet we weren’t bornwith the ability to do them. Most of the training we received occurred so early inlife that we may struggle to recall it, but we have only to look at a young person
still in the training years to be reminded that all of us had to be taught. Whether
we taught ourselves these skills or were taught by others, the point is thatknowledge had to be acquired in the form of practical know-how. Everyday
experience consistently shows us that even simple tasks like these neveraccomplish themselves. If no one makes breakfast, then breakfast goes unmade.
Likewise for cleaning up after breakfast, for making the bed, and so on.

Of course, this is anything but new. Plutarch, a first-century Greek historian,captured the universal design intuition nicely in an essay called “Fortune”(meaning chance):
But can it be that those things which are most important and mostessential for happiness do not call for intelligence, nor have any part in
the processes of reason and forethought? Nobody wets clay with waterand leaves it, assuming that by chance and accidentally there will bebricks, nor after providing himself with wool and leather does he sit
down with a prayer to Chance that they turn into a cloak and shoes forhim.4
According to the design intuition, neither bricks nor shoes get made unlesssomeone makes them. As familiar as this intuition is, it turns out to have huge
implications for biological origins, because the claimed exceptions are soconcentrated there. And what dramatic exceptions they are! Bricks don’t get
made until someone makes them (or today, until someone makes the machinethat makes them), but somehow much more complex things, like dragonflies andhorses, did get made without anyone making them, we are told.
If you think this riddle has a solution that leaves evolutionary biology intact,
I hope to convince you otherwise before our journey ends. To whet your appetite
for what’s to come, spend a moment contemplating a striking contrast ofcomplexity. At the very low end of the scale are the many simple, everyday tasks
that require very little thought, like the making of a bed, but that we know fromexperience are never accomplished without someone working to accomplish
them. These things are far too simple to fascinate us but evidently toocomplicated to be done by accident. This realization seems to justify our sensethat nothing impressive ever does happen by accident. Far beyond such simple
things are the pinnacles of human technology, like robots and communications
satellites and smartphones, which we also know can’t appear by accident.
Finally, at the highest reaches of the complexity scale are the true masterpieces—things like hummingbirds and dolphins—all of them alive, all of them eluding
our best efforts to understand them. Some technophiles like to think that humaningenuity will one day produce their equal, and good things will surely comefrom rising to that challenge. To me, though, speaking as a fellow technophile,
those masterpieces look positively untouchable.
I aim to give you a better sense of what I mean by this later in our journey.

The next step toward resolving the conflict within, however, will be to gain abetter understanding of what this thing we call “science” really is. For that, we’ll
focus less on scientific questions than on the scientific culture within whichthese questions are raised and answered.

CHAPTER 3

SCIENCE IN THE REAL WORLD
Determined to resolve the conflict between the design intuition and Darwin’s
theory, I spent much of my spare time from 1988 to 1990—the end of my Ph.D.
years—reading as much as I could about evolution. I wanted to know who else
was wading against the stream, and I was encouraged to find a few impressive
skeptics. Several of these skeptics had given talks at a symposium organized in
Philadelphia back in 1966 under the eyebrow-raising title “Mathematical
Challenges to the Neo-Darwinian Interpretation of Evolution”: Marcel
Schützenberger from the University of Paris; Stanislaw Ulam at Los Alamos
National Laboratory; MIT’s Murray Eden—people who aren’t easily ignored.
Their talks, transcribed and published the following year,1 presented thoughts at
various stages of refinement. These short papers lacked the weight of finishedresearch projects, but to my mind they amply demonstrated the need for suchprojects. The very fact that serious scientists were thinking and expressing theseanti-Darwinian thoughts was intriguing.
Slightly troubling was the fact that in the twenty-some years between the
symposium and my reading of it, nothing as healthy as that gathering seemed tohave occurred again. It was as though a monumental train of thought had
somehow not been allowed to continue its course. A few brave books in those
years had challenged the evolutionary story on scientific grounds, most notably
Michael Denton’s Evolution: A Theory in Crisis, published in 1985.2 But theapparent lack of any gathering of scientists at an established scientific institution
to carry this critique of Darwin’s theory forward suggested to me that thescientific establishment was not at all in favor of it. What had happened in
Philadelphia in the late 1960s seemed, anyway, not to be possible anywhere in
the late 1980s. For me, this weird opposition, if that’s what it was, made theopposed work even more attractive. On top of the obvious intellectual
importance was the danger-sport-like adrenaline rush that comes from being ascientific renegade.

I was in. If opposition prevented me from openly stating my aim as I
embarked upon this dangerous career path, then I would keep my aim private.
TINY DESIGNSWhat I found most intriguing in the small body of technical literature thatchallenged Darwin’s theory was the improbability of characters becoming
arranged into long functional sequences by accident. This is exactly what madeus so suspicious of oracle soup. There the characters were alphabetic letters, andthe functional sequences were written instructions. We knew intuitively that theaccidental arrangement of pasta letters into instructions is so fantastically
improbable that it can’t happen.
The same intuition—the design intuition—applies to functional sequences
built from any kind of character set, from the zeros and ones of computer code to
the hieroglyphs on the Rosetta Stone. Fascinatingly, the molecular underpinningsof life provide two more prime examples: gene sequences and protein sequences.
We will get to genes in a minute. As for proteins, these are the molecules
responsible for most of the cellular activities of life. By rough analogy, if weliken a cell to a car, then the individual protein molecules within the cell are likethe individual mechanical parts of the car—proteins are that crucial to life. Each
protein molecule is a long chain of connected “characters” called amino acids.
These amino acids are small molecules with standard connectors on both ends
and a protruding part in the middle. The twenty natural amino acids differ onlyin these protruding parts, which I’ll refer to as appendages (see Figure 3.1).3 If
the sequence of amino acids along a newly made protein chain has the rightproperties, the whole chain folds up automatically (or nearly so4) inside the cell
to form a compact three-dimensional structure. Like wire sculptures made fromsingle wires, proteins can take on a great many different shapes, but unlike awire, most protein molecules have a single preferred folded shape, the details of
which are crucial to its function. Just as the parts of a machine must be shaped
correctly to do their various jobs, so it is with proteins.
The preferred shape of each protein turns out to be specified by the sequenceof amino acids along the length of its chain. But that raises an interestingquestion: How do cells “know” what these sequences should be? The answer lies
in genes and the genetic code. Each protein molecule is constructed by linking
amino acids according to sequence instructions carried by a gene. There’s a trickto reading these genetic instructions, though. DNA consists of four types ofcharacters joined in sequence, whereas proteins consist of twenty amino-acidcharacters joined in sequence. A code is therefore needed for cells to translatesequences of four into sequences of twenty. Life has precisely such a code: thefamous genetic code that was cracked in the late 1960s (see Figure 3.2).

Figure 3.1 The construction of proteins from amino acids. Most living cells use the same basic set oftwenty amino acids depicted in the upper left (with artistic license). Amino acids are linked one by one, inthe precise sequence specified by a gene, to form a long, flexible chain-like molecule (upper right). The
amino-acid sequences specified by most natural genes have the highly special property of causing the wholechain to fold into a well-defined three-dimensional structure, an example of which is shown in the lower
left. Scientists use simplified representations to make it easier to see the features of these folded protein
structures, the most common one being the “ribbon” diagram, shown for the same protein (called betalactamase) in the lower right. Each coil in a ribbon diagram represents an element of structure called analpha helix, and each arrow represents a beta strand. These two elements make up most of the structures ofall proteins, with the connections between the elements called turns or loops. Although the loops look
floppy, like spaghetti, they usually have a firmly fixed structure just like the rest of the protein.

Figure 3.2 Genes and the genetic code that cells use to translate them. For our purposes, think of a gene as astretch of chromosomal DNA. DNA chains are made from characters that, like amino acids, differ in their
appendages. The DNA appendages are called bases. Because these bases come in only four kinds(represented by the letters A, C, G, and T), it takes a group of three consecutive bases, called a codon, to
specify any one of the twenty amino acids.5 A highly sophisticated molecular system involving about ahundred specialized proteins is used to interpret each of the 64 possible codon sequences as specifying oneof the twenty amino acids (or the end of the protein chain, represented by the hand symbol). The end result
is the set of codon “meanings” that we refer to as the genetic code, often represented in the form of a table,
as shown.

As we trace the source of proteins back, we see that the genetic code
explains how the sequence instructions for proteins are encoded in their genes.
But that raises another pressing question: How did the various forms of life
acquire these necessary genes in the first place? Here our design intuition
clashes with the scientific consensus, which attributes genes and proteins andeverything else to accidental causes. As Michael Denton put it, “The intuitive
feeling that pure chance could never have achieved the degree of complexity andingenuity so ubiquitous in nature has been a continuing source of scepticism eversince the publication of [On the Origin of Species].”6This skepticism kept coming up in the critiques of evolution I was reading in
the late 1980s. Denton’s book described the problem this way:
There are, in fact, both theoretical and empirical grounds for believingthat the a priori rules which govern function in an amino acid sequence
are relatively stringent. If this is the case . . . it would mean thatfunctional proteins could well be exceedingly rare. . . . As it can easily beshown that no more than 1040 [1 followed by 40 zeros] possible proteinscould have ever existed on earth since its formation, this means that, if
protein functions reside in sequences any less probable than one in 1040,
it becomes increasingly unlikely that any functional proteins could ever
have been discovered by chance on earth.7
Simply put, it seemed likely to Denton that protein science was poised todisprove Darwin. I agreed, and I wanted more than anything to do this science.
Within a few years, my pursuit of that ambition took me to Cambridge,
England. Working first in the Department of Chemistry at Cambridge University,
I soon came to realize that opposition was not the only thing that had kept
scientists from settling the matter Denton and others had raised. The kinds ofexperiments that were needed were easy to describe in theoretical terms, but theyturned out not to be so easy to nail down in practical terms. The basic idea wasto put Denton’s claim that “functional proteins could well be exceedingly rare”
to a decisive test. Doing this would require more experience and more careful
thought.
In pursuit of this experience, I eventually landed at another major research
center in Cambridge, this one having a rather extraordinary history behind it.
THE HUMANNESS OF GENIUS
Housed within an unimpressive box-like building at the south end of Cambridge
was the highly impressive Laboratory of Molecular Biology—the LMB. Withinmonths of opening its doors in 1962, the LMB could boast three Nobel Prizes
shared among its scientists. Fred Sanger was the sole winner of the chemistry
prize in 1958 for his discovery of the amino-acid sequence of insulin. The
second and third prizes both came in 1962, one going to James Watson andFrancis Crick for discovering, along with Maurice Wilkins, the double-helix
structure of DNA, and the other going to Max Perutz and John Kendrew for
discovering the first protein structures. Many more LMB Nobel laureates havebeen named since then, but the intellectual thrust that propelled the lab into highorbit traces back to the explosive success of that small initial group of people,
originally headed by Max Perutz.
In September of 1999, I paid a visit to an office at the LMB that reflected thecharacter of the man who occupied it, humble and tidy. Max stood opposite me,slightly hunched, using a wood lectern to support himself. Pain in his back made

sitting difficult. Indeed, his body showed all of his eighty-five years, but his
mind and his work schedule were those of a much younger man. Although he
had long since handed leadership of the LMB over to others, he continued towalk the halls almost daily, keeping abreast of the latest research and evencontributing to a project here and there.

Figure 3.3 The “brick box” that served as the home of the Medical Research Council’s Laboratory of
Molecular Biology (MRC LMB) from 1962 to 2013.
Laboratory of Molecular Biology, Cambridge, James King-Holmes/Science Photo Library (for illustrative
purposes only).

Figure 3.4 Six Nobel Prize winners at the Nobel ceremonies in Stockholm in 1962, four of them associatedwith the research groups that formed the LMB that year. Shown from left to right are Maurice Wilkins, Max
Perutz, Francis Crick, John Steinbeck, James Watson, and John Kendrew. Crick and Watson, both
associated with the groups that formed the LMB, shared with Wilkins the prize for physiology or medicine,
while Perutz and Kendrew—both LMB leaders—shared the prize for chemistry. Steinbeck received theprize for literature.
Six Nobel Prize Winners, NYPL/SCIENCE SOURCE/Science Photo Library.

On his lectern were twenty-six sheets of paper that represented more than ayear of my work. I was taking a calculated risk. A prevalent idea at the time wasthat proteins were not particularly fussy about the sequence of amino acids along
their chains, and even less fussy about the identities of the amino acids that end
up on the outside of their folded structures. According to many scientists then,
all a protein needed in order to fold was an appropriate placement of waterloving and water-repelling amino-acid appendages along the chain. About five ofthe twenty appendages can be classified as water-repelling and seven or so can
be classified as water-loving (the rest fall in between), so you can see how thissimplified view would, if correct, make it much easier for evolution to findamino-acid sequences that fold to form new protein structures (Figure 3.5). In
effect, the difficulty of arranging twenty kinds of appendages into a stablestructure would be reduced to that of arranging just three kinds of appendages:
water-loving, water-repelling, and ambivalent.
My paper opened by connecting this simplified view to work Max had donein the late 1960s. I knew this connection could backfire, though, because the restof the paper described experiments that clearly showed the simplified view to beincorrect. Even I found this result surprising. My experiments had been
performed on two different enzymes—the general term for proteins that perform
specific chemical transformations. Having shown in 1996 that a particular small
enzyme continued to do its chemistry even after all its interior amino acids had
been randomly replaced with water-repelling alternatives,8 I had assumed theexterior would be content with any combination of water-loving amino acids.

Figure 3.5 The simplified view of protein structure formation. All three images depict the same small
protein, called chymotrypsin inhibitor 2. The sandwich-like packing of an alpha helix onto a group of beta
strands (called a beta sheet) is shown with the appendages that stabilize this structure visible (right) or
hidden (upper left). The tumbleweed appearance with the appendages is deceptive. Although you can see
through the protein in this stick representation, a surface representation (peek ahead at Figure 7.5 for an
example) would show that water can’t enter the interior. The importance of excluding water from theinterior by placing water-repelling appendages there was what led to the simplified view.

This turned out to be untrue. Shortly after I started the work, it became clearthat both of the enzymes I was testing were completely inactivated after just a
fraction of their exteriors were replaced in this haphazard way. I responded byredesigning the experiments, carefully replacing exterior amino acids in groupsof five or ten, not haphazardly but with alternatives that were the most similar.
Again, both enzymes were ruined in the process, long before their exteriors had
been fully replaced.
The fact that the amino-acid replacements were now very conservative madethis a significant result because it contradicted the prevailing view so clearly.
These two proteins were much more fussy about the identities of amino acids ontheir exteriors than I and most other scientists had assumed, and moreover, themethod by which I had shown this suggested the same was true of other proteins.
In short, I had shown that the ability of proteins to keep working after a small
number of their amino acids are replaced—one of the main justifications of thesimplified view—didn’t mean that these changes were harmless. It only meant

the harm had not yet reached the breaking point. The breaking point is always
reached as more changes are introduced, even changes of the conservative kind I
was using.
My hope during the week or so between handing my paper to Max andsitting down to hear his thoughts was that any unease this new finding might stirin him would be offset by his appreciation of the clarity of the result. If all wentaccording to my plan, I would leave the room with a strong endorsement fromone of the greatest scientists alive, which would surely pave the way for mypaper to be published in an elite scientific journal.
This was not to be. I listened politely as Max, in a state of mild agitation,complained about things that, to my mind, had nothing to do with the substanceof my work. The man I had hoped to impress was annoyed instead. “I was very
disappointed with the level of my exchange with Max Perutz,” I wrote to afriend a short time later. Thankfully, other experts viewed my paper morefavorably. One of these, himself a prominent protein scientist at the LMB,
described my findings as “both startling and convincing.” So after passing thetest of peer review, my paper was published in the Journal of Molecular Biology(JMB) in August of 2000.9
Much later, with the benefit of years of reflection, I came to a newunderstanding of my meeting with Max. As difficult as our interaction in his
office had been for me, I began to realize that he had shown me something more
important that day than anything I had been hoping to show him. What I learned
will sound too obvious to be profound, and indeed, although it is obvious, thishappens to be one of those obvious truths we easily lose sight of: Max Perutz,
the small giant who deservedly occupies a position in the history of science well
above that of most Nobel Laureates, was as human as you and I are.
Somehow, with the conferring of rare honors, with the establishment ofscholarship funds and the dedication of buildings that bear a person’s name, withoil portraits and marble busts and postage stamps bearing a person’s likeness,with the passing of the person in the flesh and the growth of a legend to take hisor her place—somehow the fallible aspects of humanness we most easily relate
to evaporate, leaving us with an image that hovers midway between heaven andearth, neither divine enough to be worshipped nor human enough to be hugged.
Perhaps this tendency to idolize the legends of science is connected to askewed view of the whole scientific enterprise. Many of us, including me, havebought into the idea that science, though practiced by humans, has managed torid itself of the human flaws that leave their mark on every other humanundertaking. The purity of science is guaranteed by the rigor of “the scientificmethod,” we think.
Astrophysicist Neil deGrasse Tyson described this utopian view as follows in
the first episode of the Cosmos: A Spacetime Odyssey television series:
This adventure is made possible by generations of searchers strictly
adhering to a simple set of rules: test ideas by experiment andobservation; build on those ideas that pass the test; reject the ones that
fail; follow the evidence wherever it leads; and question everything.
Accept these terms, and the cosmos is yours.10
That all sounds very nice. And if ideas could be tested with a meter, the way
batteries and fuses can, then Tyson’s simple rules would work. But if we intend
to question everything, perhaps we should begin by questioning whether thehuman testing of human ideas can really be so simple, considering how
complicated humans are.
Nowhere are these complications more evident than in the discussion of big
ideas that touch the way we live, because here we find that everyone—scientists
included—has a strongly held view. And the very biggest ideas are those thatoffer answers to the all-important question of how we got here. We should by allmeans trust the scientific community to tell us how many moons orbit Neptune
or how many protons are packed into the nucleus of a cobalt atom. Why would
anyone distort facts of that kind? Matters where everyone wants to see things acertain way, however, are a completely different story. With those we should
always apply a healthy dose of skepticism.
Many of us have bought into the idea that science, though practiced byhumans, has managed to rid itself of human flaws. But if we intend toquestion everything, perhaps we should begin by questioning whether thehuman testing of human ideas can be so simple, considering how
complicated humans are.

FROM UTOPIAN SCIENCE TO AUTHORITARIAN SCIENCE
Having not yet come to appreciate this human factor fully, I was quite confident

by 2000 not just that the scientific facts were at odds with the evolutionary story
but also that with the right protein experiment I could reverse the stream ofscientific consensus by proving so. I hadn’t done this key experiment yet, but I
knew how it would be done. Holding a utopian view of science very much likethe one Tyson describes, I was convinced that no matter how startling a scientificresult may be, no matter how many scientists may react with incredulity or how
many textbooks may have to be rewritten, science always sides with the truth in
the end. And maybe it does. But had I seen myself as less exceptional,
recognizing that many other scientists had been offering similarly weighty
challenges to Darwinism for well over a century, I might have reached thesobering realization of how long the scientific community can take to settle on
the truth.
Oddly enough, I now see how the pursuit of prestige—so evident in my own
life—goes a long way toward explaining how science gets stuck on certain
wrong ideas. In the professional world of science, prestige is bestowed in theform of praise, and not just any praise but the rare praise of those who arethemselves most highly praised. Knowing how fickle praise can be, though, why
would anyone assume that praiseworthy science always gets the praise it
deserves? The sight of true words eliciting a strongly negative response isfamiliar to everyone, in all walks of life. Why, then, would anyone believe thatthe road to scientific truth and the road to scientific prestige are one and thesame?
The answer, I think, is that when we fall for the utopian view of science,
truth and prestige do appear to be on the same road. If we assume scientists are
single-mindedly driven by the quest for truth and nothing else, then we expect
those scientists with the keenest perception of the truth to rise to the top. These
top-notch scientists form an elite body of experts whose consensus opinion is thesurest indicator of the truth there is. Prestige and truth then seem inseparable, as
though they are just two different names for the same destination. And we need
only follow the road a short way toward this destination to see that it is also theroad to authoritarian science. With the truth perceived to be so reliably in thehands of the elites, we ordinary folks need not concern ourselves with the details
when the elites are challenged. Instead, we wait patiently for them to deliver
their official response, which is sure to be correct, we assume.
Of course, as a challenger of the consensus view of biological origins, I had
to concern myself with the details, but I was strangely confident that thechallenge I was mounting would compel the scientific authorities to concede out

of sheer inability to oppose the truth. Confidence can be a good thing, but inretrospect, I see that mine was tainted with pride, which is not a good thing. I say
this because my intent in showing you the less flattering side of science is not tomake me look good or others look bad, and certainly not to make science lookbad. My purpose is instead to promote a realistic view of humanity and of
science as a human undertaking. After all, we won’t really love science until welearn to love real science—not a hypothetical pursuit in a utopian world but an
intrinsically human pursuit in this world, however imperfect.
What happened next turned out to be just the right medicine for my pride,
though not the sort I would have prescribed for myself.

CHAPTER 4OUTSIDE THE BOX
Under the directorship of Alan Fersht, whom I mentioned in chapter 1, theCentre for Protein Engineering—or CPE, as we knew it—occupied a buildingthat was joined by a connecting corridor to the brick box that housed the LMB.
For the most part, the engineering done by the forty or so scientists at the CPE
consisted of designing small alterations to natural proteins in order to study how
their chains fold into compact structures. One project, though, had a much more
ambitious form of engineering in mind.
While I was doing the work that led to the 2000 JMB paper,1 a colleague ofmine, Myriam Altamirano, was attempting to re-engineer a natural enzyme inorder to make it perform the function of a different enzyme. Like many otherscientists at the time, she was using a hybrid approach that combined aspects ofdesign with aspects of evolution. In all of these projects, the idea was first to
make informed guesses as to what parts of the original enzyme should bechanged and how, and then, after implementing these changes, to use thestandard laboratory version of evolution (mutate select repeat) to sort out any
minor problems. Although this strategy could work in theory, the limitations
have become increasingly apparent in the years since. Eleven years later, someof the leaders in the field conceded that “efforts to date to generate novel
catalysts have primarily demonstrated that we are getting good at making bad
enzymes. Making good enzymes will require a whole new level of insight, or
new methodologies altogether.”2
The crux of the problem is that the evolutionary step at the end accomplishes
so little that success rests almost entirely on the ability to make the right guesses
in the first place. But, of course, if we knew how to do that, the evolutionary stepwould be largely superfluous. In other words, evolution seems to be an
inadequate replacement for knowledge. Indeed, if our design intuition proves
true, nothing is an adequate replacement for knowledge.
Very good informed guesses, however, are tantamount to knowledge, and inthis case Myriam’s guesses seemed to be that good. She found that her evolved
engineered enzyme worked as well as the natural enzyme it was designed toimitate—a remarkable feat in a field where the term “success” usually had to be
applied very generously. After writing up her results, Myriam submitted her
paper for publication in the prestigious journal Nature around the time I met withMax Perutz. Her paper passed Nature’s peer review and appeared in February of
2000.3A GROUP WITHOUT A LEADER
Hoping Myriam’s strong success would pave the way for more success, as isoften the way in science, several Ph.D. students began to work under her
supervision on projects that extended her method to other enzymes. But
technical challenges began to present themselves, and just as this was becoming
evident, the students suddenly found themselves without a leader. In late 2001,
Myriam unexpectedly left the CPE. As the director of the CPE, Alan knew hewould have to find someone to take her place, and since his own work had neverfocused on protein evolution, he knew he would have to look to someone else.
The rapid three-year timetable for completing a Ph.D. in the British system madethe situation all the more urgent for the students who had been in her charge.
Knowing that my work was increasingly touching on protein evolution, Alan
approached me. After stressing the significance of Myriam’s work, underscoredby her paper in Nature, he spoke with me about the students who had been
stranded without Myriam, ending with words to the effect of “You know a lot
about protein evolution, Doug.” I knew he was offering to hand the leadership of
this group of students to me, but I didn’t see how I could accept. Although Alansaw that I was doing careful, critical work that touched on protein evolution, he
didn’t know the details of my current project, and he probably underestimatedthe degree of my evolutionary skepticism. Myriam’s group was abuzz with theidea that evolution could work wonders, whereas I had come to the opposite
conclusion. How could I lead a group of people who seemed to be heading in a
direction opposite of mine?
The indirectness of Alan’s offer enabled me to decline indirectly, which is
not my usual style. In this case, however, I took the easy option. By not saying I
would lead Myriam’s group, I conveyed to Alan that I wasn’t interested inleading her group without having to explain why.

SCIENCE WITH AMBITION
I had been proceeding with caution for a long time. Even before that aha
moment I recounted at the beginning of chapter 2, I had been a quiet critic ofmaterialism. My views were known to close friends, but they went no further
than that. Written declarations of my thoughts were restricted to the bulletinboard in my student room, which was cluttered with personal proverbs. One wasa higher version of the design intuition: “It is intuitively obvious to me that amere collection of atoms cannot attain consciousness. It can never become awareof its own existence.” Another supported that higher intuition with a simple
argument. I deduced from the reality of human free will that humans can’t bematerial things, and “therefore, man did not evolve from the physical.”I never intended to keep silent forever, though. My plan all along was tocontinue thinking and working carefully in the hope of solidifying my early
design intuitions and eventually earning the opportunity to communicate thempublicly. If and when that time came, I was sure that science would be the best
podium from which to speak. My utopian version of science wasn’t contradictedby anything I knew at the time. I understood that people had their biases, and I
had seen the prejudicial attitudes of anti-faith scientists. But the scientificarguments in defense of the design intuition seemed incomplete to me, andbecause I felt certain a complete argument could be made, I held to the idea that
this argument would be widely accepted.
Now, if you’re wondering whether it’s legitimate for scientists to hope for aparticular result when they set their goals, I can assure you that it is. We do this
all the time. The search for extraterrestrial intelligence is a well-known example.
SETI involves the work of many scientists who hope their search will one day
prove successful. They have no proof, but science never starts with proof. Like
every other worthwhile undertaking, science starts with ambition. The same
could be said of the many scientists who devote themselves to finding cures forvarious diseases. There is no proof that these long-sought cures will be found,but the goal and the ambition are there, and this is no small thing. Scientificproof never comes without those key ingredients.
Harm comes to science not by people hoping to find a particular result but
by people trying to suppress results that go against their hopes.

When we consider who has the power to suppress unwelcome results, we see
right away that the view most likely to cause suppression is the majority view ofthe scientific community.
A PERFECT STORM
In early 2002, scarcely a month after I passed up Alan’s offer to assume
leadership of Myriam’s group, there was discussion in the LMB cafeteria of a
possible problem with the results reported in Myriam’s Nature paper two years
earlier. It sounded serious. A graduate student who had been sorting through thestorage tubes in Myriam’s freezer had found that the labels on certain criticaltubes didn’t match the contents, and most troubling of all, the re-engineered
enzyme that had received so much attention seemed not to work. A sinking
feeling descended on the whole lab at the thought of several graduate students
having spent a year or more of their precious time on projects that werepredicated on a mistake.
Within days of the first mention of the inconsistencies, the nightmare wasconfirmed. The storage tube investigation revealed that Myriam had found her
enzyme to perform as well as the natural enzyme because it was the natural
enzyme. As in all laboratory selection experiments, she had looked for signs ofbacterial growth under conditions where growth can’t occur unless the desired
function is present. In this case, however, nothing should have grown on her
petri dishes because neither her designed changes nor the subsequent mutationalvariations on those changes actually caused the desired function. By accidental
cross-contamination, a few cells of the strain with the natural enzyme had been
mixed in with the cells that couldn’t grow. This meant her positive result was
really a false positive. A brief note of retraction soon appeared in Nature, leaving
no doubt as to the status of the paper that had been published in 2000: “Weconclude that the results are unsound.”4
As if these internal events were not creating enough tension, the intelligent
design (ID) view of biological origins was beginning to make headlines in the
UK in connection with escalating controversy over the teaching of alternatives toDarwinism in state-funded schools. As my boss, Alan knew I had been receiving
fellowship and research money from the major funder of ID work, the Discovery
Institute, for several years. He had never asked me to explain why Discovery
was interested in my work, and being well aware that the connection tointelligent design could generate controversy, I never brought it up. Alan had
earlier mentioned the Discovery Institute website, so I presumed he had madethe connection himself and was not bothered enough by it to discuss it with me.
But the hostile treatment of ID by the British news media seemed to be
having an effect on him. I was the first person in the lab one morning in
February of 2002. Alan usually made his rounds through the labs later in the day
when work was in full swing, but on this morning he dropped in early to have aword with me. He seemed tense. He approached me as if there were a pressing
matter he needed to discuss, yet he seemed unable to initiate the discussion. I
assumed what burdened him was the question of whether he could allow me tocontinue my work at the CPE, knowing that I was a part of this thing being
portrayed so publicly in such awful, conspiratorial terms.
There’s no easy way to initiate a conversation like that, but any otherconversation would miss the point. And if my future at the CPE was indeed thepoint, the point was missed. After mentioning that he had just listened to a BBC
radio program discussing intelligent design, Alan put a few questions to me,somewhat awkwardly.
“You know this William Dembski fellow, don’t you?”“Yes.”“And you know about his intelligent design theory.”“Yes.”“Tell me, then, who is the designer?”
That was the top question asked by critics of intelligent design back then.
They thought the answer would expose deception on the part of ID proponents.
Their underlying assumption was that ID proponents were being coy about theidentity of the designer of life in order to construct a version of creationism that,by avoiding the G-word, could be taught in American public schools. In reality,
the question only exposed confusion as to what ID is.
HOW TO SPOT A FAKE ID
The truth is that ID and creationism have always differed fundamentally in their
methods and starting assumptions. Creationism starts with a commitment to aparticular understanding of the biblical text of Genesis and aims to reconcile
scientific data with that understanding. ID, on the other hand, starts with acommitment to the essential principles of science and shows how thoseprinciples ultimately compel us to attribute life to a purposeful inventor—anintelligent designer. ID authors settle for this vague description not because theywant to smuggle God into science but because the jump from “intelligent
designer” to “God” requires something beyond the essential principles ofscience.
The confusion over ID really stems from broader confusion as to what theseessential principles are. Intelligent design takes a minimalist view. If science isthe application of reason and observation to discover objective truths about thephysical world, then doing science requires accepting just a few things—none ofthem controversial. First, we must accept that objective truths exist, as we all
naturally do. Then we must accept that some of these truths pertain to thephysical world, and that some of those that do can be discovered through humanobservation and reasoning. Since we all engage in this discovery process from anearly age, we all naturally accept these propositions.
There is nothing more.
In fact, adding anything to this essential set of propositions causes twoserious problems. First, the resulting embellished definition of science excludes
what shouldn’t be excluded, namely any work that adheres to the essential set
without adhering to the embellishment. For example, if a group of people wereto insist that science can’t be done properly without accepting that life exists onother planets, then that group will refuse to consider any work done from acontrary perspective, even though this work may be perfectly legitimate science.
Worse, embellishments run the risk of pressuring scientists into accepting wrong
answers by ruling the right answers “unscientific.”
As odd as this situation may seem, it’s not hypothetical. The scientistic view
introduced in the first chapter—scientism—is the most striking example of anembellished version of science that has risen to prominence. The reason
adherents to this version hold science to be the only legitimate source of truth isthat they also hold to materialism. This commits them to the idea that there isn’t
anything but physical stuff, and because science is the only way to know thetruth about physical stuff, this leads them to conclude that science is the only
source of truth. The materialist commitment itself, though, is completely
unnecessary to science and therefore a harmful embellishment.
Later in our journey we’ll see how scientism unravels with the unraveling ofmaterialism. Our design intuition will turn out to be good science, whereas
scientism will turn out to be bad philosophy. For now, just notice that scientism
makes itself vulnerable by hitching itself to materialism, which has no place inscience.

THE IDES OF MARCH
Alan’s questioning didn’t seem to lead anywhere on that February morning, but
the mounting tension surrounding intelligent design in 2002, and the way thistension amplified the problems caused by the collapse of Myriam’s result, leftme thinking my time at the CPE might be coming to an end. If I could somehow
become the solution to these problems, though, my position would become
secure, I reasoned. I had passed up the opportunity to lead Myriam’s students
because our projects were pointed in opposite directions. Now that their projects
were on the verge of being abandoned, however, the idea of salvaging them byviewing them in reverse seemed promising. In other words, if I could get Alanand the students to consider interpreting their results not as proof that converting
enzymes to new functions was easy but as proof that it was hard, then I would be
happy to provide the needed leadership. I proposed a meeting to discuss thisidea. Alan was very receptive, as were the students, so the meeting wasscheduled for the final week of February 2002.
My gross underestimation of the difficulty of getting people to change theway they think in an hour or two is humorous to me now, but none of thisseemed funny at the time. With visuals prepared and the outline of my argument
well rehearsed, I took up the challenge of convincing the Herchel Smith
Professor of Organic Chemistry at Cambridge University, who also happened to
be a Fellow of the Royal Society and the director of the Cambridge Centre forProtein Engineering, along with half a dozen graduate students that their view ofprotein origins was incorrect, and that the failed projects could be combined withmy project to make a strong case for the correct view.
Needless to say, my pitch was not a smashing success.
Years later, an article in New Scientist magazine about Biologic Institute(titled “The God Lab”5) revealed that one of my fellow scientists at the CPE had
been pressing Alan to dismiss me because of my connection to ID. The article
says Alan refused to do so, quoting him as saying, “I have always been fairly
easy-going about people working in the lab. I said I was not going to throw himout. What he was doing was asking legitimate questions about how a protein
folded.” According to the article, I left the CPE after “Axe and Fersht were indispute with each other over the implications of work going on in Fersht’s lab.”
The truth is that Alan did, in the end, give in to the internal whistle-blower
who wanted me removed, though I certainly accept his account of having
resisted this for some time. When he did finally act, I interpreted theawkwardness of his action as an indication of his reluctance. There was no heartto-heart conversation or even a word spoken face-to-face. When everyone
gathered in the customary way to bid me farewell, Alan was conspicuously
absent. All I received was an e-mail from Alan’s assistant on the eleventh ofMarch 2002, succinctly stating that the CPE was “very short of [lab] bench
space” and declaring Alan’s solution: “Please vacate as soon as possible and by
the end of March latest.”
Evidently the needed space matched my dimensions exactly, so, after saying
my good-byes to everyone present, I said good-bye to the CPE and to the brickbox at the other end of the corridor: the LMB.
CONSCIENCE AND COURAGE
The truth is that I may well have made the same decision if I had been in Alan’s
position. After all, challenging the evolutionary story was my calling, not Alan’s.
I am the one who accepted the risk of pursuing research I knew would lead to aconfrontation with the scientific establishment. Since I had never consulted Alanon that aspect of my direction, it would have been presumptuous of me to think
he would be willing to shoulder some of that risk himself.
Further confirmation of the risks came from all directions over the course ofthat week in March 2002. Heading into the weekend, The Guardian, a major
British newspaper, ran a story on Friday afternoon, March 8, that began with its
particularly alarmist version of whistle-blowing:
Fundamentalist Christians who do not believe in evolution have taken
control of a state-funded secondary school in England. In a development
which will astonish many British parents, creationist teachers at the city
technology college in Gateshead are undermining the scientific teachingof biology in favour of persuading pupils of the literal truth of the Bible.6
That set a whole gaggle of whistle-blowers off, and within days Prime
Minister Tony Blair was fielding questions on the matter in the House ofCommons.7 Meanwhile, on Monday and Tuesday, March 11 and 12, the New
York newspaper Newsday ran a two-part series under the heading Creation vs.
Evolution,8 which included the following provocative reference to my work:
In the meantime, intelligent-design advocates have pointed to a third line

of research as “the most promising development in the next few years”
and yet another potential roadblock to evolution. The research, by
Douglas Axe of the Centre for Protein Engineering in Cambridge,
England, introduces a concept called “extreme functional sensitivity” that
relates a protein’s specialized function to the changes permitted in its
amino acid sequence. Axe’s premises [sic] are hinted at in an article
published two years ago in the Journal of Molecular Biology, but[William] Dembski and others say Axe plans to go public with his full
findings soon and “shake things up.”9
I had said nothing so provocative. Newsday reporter Bryn Nelson had asked
me at the beginning of March whether I thought the results of my 2000 JMB
paper meant that the enzymes I studied didn’t originate by evolution. I was
careful to restrict my response to what was presented in the paper:
I don’t think the data presented in the JMB paper allow one to draw thisconclusion. That paper does reveal that the constraints imposed byfunction on sequence are unexpectedly high, and this raises some
important questions that need to be explored further and which I hope to
explore further.10
Indeed, as I had just disclosed to Alan and the graduate students, I was
exploring those questions further, and I had a sense of where the results werepointing, but the last thing I wanted to do was compromise my research by
talking about unfinished work with a reporter.
The media storm soon dissipated, and in the end, I was able to complete theproject I described to Alan and the graduate students at the Babraham Institute,
located just outside Cambridge. Like the prior study, this one was accepted for
publication in JMB, appearing in August of 2004.11
The tension continued after the storm, though, and still continues today, as
does the scientistic interpretation of this tension. According to this now-familiar
view, people of faith who challenge Darwinism are really pushing religion, even
if their challenge has a scientific look to it. That being so, we need to warn
everyone not to be deceived by appearances. Blow your whistles! The religious
agenda is the enemy that threatens science, so all enlightened people should
defend science against this enemy, we’re told.12
The real problem for science, however, is not people having agendas (as they

always do) but rather the institutionalization of agendas. This is theembellishment problem we discussed earlier. Once an embellished view ofscience becomes established, active suppression of dissent becomes inevitable,with predictable consequences. Everything that opposes the institutionalized
agenda is labeled “anti-science” by those working to protect the agenda, and thefear of that label quickly enforces compliance among the timid.
Something even greater than science is at stake here. To see this, we need togo back to the question we considered at the outset: To what or to whom do weowe our existence? Pondering this, we see that the most significant cost ofgiving in to the whistle-blowers is not violation of our sense of fair play but
participation in the systematic devaluation of human life. It is the cost ofremaining quiet as young people who innately know themselves to be thehandiwork of a “God-like designer” are indoctrinated with the message that they
are instead cosmic accidents—the transient by-products of natural selection.
University of Washington psychology professor David Barash brings the
sanctioned message to two hundred undergraduates every year in his course on
animal behavior. With professorial authority, he declares to his young captive
audience, “The more we know of evolution, the more unavoidable is theconclusion that living things, including human beings, are produced by a natural,
totally amoral process, with no indication of a benevolent, controlling creator.”13
His agenda, clearly, is to treat human behavior as just another example of animal
behavior, all of which he thinks is ultimately explained by evolution.
If this explanation turns out to be untrue, then his indoctrination is apredictable tragedy. Barash believes the falsehood that was instilled in him when
he was a student, and having believed it, he dutifully assumes responsibility forinstilling the same falsehood in other young people. But the fact that his actions
are predictable makes them no less destructive. Contemplate for just a moment
the dystopian vision of a generation of human beings believing in their hearts
that they are nothing more than bestial accidents fending for themselves in aworld where morality is a fiction, and you begin to grasp the true stakes.
Heroes are badly needed here, and we have every reason to think they willtake their conspicuous stand in each generation. After all, having whistles blown
on you is a small price to pay for the privilege of defending the existence ofmoral truths. If you think these heroes need to have Ph.D.s, I hope to convince
you otherwise in the next chapter. When it comes to defending the big questionof our origin, everyone is scientifically qualified.

Figure 4.1 Barry Palevitz, a University of Georgia biologist and a contributing editor to a monthly
magazine called The Scientist, epitomized the whistle-blowing mentality with this e-mail, which came justafter I left the CPE. Because I knew anything I said in reply could appear in The Scientist, embedded in“pro-science” commentary from Palevitz, his reference to my reputation being besmirched had the sound of
a school-yard bully taunting his next victim: What’s the matter, ya little wimp? Afraid yer gonna get a blackeye?

CHAPTER 5

A DOSE OF COMMON SCIENCE
Despite the opposition, by 2004 I was confident that I had confirmed Michael
Denton’s hunch that “functional proteins could well be exceedingly rare.”1 As
quoted in chapter 3, Denton reckoned that accidental processes would beincapable of finding new functional proteins if their amino-acid sequences weremore rare than about one in 1040 (1 followed by 40 zeros). Having now
completed the experiments I described to Alan Fersht and the graduate students
in 2002, I was able to put a number on the actual rarity—a startling number.
With only one good protein sequence for every 1074 bad ones, I had found
functional
proteinstoberoughly
10,000,000,000,000,000,000,000,000,000,000,000– fold more rare than
Denton’s criterion! Unless this number was overturned somehow, a decisive
blow had been dealt to the idea that proteins arose from accidental causes.
Nevertheless, my expectation that this would compel evolutionary biologists
to hang “Out of Business” signs on their doors proved unrealistic. The stream ofscientific consensus continued to flow in Darwin’s direction throughout 2004,
and it still does. I continue to press for the change of thinking I was pressing forthen, and this change is as unwelcome now as ever. Real science is nothing likethe utopian version I held at the beginning of my journey. The flag ofmaterialism I mentioned in chapter 1 still flies proudly over the academy, andpeople working under that banner are expected to show due respect. Any serious
opposition will bring the color guard out in full force, to the sound of blowing
whistles.
That much is obvious to me. The harder question is how to advance the truthin the face of this opposition. My early recognition of the need to put Darwin’s
theory to a rigorous technical test compelled me to devote two decades of mycareer to that need. I’m convinced those were years well spent, and yet I’ve also
become convinced of this equally important complementary need: since mostpeople will never master technical arguments, there is a desperate need for anontechnical argument that stands on its own merits, independent of any
technical work.
As an expert who has been directly involved in many of the scientific studies
described in the following chapters, I know the conclusions my coworkers and I
have drawn are correct, and I know why the good work of others that gets used
to argue against our work doesn’t support those arguments. I could try to impartthis knowledge to readers of this book, I suppose, but no matter how many
chapters I devote to this, nonexperts will still be nonexperts after they turn thelast page.
Does this matter? I’d like to say that it doesn’t, and yet I have to admit that it
does. I am just one expert among many, most of whom either disagree with myconclusion or are reluctant to admit that they agree. The simple accounts ofprotein research I give in the coming chapters are therefore sure to be criticizedby other experts, which will leave nonexperts in the position of trying to figureout which scientists to believe. Now, if Darwin was as wrong as I believe hewas, his theory can’t possibly be defended as clearly and convincingly as it canbe refuted. I will devote a whole chapter to that point. Nevertheless even poor
arguments might seem to benefit from the status of the people making them.
When all is said and done, then, nonexpert observers inevitably find themselves
unable to do anything better with technical debates than trying to follow themand score them. That never settles the matter, though, because being scored thewinner of a debate isn’t the same thing as being correct.
For me there is no debate. The scientific facts are in complete harmony withthe universal design intuition. The work my colleagues and I have done onproteins has completely resolved the internal conflict—for me. Resolving theinternal conflict for you, however, will require something more. What is needed
isn’t a simplified version of a technical argument but a demonstration that thebasic argument in its purest form really is simple, not technical.
As I thought about how to approach this, it occurred to me that I need to
begin by correcting the misconception that science is something most of us will
never do.
Because most people will never master technical arguments, there is adesperate need for a nontechnical argument that stands on its own merits,
independent of any technical work.

ALL HUMANS ARE SCIENTISTS
We tend to overlook two key facts. One is that everyone validates their design
intuition through firsthand experience. The other is that this experience isscientific in nature. It really is. Basic science is an integral part of how we live.
We are all careful observers of our world. We all make mental notes of what we
observe. We all use those notes to build conceptual models of how things work.
And we all continually refine these models as needed. Without doubt, this isscience. I have called it common science to emphasize the connection tocommon sense.
We embark on our quest to understand the world at a tender age. Long before
we walk, we have constructed simple mental models of gravity and balance.
Long before we put our hands to art, we have acquired notions of color, shape,and form. Long before we speak, we have learned to classify things into
categories that await the terms we eventually use to refer to them. All of thesemodel-building activities, and many more, use innate mental ability to processdata—the information we receive from the world by observing it. Of course, we
engage in these activities so naturally that we don’t think of them in technicalterms. My point is that they really are scientific in nature, whether or not wethink of them that way.
For the most part, professional scientists respect this broadly inclusive viewof science. Planetary scientists speak of the sun rising and setting just as the restof us do. Why? Because those terms represent our common experience more
simply and directly than a physically correct description based on the earth’s
rotation. Likewise, teachers introduce the technical understanding of sunrise andsunset by connecting it in a clear way to their students’ more intuitive
understanding. Children are not treated as fools for thinking the sun rises in theeast and sets in the west because teachers know prior understanding is crucial tothe development of refined understanding. The simple model isn’t wrong in thesense of giving false predictions but merely incomplete in that it offers no causal
insight. Children readily grasp the more complete model when they see how
their simpler model fits within it.
This tendency to view prior understanding as a foundation for refined
understanding, even in cases where the new replaces the old, continues into
adulthood. No teacher of Newton’s laws of motion starts by telling students toabandon their prior understanding of how things move. Telling young people
who have mastered swimming and cycling and skateboarding that they have noexperience of motion or no valid understanding of it would be ridiculous, just as
it would be ridiculous to tell students at the next stage of their physics instructionthat everything they learned about Newtonian mechanics is wrong. Everyone
seems to recognize that the project of refining understanding presupposes both ageneral respect for understanding and a humble recognition that it is never
perfect or complete.
Oddly, these basic courtesies are withheld when it comes to the universal
design intuition. The story of oracle soup convinced us we all have this intuition,
and we now see in simple terms how common science supports it. Bricks andbreakfasts are made only if someone makes them. We know of no exceptions.
With that assurance, we confidently apply the same intuition to primordial soup
—only to be told we’re wrong.
The people who correct us make no serious attempt to refine the design
intuition in order to explain why it would work for one soup but not the other.
We’re simply expected to ignore the discrepancy. Apparently, our otherwise
trustworthy design intuition must be overruled for the sake of Darwin’s theory.
But intuitions aren’t easily overruled. The psychology professors I quoted inchapter 2, Alison Gopnik and Deborah Kelemen, are acutely aware of this. Their
proposed solution is for teachers to begin replacing their students’ design
intuition with the counterintuitive evolutionary alternative at an early age. As
Gopnik put it, “The secret may be to reach children with the right theory before
the wrong one is too firmly in place.”2 But if the design intuition is a product ofcommon science, then surely to oppose it in the name of science is to make a big
mistake.
OPEN SCIENCE
The realization that everyone proves qualified to do science by actually doing
science is good news in multiple respects. First, this open view of science dispels
the elitist myth I accepted as part of my utopian view of science. We can let thatmyth go without denying the existence of exceptional talent. The point is thateven the most gifted people are still people—prone to all the internal tensions
and contradictions that affect all humans. None of us rises above these common
imperfections. Max Perutz didn’t, and neither does anyone else.
Next, open science brings an end to authoritarian science by emphasizing thescientific value of public opinion. Because everyone practices common science,public reception of scientific claims is arguably the most significant form of peer
review. For professional scientists to assume that public skepticism toward theirideas can only be caused by public ignorance is just plain arrogant. If ignorance
is the cause, clearer teaching should be the remedy. When that proves elusive or
ineffective, professional scientists need to be willing to find fault with theirideas, not the public.
This leads to the third piece of good news: Embracing open scienceempowers people who will never earn Ph.D.s to become full participants in thescientific debates that matter to them. Instead of merely following expert
debates, nonexperts should expect important issues that touch their lives to beframed in terms of common science. Once they are, everyone becomes qualified
to enter the debate. This doesn’t apply to intrinsically technical subjects, ofcourse, but the matters of deepest importance to how we live are neverintrinsically technical.
TRUTH, PLAIN AND SIMPLE
According to the universal design intuition, tasks that we would need knowledge
to accomplish can be accomplished only by someone who has that knowledge.
The observation in the previous chapter that “making good enzymes will require
a whole new level of insight”3 seems to fit that intuition. Good enzymes comeonly from insight, and whatever the ingredients of primordial soup might be,
insight isn’t one of them. The results my colleagues and I have found over many
years of working with enzymes also agree with the design intuition. When we
examine the proposed ways in which accidental evolutionary processes aresupposed to have invented enzymes without insight, we consistently find these
proposals to be implausible.
The key to finding a nontechnical path to this same conclusion, I think, is tostep back from the experiments that keep showing the implausibility ofevolutionary scenarios and ask if there could be a simple reason why this isalways so. Surely our immediate sense that instructions can’t just surface byaccident in alphabet soup is based on some simple, sound principle. And surely
this same principle, whatever it is, must also explain why the remarkableproteins we call enzymes can’t happen by accident. The universal design
intuition stated in chapter 2 is a law, of sorts, that describes what is impossible,
so there must be a simple explanation for why this law holds. The question, then,is why are tasks that we would need knowledge to accomplish neveraccomplished without knowledge?
The answer to this will become clear over the next four chapters, and as
expected, common science will be the source. The key point to carry with us isthat we shouldn’t shy away from affirming the universal design intuition justbecause it contradicts the scientific consensus. The community of professional
scientists is a reliable source for uncontroversial facts, but as we have seen andwill continue to see, this community has a habit of stepping well outside thatboundary—or, at least, scientists claiming the authority of this community do.
Keep that in mind, and remember:
People who lack formal scientific credentials are nonetheless qualified to
speak with authority on matters of common science.

CHAPTER 6

LIFE IS GOOD
Having established that we’re all capable of thinking like scientists and that we
can’t blindly accept how professional scientists think about life, our next step isto think about how we think about life.
“Wow factor” explains some of life’s appeal, particularly in its more exotic
forms, but what makes life uniquely attractive to us must be deeper than “wow.”
I believe it’s something closer to purpose. Tornadoes rank high on the wow
index because of their enormous power. But while tornadoes do what they dowith great intensity, they don’t try to do what they do. Spiders, on the other hand,
try to catch insects, even as those insects try to escape from their captors’ webs.
The fear that tornadoes evoke in us is as real as the danger they pose, but the fearof a crouching cougar is palpably different in that it’s a fear of harmful intent.
There are no mind games to be played with a tornado because a tornado has nomind. Cougars are another matter.
Whether the actions of much simpler forms of life, such as the strange
morphing of the foraging amoeba, involve awareness at some rudimentary levelis anyone’s guess. I suspect an amoeba is more like a machine than a cougar inthat respect, though possibly very unlike a machine in others. There is at least asuperficial resemblance between certain machines and simple forms of life. For
example, if I had to pick a kind of machine that resembles amoebas, it would be
those creeping robots used to clean swimming pools. They forage endlessly fordebris instead of food, but their movements are almost lifelike in theircomplexity.
Pool robots should convince us that a thing need not be conscious in orderfor us to perceive intent when we observe it. Anyone watching from poolsidewould notice that the little details of the robot’s momentary behavior—crawlingalong the pool bottom, climbing the wall, audibly sucking up water and debris as
it reaches the surface, turning back into the water—add up in a coherent way to ahigher level of behavior that we associate with purpose. Someone seeing a poolrobot in action for the first time would piece these observations together after
watching for a few minutes: “Aha! That gizmo is cleaning the pool!”
The same goes for life—only more so. A child’s first experience watching a
spider building a web brings particular excitement at the point when all the little
busy movements are seen to add up to a whole design that is visually striking. In
this the child recognizes intent even if the function of the web remains
mysterious. And so do we. The whole result takes on a conceptual significancethat rises above anything we perceive in the small momentary actions
themselves—the bending of a leg joint, the grasping or releasing of a fiber, thestarting or stopping of silk extrusion. We can easily imagine a succession ofsimilar small actions adding up to nothing but a mess, but what we see instead is
nothing of the kind. The little actions turn out to be significant because they
produce a significant end, and we can’t avoid the conviction that this was theintended end. The busy little spider was busy for a reason.
Activity doesn’t always produce that conviction. Sometimes the total effectis just a simple sum of the momentary effects. A little rain on the street produces
small puddles, then bigger ones if it continues. But even if the rain continues
until the street is flooded beyond use, we aren’t left with the impression that therain or the clouds intended to close the street. Rain gives no appearance of being
clever, no appearance of having imagined something and then labored skillfully
to bring it about. In sharp contrast to the work of the spider, heavy rain has no
greater conceptual significance than light rain. Much rain may bring with it
important practical consequences, but we need no new concepts to understandthis. If you know what rain and much mean, then you know what much rainmeans.
Rain happens, but life doesn’t just happen—or at least this is what I hope toconvince you of. Life is so different from rain that we will need new vocabularyeven to think about it clearly.
BUSY WHOLES AND WHOLE PROJECTS
According to the Oxford dictionary, a whole is “a thing that is complete initself.” Spiders and pool robots are wholes in this sense, whereas piles of sandand thunderstorms are not. Conditions that shorten a thunderstorm or actions that
divide a sand pile leave us with things that are comparable to the original,
though smaller. By contrast, dissection of a spider or disassembly of a pool robot
leaves us with remnants or pieces—things that aren’t at all comparable to thewholes from which they came.
The same can be said of a carbon atom or of the sun—both havecharacteristics that don’t come from a simple sum of their parts—yet neither ofthese objects manifests intent the way a spider and a pool robot do. We therefore
have in the spider and the pool robot examples of a special kind of whole—thekind that manifests intent by undertaking and completing a project. Before
developing this idea further, I should say that the existence of this special classof wholes doesn’t in any way imply that the things that lie outside it, things likeatoms and stars, are unintended or unremarkable. My point is simply that noneof those excluded things labors the way a spider or pool robot do, as though they
have their own intent.
We need a term to describe these special wholes—the ones that do look as
though they’re trying to accomplish something. As a simple way of conveying
the underlying idea, I’ll refer to such things as busy wholes. A busy whole, then,is an active thing that causes us to perceive intent because it accomplishes a big
result by bringing many small things or circumstances together in just the rightway. The big result is also a whole, which we will call a whole project. So busywholes are whole things that tackle whole projects. When we see a finishedwhole project and recognize it as such, we automatically perceive intent,
whether or not we saw how it was accomplished.
TWO TERMS WE WILL BE USING
whole project:a big result accomplished only by bringing many small things orcircumstances together in just the right way
busy whole:an active thing that accomplishes a whole project
Our design intuition offers a clear interpretation of this perception. On
recognizing a situation or an object to be a finished whole project, we realizethat work was required to bring it to completion. More specifically, we realizethat skilled work was required—work that brought the right things together inthe right way. In our experience, skill always requires discernment—the ability
to distinguish the right things from the wrong things and the right way from thewrong way—and discernment in turn requires knowledge. The moment werecognize this—that a project that requires knowledge has been completed—we
immediately infer that one or more knowers must have been behind the work.
This follows naturally from our design intuition.
Notice that this reasoning moves from the result—the completed project—tothe active thing that did the work. Also notice that knowledge and intent are
inferred in a way that doesn’t require us to know who knew or intended. When
we watch a pool robot do its work, we see that all its little actions add up to acompleted whole project: the cleaning of a pool. We know that tackling suchprojects requires knowledge, and our design intuition tells us there’s no
substitute for knowledge. But we don’t for a moment think the busy whole that
did the work—the pool robot—knows anything. Instead, we recognize that the
robot is the successful outcome of a much more impressive whole project,
namely the design and manufacture of a working pool robot. The scores of busywholes who contributed to that project were human beings: inventors, engineers,designers, machinists, assembly-line workers, project managers, and so on. So
the knowledge and intent we perceive when we observe the pool robot in
operation is ultimately traceable to human knowledge and intent, though theperception occurs whether or not we do the tracing.
Busy wholes tackle their projects by breaking them down into smaller
projects in an organized way. Big projects are divided into smaller subprojects,
which may themselves require further division. As long as the subprojects arecomplex enough to qualify as whole projects, we perceive their accomplishment
to be driven by intent, and whatever does the accomplishing is therefore a busywhole. In other words, large busy wholes tend to have layers of smaller busywholes within them, each dedicated to tackling its own subproject.
These ideas are more familiar than they sound. For example, winning atennis match may be a whole project for a tennis player. Her success, however, iscritically dependent on too many subprojects for us to list. One is the transfer ofoxygen and carbon dioxide to and from her blood, which is a whole project initself. The busy whole undertaking the top-level project (playing tennis) is ahuman being, whereas the busy wholes undertaking the major physiologicalprocesses supporting that top-level project are systems and organs within her
body. She has a pair of lungs, busy wholes hard at work tackling the breathing
subproject, hopefully well enough that she can focus on tennis. Working alongwith her lungs on the breathing subproject are other busy wholes, such as her
nervous system and her diaphragm. And as you might expect, the projects being
accomplished by each of these anatomical busy wholes may be further

subdivided into projects assigned to tissues, and then to cells, and then to
subcellular structures and intercellular interactions, and finally down to themolecules of life.
Now, the question that most interests us is whether anyone intended for ourlungs and the cells within them to tackle their respective projects the way thetennis player intends to win her match. Are we right to infer purposeful design
when we watch the human body—or any living body—in action, the way weinfer it when we watch the pool robot? The answer to this will emerge as we
continue, but the points to grasp here are more modest. First, rightly or wrongly,
we’re naturally inclined to think that things like organs and cells were intended,and second, a commonsense rationale can be offered for this inclination. Again,
whether the rationale I’ve offered is the one we actually use isn’t our concern.
Rather, our interest is to decide whether the inclinations themselves are correct.
As our journey continues, I will build a case for thinking they are correct,
but my objective is as much to inspire as it is to convince. If Darwin’s theory has
left us with an impoverished view of life—as I believe it has—then there is as
much to be gained by articulating a more satisfying view of life as there is byshowing that Darwin was wrong. I hope to do both.
OF SALMON AND ORCA
I have come to think that everything about a salmon is salmon and everything
about an orca is orca. Having worked in molecular biology for decades, I know
the similarities between these two aquatic animals are real and significant, but I
confess that this head knowledge vanishes when I watch mature salmon, having
spent most of their lives in the salty waters of the Pacific, fighting their way
upstream through freshwater to reach the place where their lives began. Their
mission literally consumes them. Forsaking all food, they sacrifice every ounceof their flesh, launching themselves over and into rocks as they battle their way
up rapids—all for their final purpose of parenting offspring they won’t live to
see.
The salmon’s way of passing the baton from one generation to the next may
look brutal to us, but that concern doesn’t seem to have crossed their minds. Nor
has it crossed mine on the occasions when I’ve watched them. In theiruncompromising determination, these magnificent creatures make it abundantly
clear that they’re doing exactly what they were meant to do—like heroes andheroines rushing into their last battle.

Most of them perish in earlier battles. I spent a day watching this too, with asmall group of friends on a whale-watching boat in the Strait of Juan de Fuca.
Orcas, often called killer whales, spend their long lives in family groups called
pods. They’re the most formidable hunters of the ocean, fearing nothing andfeeding on whatever looks good to them, including the otherwise invincible great
white shark. Like sharks, orcas kill, but the way orcas kill is altogether different.
They are clever and graceful, as greatly to be admired by us as they are to befeared by fish.
The captain of our vessel, an expert orca watcher, located a large school ofsalmon with his sonar equipment. With the engine off, we sat above the schoolfor several minutes and watched the whales do their thing . . . with style. It
quickly became evident to me that these creatures are smart enough to know
they’re being watched and gregarious enough to seize any opportunity to show
off. As though executing a play from their hunting playbook, they confined thesalmon by using a corralling technique where pod members take up positions
around the perimeter of the school to prevent it from dispersing. From ourabove-water vantage point the signs of this were occasional spouting at somedistance from the boat in all directions. The salmon, of course, had a much betterview of what was happening, though presumably not the favorable impression ofit that we had.
What we saw from the deck of the boat was unforgettable. These elegant
show-offs took turns swimming at high speed through the trapped school ofsalmon, gobbling one or two with each pass and celebrating their success withbreathtaking high breaches—five tons of slick black and white launching out of
the water with implausible ease. Gravity was repealed for a moment as they took
to the air. In the space of a breath—the half second I needed to untangle seeing
from believing—flight actually crossed my mind, only to be dispelled by thethunderous crash of reentry. How such extremes of mass and grace can possibly
reside in the same skin remains a mystery to me.
The thought that this brief spectacle meant quite a few salmon would nevermake their heroic end-of-life journey only occurred to me later. When it did, thesalmon saga again seemed more like valor than tragedy—not because salmon
can be virtuous but because there is something intrinsically beautiful about what
they are and something magnificent about the intensity with which they live that
out. What emerges from their heroism is deeply compelling.
Orcas are equally compelling in their own distinctive way. And somehow—
for me, anyway—the fact that part of what it means to be a salmon is to sacrificeyourself or some of your relatives to feed the orcas makes neither species lessmagnificent or less compelling.
LIFE à LA DARWIN
If there’s anything compelling about Darwin’s view of life, it’s the simplicity of
his core idea. Underlying the jumble of ideas that evolutionary biology has
become is one crisp principle: things with the ability to reproduce themselvesautomatically carry the potential to produce descendants that are better
reproducers. Few theorized explanations are so disarmingly direct. The perpetual
improvement of reproducers seems to require only (1) that they carry out theirreproduction imperfectly—with small errors (mutations) being introduced
occasionally—and (2) that at least some of these errors enhance reproduction, if
only slightly.
The problems with this idea will become clear later. For now, I simply ask
how this explanation, if we accept it, ought to shape our picture of life.
Considering how innocuous the assumptions appear, the depth of theirimplications may come as a surprise. We are left to view the many kinds of life
much the way we view geological features: as things in constant flux. Mountains
seem permanent to us because they retain their shapes for long periods, yet weknow they’re constantly being reshaped by the natural forces that formed them.
The same must be true of life if, like the earth’s crust, it is constantly being
molded by unseen forces.
By this view, there must have been a simple ancestor of all animals, whose
offspring were pushed by natural selection in many different directions, likeleaves dispersed over water by convective currents. Modern animals must thenbe nothing more than the present locations of those drifting leaves. Each is likeone frame in a long time-lapse video—the snapshot of the day. The magnitude of
the cumulative changes may amaze us as we contemplate the staggering varietyof animals that came from that single ancestor, but nothing about the present
forms themselves should amaze us, as this would be like being amazed by one
frame in the middle of a long video. Presumably the descendants of today’s
spiders and whales and salmon will become as radically different again, given as
much time again.
Though I personally dislike this fluid view of life, I would have to come toterms with it if I were committed to the idea of natural selection being life’s
creator. That wouldn’t be easy. I would be constantly bothered by thecontradiction between this view and what I see when I open my eyes, because
life looks profoundly unlike geology to me. The things of geology are best
understood by grouping them into a relatively small number of categories,
whereas biology calls for a different approach. Serious pursuit of a satisfying
understanding of life’s distinct varieties forces us to abandon the idea thatthey’re all fundamentally the same thing: reproducers stumbling along toward
better reproduction. The spider, the salmon, and the orca will have none of that
idea. Each is strikingly compelling and complete, utterly committed to being
what it is. Each will finish heroically by death or even by extinction, but not by
surrendering to forces that would turn it into something else.
PERFECTION AND ITS CRITICS
This theme of commitment takes the idea of wholes to a new level by hinting at
the possibility that some wholes are what they are because they ought to be so—
as if they are expressions of something truer and more significant than any
temporary physical representation. The idea here is not that some things are sogood that they had to exist but rather that some things are so good that theycannot be other than what they are. The tapestry of human creativity is adorned
with several examples: a perfect musical composition, a perfect poem, a perfectmathematical proof—timeless treasures to be beheld but never to be reworked.
Life is the quintessential representation of this idea, utterly without rival
among human works. Forget the old textbook definition of life—something to
the effect of life being a self-perpetuating, nonequilibrium process based oncarbon chemistry and driven by the influx of solar energy. That never resonatedwith anyone who mused on life. No, life must be something much richer,immeasurably more worthy of our attention. Life is mystery and masterpiece—
an overflowing abundance of perfect compositions. You and I are among them,here for a brief time to delight in as many more as we possibly can.
Surely everyone senses the profound wonder of life. It seems too
overwhelming to be overlooked. Equally obvious is the tension between thissublime view of life and the explanation offered by Darwin. His idea that life
wanders from one variation to the next, never committing, always yielding to theblind force of natural selection, is plainly incompatible with the idea that thephysical forms of life are expressions of something deeper, something
immovable, something perfect.

Darwin’s idea that life wanders from one variation to the next, nevercommitting, always yielding to the blind force of natural selection, is
plainly incompatible with the idea that the physical forms of life areexpressions of something deeper, something immovable, something perfect.
So how might a person who’s reluctant to abandon Darwinism respond to
this high view of life? I’ve seen two approaches. The cruder of the two, andprobably the better known, is to downgrade the high view. Of the various
downgrade paths, one emphasizes aspects of life that we all agree are not right.
Birth defects, cancer, infectious diseases, parasites, suffering, and loss of
biodiversity are all disturbingly bad, so it’s reasonable to offer these as evidence
against any claim that life as we see it is comprehensively good. But my point ismore subtle than that. I’m not denying that the present state of life is troubling inmany respects. Rather, I’m affirming that something spectacularly good isclearly discernible even through the haze of trouble.
Another way of downgrading life is to assume the role of a bio-critic—
someone who looks for faults in the design of living things. As one example, thegiant panda has a protruding bone in its wrist that serves a thumb-like role,enabling the bear to grasp bamboo (Figure 6.1). The fact that this bone (called aradial sesamoid) isn’t a true jointed thumb like ours has led some people to view
it as a makeshift adaptation that no good designer would employ. Not
surprisingly, others argue that it is a good design. For my part, I find myself
evaluating the people more than the panda. None of these people, however
earnest they may be, have any deep grasp of the principles of design anddevelopment underlying sesamoid bones or thumbs, to say nothing of pandas.
Indeed, none of us do. Search the world’s top research centers and you’ll find noskeletal engineers—no one who has the faintest idea how to encase earthworms
in exoskeletons or how to endow leeches with backbones. Surely, then, our total
inability to answer these how questions categorically disqualifies us from serious
engagement of the higher why questions. We’re free to form opinions on thesematters, but they’re nothing more than that. My opinion, for those interested, isthat the giant panda is yet another example of something perfect—somethingthat is exactly as it should be.

Figure 6.1 Location and use of the radial sesamoid bone in the forepaw of the giant panda.

The better option for people who aren’t ready to part with Darwin’s theory is
to embrace life’s excellence in the hope that this will ultimately prove explicablein Darwinian terms. This option has the considerable advantage of affirming ourhigh view of life, but with that comes the challenge of making a square peg fit around hole. If natural selection is not just the master shaper but also the incessant
fiddler, as Darwin thought, then evolution never reaches a compelling end. In his
own words,
It may be said that natural selection is daily and hourly scrutinising,throughout the world, the slightest variations; rejecting those that are bad,preserving and adding up all that are good; silently and insensibly
working, whenever and wherever opportunity offers, at the improvementof each organic being in relation to its organic and inorganic conditionsof life.1
For Darwin, then, the thought of all the various evolutionary lines
terminating at ends that are too good to be altered would have been as
inconceivable as the thought of unchanging conditions. Local ecosystems andclimates experience one change after another, which means conditions neversettle into a permanent state, which means the work of natural selection is neverfinished. By contrast, the affirmation that there is something uniquely
compelling about living things as we now see them is an affirmation ofcompletion. It rejects the idea that the designs of life are like leaves drifting on apond, or like ever-changing mountains, or like frames in a video. So followers of
Darwin seem to be faced with the dilemma of deciding whether to believe their
theory or their eyes.
To understand this dilemma more clearly, try to imagine a plausible

evolutionary precursor of all modern animals. Having descended from the very
simplest life, this creature would have possessed only the most basic charactersfound in all modern animals, most notably a multicellular body that differs fromplants by lacking cell walls and photosynthesis. Among modern animals,
sponges come closest to meeting this description. So picture an ancient creatureof sponge-like simplicity.
Now, if this ancient sponge really produced the modern orca through a long
succession of intermediates, we should ask: What drove the astoundingtransformation of animal form along this particular line of descent? There seemto be only two possible evolutionary answers. Either the “conditions of life”
determined the form, or natural selection did. That is, either selection delivers
whatever the conditions of the day call for, or selection steers its own course to ahighly fit end, dealing with the changing conditions along the way. The first
implies that ancient sponge and modern orca are connected by a succession ofcomparably fit animal forms, whereas the second implies an upward progression
from the inferior ancient form to the superior modern one.
Both scenarios have issues. If we say conditions are in the driver’s seat,
we’re saying life is noncommittal to the point of incoherence—open to being
either a sponge or an orca or any of the subtle gradations supposed to span that
not-so-subtle gap. On the other hand, if we say selection is in control, then wecome uncomfortably close to personifying evolution, as though it had both thevision to know what it wanted to do with that crude sponge and the patience towalk it through a long period of awkward adolescence, knowing how good theend result would be.
WHY PROTEINS DON’T EVOLVE (ANYMORE)
The bigger question, though, is whether life is open to evolutionary reshaping at
all. The answer that has emerged with increasing clarity in recent years would
have surprised Darwin.
Some of the key facts take us back to the subject of proteins. To explain how
natural proteins, with their exquisite functions, could have appeared by accident
is a monumental challenge. This challenge can be divided into a more extreme
aspect and a less extreme aspect, both of which are proving to be major obstacles
for evolutionary theory. The more extreme challenge is to explain how mutations
and selection could have produced completely new structural themes forproteins, called folds (Figure 6.2). The less extreme challenge is to explain howmutations and selection could have produced functional variations on existing
fold themes.
My colleagues and I have studied both of these challenges. To focus on theless extreme one, biologist Ann Gauger and I chose to work with two strikingly
similar yet functionally distinct natural enzymes, which we’ll call enzyme A andenzyme B (Figure 6.3). Our aim was to determine whether it would be possible
for enzyme A to evolve the function of enzyme B within a time frame of billionsof years. If natural selection really coaxed sponges into becoming orcas in lesstime, inventing many new proteins along the way, we figured it should haveample power for this small transformation. But after carefully testing themutations most likely to cause this functional change, we concluded it probably
isn’t feasible by Darwinian evolution.2 Additional work supports this conclusion.
Mariclair Reeves—like Ann Gauger, a biologist at Biologic Institute—
painstakingly tested millions upon millions of random mutations, searching forany evolutionary possibility that we may have overlooked in our first study. She
found none.3

Figure 6.2 The distinction between structural themes and variations on a theme for proteins. Of thousandsof known structural themes, or folds, ten are shown as ribbon diagrams on the left (A). Notice the great
variety of folds that can be made from the two basic structural elements, the alpha helix and the beta strand.
Figure 6.2B shows two variations on the same fold theme. Although the boundary separating variations on atheme from differences of theme is imprecise, these two categories have proved useful for classifying
protein structures.

Figure 6.3 Both enzymes that Ann Gauger and I chose to study are formed by two identical protein
molecules that grip each other in a manner analogous to a handshake. Here you see the striking similarity
between the “hands” that form enzyme A and enzyme B (their actual names are Kbl and BioF, respectively).

We’ve received two good questions about this result from nonscientists. The
first is how it’s even possible to test a process that takes so long. Certainly wecan’t observe anything over eons, but you’re familiar with the possibility ofcalculating times for processes that are too slow to watch. To estimate how many
years it will take a young tree to reach a desired size, we measure the growthover one year and then compare this to the additional growth needed. Estimatesfor processes involving chance carry a slight twist. If you know the proportion oflottery entries that win each week, for example, then you know how many times
players should expect to have to enter before they win. Individual players will dobetter or worse than expected, but the average long-term result should be as
expected. Scientific theories that involve chance, as Darwin’s theory does, areanalyzed in much the same way. Unlike a lottery player, though, a scientifictheory can’t appeal to luck in hopes of beating the odds. Defenders of Darwin’s
theory must instead show that something comparable to life in its present
fullness is the expected outcome once simple life exists.
The second good question is whether scientists who accept Darwin’s
explanation of life also accept our conclusion that enzyme A can’t evolve towork like enzyme B. You may be surprised to hear that many of them do. In fact,
I’m not aware of anyone having challenged that conclusion. How, you may
wonder, can anyone believe that natural selection is incapable of such a tinytransformation while maintaining that it accomplished so many gargantuan ones?
The current answer from evolutionists is that natural selection is a victim of its
own success. That is, natural selection is now thought to have been so effective
at tailoring organisms to their environments that it did reach end points—
creatures so good at being what they are that they can no longer undergoevolutionary change.
Berkeley paleontologist Charles Marshall exemplifies this perspective in his
critical review4 of Stephen Meyer’s book Darwin’s Doubt.5 Meyer’s thesis isthat Darwin’s evolutionary mechanism is incapable of generating new animal
forms, in part because it’s incapable of generating new protein forms. In reply,
Marshall suggests that new animal forms evolved without any need of new
proteins.6 According to him and others, this was done by “rewiring” the gene
regulatory networks (GRNs) that control when and where existing genes areturned on within a developing embryo. Marshall concedes that experimental
alterations of these networks usually kill developing embryos, but he thinks thisshould be overlooked because “today’s GRNs have been overlain with half abillion years of evolutionary innovation (which accounts for their resistance tomodification), whereas GRNs at the time of the emergence of the phyla [thebasic animal forms] were not so encumbered.”
Marshall and I agree, then, that life in its present form resists evolutionarychange. We disagree on the likelihood of natural selection ever having done
anything remarkable, but we both end up favoring an explanation of life thatlooks more purposive than Darwin’s explanation. If natural selection reallyshaped life, it worked more like an artist shaping clay than erosion shaping
sandstone. It was skillful enough to transform the ordinary into the extraordinary,and wise enough to know when that work was finished.
The molecular version of that view has become the main criticism of theconclusion I reached with Ann Gauger and Mariclair Reeves. We were wrong,
critics say, to expect enzyme A to be capable of further evolution because
enzymes, like animals, have been perfected to the point where they’re no longer
pliable in the hands of natural selection. Dan Tawfik of the Weizmann Institute,
whom I know from my days in Cambridge, is a champion of this idea. Believingthat “broad-specificity enzymes served as progenitors for today’s specialist
enzymes,”7 Tawfik would presumably agree with the critics that Ann and I were
wrong to expect today’s specialist enzymes to evolve the way yesterday’s broadspecificity ones did.
Whether this latest version of evolutionary thinking is any more plausible
than previous versions will become clear as we proceed. To his credit, Tawfik
recognizes the difficulty of explaining how the supposed broad-specificity
enzymes would have arisen in the first place. Since they had to be true enzymes—folded proteins with geometrically complex active sites—it’s unclear what’s
been gained by proposing them as precursors. His own diagnosis of this isadmirably frank: “Evolution has this catch-22: Nothing evolves unless it alreadyexists.”8 In other words, don’t expect a working X (you name it) to come out of
the evolutionary process unless a working X went in.
Again I find myself in agreement, and that makes resolution of the dispute
among scientists seem hopeful. The most sensible question to ask next, though,will put this hope to the test: What’s left of a theory of origins once it has been
conceded that it doesn’t explain how things originate?
We’ve seen in this chapter that living things are exquisite wholes—socommitted to being what they are that they give the distinct impression of being
meant to be what they are. With that realization in mind, we’re ready to begin
scrutinizing the opposite view. If life was not meant to be, then it is accidental,
and of the very few suggestions for how it could be accidental, none has had
more hopes pinned on it than natural selection. Accordingly, we will use the next
chapter to examine natural selection under the powerful lens of common science.

CHAPTER 7

WAITING FOR WONDERSAll attempts to explain how Earth came to be teeming with life must face thechallenge of explaining extraordinary things. Ordinary physical causes seem
adequate for explaining things that aren’t task-oriented (things like atoms andstars and tornadoes), but our design intuition tells us those causes can’t explain
the things we’re calling busy wholes (things like spiders and pool robots). Many
scientists tell us otherwise, that ultimately everything is rooted in ordinary
physical processes. Those processes, they say, turned primordial soup into
simple life, and simple life into simple animals, and simple animals into complex
animals, some of whom make robots. If those scientists are right, extraordinary
things don’t really require extraordinary causes after all.
This doesn’t sit well with our design intuition, though. When we see working
things that came about only by bringing many parts together in the right way, we
find it impossible not to ascribe these inventions to purposeful action, and thispits our intuition against the evolutionary account. As our rejection of oracle
soup showed, people differ not in whether they have the design intuition but inwhether they have exempted evolution from it. We all agree that a spider’s web
is the product of the spider’s spinning instinct. The point in dispute is whether
anyone intended for spiders to have that instinct, or the body parts that enable it
to be used. If no one meant for spiders to spin, then spiders were invented by
accident, making our design intuition deceptive. If someone did, then spiders
were deliberately invented, making the evolutionary account deceptive.
The way forward is to recognize that whatever value we place on the design
intuition, we can certainly reason without it. Without rejecting intuition, we canlean instead on observation and calculation to decide whether we should expect auniverse like ours to produce busy wholes like spiders. The important question,
then, is whether evolutionary theory is more in touch with our observations thanour design intuition is.
Is it? What fact did Darwin cite that should, contrary to our intuition, make

us expect things like sponges to be converted into things like orcas? What cause
did he identify that has the power to make such extraordinary transformations soeasy they happened a million times over in different ways? What could possibly
tame such frightening improbabilities? The standard answer even today isnatural selection—the tendency of more fit organisms to have more offspring.
No one disputes this tendency, but can it really work these wonders?
ROBOTIC FOOTBALL FANS
A thought experiment will help point us to the answer. The one I have in mind
has to do with football, of all things. As every one who’s been to a professional
football game knows, football crowds are loud. This is true in the United States,
where footballs are oblong, and equally true in the rest of the world, where
they’re round. Fans of my local team, the Seattle Seahawks, have taken thephenomenon to what some would call an unhealthy extreme. Exactly twomonths before the Seahawks won Super Bowl XLVIII, their fans earned theworld record for the loudest crowd at an outdoor sporting event, reaching an earsplitting 137.6 decibels on the second day of December in 2013.1
Because football crowds are characteristically loud, then, might somethingwith absolutely no understanding be able to find its way to a football game justby seeking loudness? I’m thinking of a noise-seeking robot. Imagine aweatherproof robot that can be dropped by parachute to any location, land or sea.
Upon landing, it detaches its parachute and begins homing in on sources ofsound. First it uses a directional microphone to measure sound in all directions
from its present location. Then it swims or crawls a short distance in the
direction of the loudest measured sound, after which it stops to repeat themeasurement. This listen-and-move homing cycle is repeated long enough forthe small moves to add up to a considerable distance, though how far this takes
the robot will depend on how straight the course is.
The question is, what would have to happen for a robot of this kind to find its
way to a roaring football stadium? Being dropped within earshot of the crowd’sroar, or at least in close proximity of earshot, would be helpful. Even then all
kinds of things could go wrong. Competing sounds—like that of traffic on thestreets—could interfere. The football crowd would probably generate much
more noise than the traffic, but because sound falls off with distance, nearby
traffic may register as louder than distant cheering. Still, there is at least a small

hope that the robot would find its way to a game if it were dropped within
earshot of a stadium.
But suppose the drop point is entirely random—anywhere on Earth withequal likelihood. In this case, the odds of success would be very slim indeed.
Even when we take all the world’s football stadiums into account, the earth is solarge in comparison to the regions within earshot of stadiums that there’s little
chance of our robot hearing even the faintest sound of a football crowd. As
powerful as the crowd’s roar is inside any stadium, it’s completely inaudible
over most of the planet. Our poor robot would probably end up on a shoreline
somewhere, enticed by the sound of crashing waves. Even if it were to land in acity that has a football stadium, being drawn to an air conditioner or getting hit
by a bus would be more likely than making it to a football game (Figure 7.1).

Figure 7.1 The noise-seeking robot’s dilemma. Even in locations where the roar of the stadium crowd is
audible, there are competing sound sources. Although no single competing source is producing as muchsound as the crowd, the robot will register nearby sounds as louder than distant sounds. Combined with theabundance of competing sound sources, this makes homing much less reliable than it would otherwise be.

We can get a more accurate assessment by looking at some numbers. If weassume there are about two thousand major football stadiums in the world, eachof which can be heard up to about a kilometer away (about two-thirds of a mile),
then all of these within-earshot areas amount to about six thousand square
kilometers (about two thousand square miles). This is a meager thousandth of apercent of the earth’s half billion square kilometers of surface, which means theprobability of our robot landing at a spot where a football crowd can be heard—

if the timing is right—is a mere one in a hundred thousand.
Nevertheless the robot’s movements might bring it within earshot of a
stadium eventually. Success is unlikely in the short term, but if we suppose ourrobot runs on solar power and is built to last, the odds should increase with time.
Unhelpful noise sources will almost certainly be homed in on for a long time,
but eventually changes of circumstance will cause the robot to leave each ofthese distractions and move on to something new. This could happen in any
number of ways. Maybe the force of a wave or the paw of a curious bear will
push the robot to a location where new sounds are audible. Or perhaps the soundof thunder or of wind in the trees will distract the robot momentarily, just longenough to set it on a new course. Because occurrences like these are possible, it’s
only a matter of time before they happen. Our expectation, then, is that repeatedchanges of circumstance will eventually put the robot within earshot of a footballstadium. It may take years or decades or even centuries, but success must comein the end if the experiment continues long enough.
There’s something odd about this version of success, though. We started byasking whether the ability to seek noise might enable a robot to find a footballstadium, and now we’re invoking something other than noise-seeking to achieve
success. This other factor is repetition—repeated opportunities for rare favorable
circumstances to be stumbled upon. To the observer, this blind repetition carries
so little promise that it seems like nothing more than an interminable wait. Sure,
waiting is bound to work if it can be extended indefinitely. But if open-ended
waiting is really an option, just how significant was the homing ability in thefirst place? After all, even something completely passive—like a Styrofoam
packing peanut—might make its way into a football stadium if we wait longenough.
THE CONNECTION TO EVOLUTION
That same question of significance impinges on our discussion of evolution,
which motivated the thought experiment in the first place. In fact, there arestrong similarities between our robot and the evolution of a species, the main one
being that natural selection acts very much like homing. Just as the robot moves
toward the loudest noise as judged from its present location, so natural selection
tends to shift the genetic makeup of a species toward the highest fitness as
judged from its present members. The robot’s homing causes movement throughgeographic space; selection’s homing causes movement through an abstract

space, namely the genetic space consisting of all possible genome sequences.
Each movement in this genetic space consists of a change in the genome
sequence that typifies the species, taking many generations to complete.
Figure 7.2 shows what one of these changes might look like if we observed a
species long enough to watch it happen. The process is nothing more than a
gradual replacement of the most common genetic type (unmarked beetles, in thiscase) caused by the presence in the population of a more fit type (double-dot
beetles). In most actual cases the types wouldn’t be as visibly different as they
are in this hypothetical example. Furthermore, the observer wouldn’t reallyknow whether natural selection was the cause of the change, because transitions
like this often happen for reasons having nothing to do with fitness.
Nevertheless, when fitness is the cause, the process is akin to the stepwise
homing of our robot, as we will see in more detail in a moment.
Another similarity between our robot and the kind of genetic movement
we’re interested in is that for both we have a clear understanding of success. I
chose football stadiums as the robot’s objective because they’re highly
distinctive locations—numerous and varied but always noteworthy. Those same
adjectives apply even more profoundly to the living things that evolutionary
theory must explain. We aren’t asking whether natural selection causes just any
changes. Instead, we’re focusing on changes of the most noteworthy kind. We
want to pinpoint anything in the evolutionary mechanism that might have theastonishing inventive power that Darwin and his followers have attributed toevolution.

Figure 7.2 The visible work of natural selection on a hypothetical beetle species. Eight beetles represent the
makeup of the population at three points in time, many generations apart. By the final point, selection has
homed in on the double-dot variant, as seen by the fact that this now typifies the species.

SELECTION: EXIT STAGE LEFT
To that end, the most important thing we learned from our robot is that the mere
ability to home in on signal sources isn’t what brings success. Instead, successoccurs when the right kind of source happens to be close enough to outcompete
any other sources. We saw this when we recognized how unproductive homing
was unless the noise being followed happened to be from a nearby stadium. If
the analogy to evolution holds, we should expect something similar for thehoming caused by natural selection.
As Figure 7.3 shows, the situation is indeed similar. Like the robot
represented in the upper half of the figure, the species steps toward the weaker of
the two signal sources shown. In both cases this is because the weaker source iscloser and therefore more strongly sensed. The difference is that the robot
receives sound straight from the closer source, but the species must make dowith much less definitive information. All the species senses is the relative
fitness of the different genomes that currently exist among its members. Youmight think this amounts to a huge amount of information, considering how
many millions of individuals can belong to a species. However, the genetic
makeup of most individuals differs only negligibly from a great many others, so
relatively few genomic variations are in play at any time (represented by the dotsin the lower half of the figure). The homing action of natural selection is limited
to stepping from the current dot (labeled Initial location) to the best available dot(New location). The figure shows one such step. More often than not, the best
available location would be the current location, so no step would be taken.

Figure 7.3 Comparing a single step of homing by our robot to a single step by natural selection. The top
half is a map in the usual geographical sense, and the bottom is a map of “genetic space,” meaning thespace of possible genome sequences. Concentric rings mark the locations of two sound sources in the upper
map and two fitness sources in the lower map, showing how the signal strength falls the farther we go fromthese sources. Genome sequences in the species are shown by dots. Larger dots indicate the predominant
genomes before and after the homing step.

For our purposes, the crucial thing to get is that a new functional feature—aninvention—produces no fitness signal at all until at least one individual in thespecies already has that invention—which means natural selection itself can’t
invent! Suppose, for example, that the strong source of fitness in the lower left of
Figure 7.3 is a genuine invention of some kind and the weak source in the lower
right is completely insignificant as far as invention goes (I’ll give real examples
in a moment). Oblivious to matters of significance, selection moves the species
away from the invention because in this case the invention is completely“invisible.” That is, none of the species’ members has one of the special genome
sequences needed for the invention to be produced. Of course, if I had placed
another dot close to the invention, then the result would have been different. The
point is that this dot would belong there only if the special genome sequence itmarks already existed within the species. Selection can’t place the dots. It only
follows the dots, and then only in this shortsighted way.
So by the time selection begins to favor an invention, something other thanselection has already invented it. This is one of those common-science gems tobe treasured—an obvious realization that gains revolutionary status for no otherreason than a long tradition of ignoring it. Let this soak in for a moment. Despite
all the grand claims—everything from the popular plea of Richard Dawkins’s
The Blind Watchmaker2 to the technical pitch of Graham Bell’s Selection: The
Mechanism of Evolution3—the very logic of natural selection assures us that thepower of invention resides elsewhere. And because evolutionists have neveragreed on what this elsewhere is, the gaping hole that has always existed in the
middle of evolutionary theory is still there.
Dan Tawfik hit the nail on the head: Nothing evolves unless it already exists.
THE GAPING HOLE IN EVOLUTIONARY THEORY
Evolutionary theory ascribes inventive power to natural selection alone.
However, because selection can only home in on the fitness signal from aninvention after that invention already exists, it can’t actually invent.
The response to this gem from defenders of Darwin’s theory is that selection
didn’t produce eyes or brains or lungs all at once. Long before it worked uponcomplex organs like these, it was refining the many simpler things that paved theway for these greater things to appear. Each of the simpler things was beneficial
for its own reason, we are told, so selection was able to work even though thegrand functions didn’t yet exist.
Although this response continues to put selection forward as the hero of thestory, again something else has to be doing all the remarkable work of invention.
Selection can cause a species to take genetic steps, but without any way of
directing those steps, movement of that kind wouldn’t go anywhere. To reach aninteresting destination requires not just steps but coordinated steps, helped alongby nicely arranged stepping stones.
Suppose, for example, that some biological feature—call it X—performs its
function by means of numerous component functions. For X to work requires,say, a working P and a working Q and a working R, and for P to work requires aworking H and I and J and K, and so on. In light of all these requirements, howcould the invention of X have come about by accident? What is supposed to havecoordinated the appearance of all these necessary things at the right times andplaces, laying the stepping stones to X out so insightfully? To say merely that theprecursors for each necessary part were selected for different reasons is to ignore
the uncannily complicated circumstances that would be needed for this to be so.
After all, knowing that a certain species would benefit from a working X gives
us no reason to believe that precursors to all the components needed to build X
would just happen to have been beneficial earlier, each for its own reason, or that
all these precursors could have been coaxed by small modifications into their
new X-critical roles just when X was needed. Only in action films—where
realism isn’t even on the agenda—do things fly together in such helpful ways.
Science, on the other hand, should view claims of helpful coincidences ofthis kind with suspicion. At best, they’re a misinterpretation of history, whereselection—the sham hero—steals glory from an unnamed hero working behindthe scenes to make everything come out right.
ODDS BEATEN . . . OR BYPASSED
We’ll soon see why accidental invention must be highly improbable. In themeantime, if we provisionally accept this on the basis of our intuitions, we’re
prompted to wonder how an explanation of life can stand in light of these
improbabilities, not having overlooked them but having properly dealt withthem. There seem to be only two possibilities. Either an explanation beats the
improbabilities (that is, it counters them with something equally potent) or it
bypasses the improbabilities (that is, it renders them irrelevant).
As you may have noticed, the improbabilities we’re discussing are easily
bypassed by following our design intuition. Explanations of life that credit theinvention of living things to a knower avoid the burden of improbability
altogether. As for beating the improbabilities, the tactic we resorted to with ourrobot turns out to be the only tactic. That is, the only way to beat improbabilities
is to have such an abundance of opportunities for the unlikely outcome tohappen that its occurrence is no longer unlikely.
Another serving of oracle soup will help us see this. Picture a chef presenting
a pot of alphabet soup and lifting the lid to reveal written instructions. Now, ask
yourself what would qualify as a satisfactory explanation for what you justwitnessed? Someone having spent a couple of hours in the kitchen arranging theletters would qualify, but that would be bypassing the improbability, not beatingit. My question is, supposing the chef insisted the instructions were formed bynothing more than the process of boiling and cooling the soup, what could
conceivably satisfy you that he or she is telling the truth?
I hope you wouldn’t fall for an authoritarian approach. Imagine a team ofphysicists, all committed to the materialism. Would you be persuaded if theygave you a series of technical lectures claiming that the physical causes thatwrote genetic instructions in primordial soup did their work again in alphabet
soup? Surely not.
To stand your ground in the face of that kind of intellectual intimidation,
you’d need a simple, unassailable common-sense argument, and that’s exactly
what you’d have. No amount of technical mumbo jumbo can change the fact thatit’s extremely improbable for accidental causes to do the work of insight. If thephysicists attribute the instructions in the alphabet soup to “correlative
entrainment”—whatever that means—your first question should be “Did this‘correlative entrainment’ receive any assistance from someone who understoodthe instructions, or was it a completely unguided physical process?” And if theanswer is that it was unguided, your next question should be “Of all the possible
outcomes an unguided process might have produced, how was this ‘correlative
entrainment’ so fortunate as to achieve such a special outcome—one that looks
for all the world as though it was guided?”
There is no credible answer. Insight is absolutely unique, without rival
among the mindless causes to which materialists limit themselves and, as we
will later see, not reducible to those causes either. Being fundamentally unlike
insight, physical causes can’t do what insight does in any systematic way. Sound
waves are unlike water waves in their physical substance, but the fact thatthey’re both waves means they show strikingly parallel behavior in many
respects. Parallels for insight, on the other hand, are nonexistent.
The lack of any parallel to insight means that any instance of mindlesscauses doing the work of insight would have to be a fluke . . . a coincidence.
Minor examples abound. Short words do appear in alphabet soup from time totime, not by any mysterious force working in the broth but by coincidence.
Indeed, our robot exercise showed that the improbability of coincidence can beoffset by repetition, at least to a degree. Whether repetition can conquer thechallenge of biological invention is therefore worth considering. Certainly,
billions of organisms propagating through millions or billions of generations isrepetition on a whopping scale. Perhaps, then, we’ll find that our design intuition
isn’t calibrated for use on such a scale.

A CONSEQUENCE OF THE UNIQUENESS OF INSIGHT
The lack of any parallel to insight means that any instance of mindlesscauses doing the work of insight would have to be a coincidence.
We can imagine being surprised, anyway. Continuing our thought
experiment, suppose that after you express your skepticism to the chef, he or sheleads you through the swinging doors, whereupon you discover that what you
thought was a kitchen is really a logistics center—the Mission Control for a
massive soup-boiling operation involving a hundred million square feet ofkitchen space scattered over six continents! With the aid of automated text
detection, human operators are alerted whenever the pasta letters in any ofmillions of cooled pots resemble instructions, at least to the eye of a computer.
After running this operation at full tilt for just over nine years, one of those alerts
turned out to be the real thing. The contents of that winning pot were carefully
frozen to keep the letters in place for transport from a kitchen facility on theoutskirts of Johannesburg, and you were fortunate enough to be invited towitness the presentation (after thawing).
Let’s also suppose that with the help of a statistician you do the math andeverything checks out. When the scale of the operation is taken into account, you
calculate that instructions comparable to what you saw should pop up every 7.2
years, on average. It took a bit longer than expected, but it was worth the wait.
Your skepticism has been answered. The chef was right. And interestingly, whilethe vast scale of repetition is what caused the instructions to be produced, whatcaused them to be noticed was selection, of a kind. So selection did have a role
—more modest than invention, certainly, but not insignificant.
Of course, considering the amount of supposing we’ve done here, closer
inspection may show this whole scenario to be implausible. We’ll settle this overthe next two chapters. Here, the point is that accidental invention would have toleverage repetition to beat the unfavorable odds of extraordinary coincidence.
With respect to the invention of living things, then, a commitment to materialism
is a commitment to accidental explanation, and a commitment to accidental
explanation is a commitment to coincidence, and a commitment to coincidence
is a commitment to the power of repetition. These things stand or fall together.

Figure 7.4 The dominoes that must stand if materialism is to stand.

IF ANYTHING POWERS ACCIDENTAL INVENTION, IT IS REPETITION
Only by improbable coincidence can accidental causes do the work of
insight, and only by repetition can this improbability even conceivably beoffset.

REAL SELECTION—GOOD, BAD, AND UGLY
To round out this chapter, I want to describe three case studies from thelaboratory that bear out the conclusion we’ve drawn about selection—that it’s anaimless wanderer, incapable of inventing. However strong the desire is to portray
selection in glowing terms, the reality confronting scientists who work with it in
the laboratory is much more humble. No one has a truer sense of what selection
can and can’t do than those who’ve attempted to harness its power, to make it
perform before our very eyes. When I say that these people—myself included—
have, over the decades, come to a much more modest view of natural selection,
I’m saying something worth listening to.4
The modest view isn’t entirely negative. Selection does one thing reasonably
well, in fact. Having failed as an inventor, it has managed to prove itself as afiddler, referring to the kind of fiddling we do in a cluttered toolshed or garage.
Just as a stalled motor can sometimes be made to run with a slap on the side, or abarely working piece of equipment can be made to work better with a drop of oil
here or the turn of a wrench there, so it is with biological systems. Small
adjustments can sometimes mean the difference between working poorly andworking well, and selection seems to have a knack for finding adjustments ofthat kind.
I once constructed a mutant enzyme that proved to be a fiddler’s dream.
Starting with a natural gene that protects bacteria from penicillin by encoding a
penicillin-inactivating enzyme called beta-lactamase, I mutated this gene to thepoint where its encoded enzyme barely worked. The weakly functional enzyme
enabled the bacteria producing it to survive very low doses of penicillin, withanything higher being lethal. Like a rusting motor in a junkyard, this beat-up
enzyme turned out to be just the sort of thing a fiddler can fix. My colleagues
and I turned selection loose on it in the laboratory by making lots of mutationalvariants of the encoding gene and letting selection choose which ones worked
best. After six rounds of mutation and selection, using increasingly stringent
selection with each round, we found ourselves with an amazingly well-repaired
enzyme.5 In fact, the five-hundred-fold improvement accomplished by thenatural fiddler even surpassed the performance of the highly proficient natural
enzyme I had beaten up!
Under these favorable circumstances selection is indeed able to home in on
fitness to arrive at a well-tuned function. At the start of our laboratory
experiment, the bacteria were in a situation analogous to a noise-seeking robot
within earshot of a football stadium and with an unobstructed path to the stadium
entrance. But as effective as homing was in this experiment, it did nothing that
resembles invention. In order to make its improvements, selection had to begiven a gene that encodes a working beta-lactamase enzyme, which is no smallthing.
Remember that protein molecules that form enzymes must be folded into justthe right shape to perform highly specific chemical reactions. The precise shapeof each protein and, typically, the precise assembly of these into a multi-protein
complex are what enable enzymes to perform their tasks with remarkableefficiency and precision. Selection did a fine job of making the necessary
adjustments to return my messed-up beta-lactamase to good working order, but
drops of oil and turns of a wrench are a far cry from the genius we associate withinvention.
The best way to prove this is to challenge selection to come up with a marvel
of its own. We did this too, by turning it loose on another protein that gives
bacteria slight protection against penicillin. Like the weak enzyme justdescribed, this variant was derived from the natural beta-lactamase enzyme. In
this case, however, the structural disruption was so extreme that the protein
didn’t even qualify as an enzyme. Its encoding gene had suffered the deletion of

108 DNA bases, the loss of which prevented formation of the cleft where thechemical inactivation of penicillin normally occurs (Figure 7.5).
Nevertheless some of the simplest chemical reactions can occur even without
enzymes, and inactivation of penicillin is one of them. Penicillin is a fragile
molecule that breaks down in a matter of days in pure water or hours in acidic
water, so nothing like the sophistication of an enzyme is really needed toinactivate it—unless you’re in a hurry. Bacteria are in a hurry, though. Since
they can reproduce within half an hour of their “birth,” they can’t afford to wait
around for penicillin to break down on its own. Beta-lactamases reduce that waitfrom days or hours to minutes or seconds.
I discovered the deletion mutant after exposing bacterial cells carrying avariety of severely mutated test genes to just enough penicillin to keep themfrom growing.6 Under those conditions, all that was needed for one of the cells
to grow was a small enhancement of penicillin’s natural tendency to break down,
perhaps by something as simple as a floppy protein chain with several acidic
amino acids. One mutant gene met this challenge, and while I can only guess
how its encoded protein enhances the breakdown of penicillin, I was able toshow conclusively that it doesn’t operate the way a beta-lactamase does (seeFigure 7.5 legend).

Figure 7.5 Surface renderings of the natural beta-lactamase enzyme (left) and the most that could remain of
the natural structure in the deletion mutant (right). After binding a molecule of penicillin (dark gray) in theactive site cleft as shown, the enzyme (left) rapidly inactivates it and then expels the harmless product. Oncethe cleft is cleared, the enzyme is ready to bind the next penicillin molecule. The image on the right ishypothetical in that it depicts what remains of the deletion mutant as if Legos had been removed from a
Lego structure. Proteins are very unlike Legos, though. They tend to form their structures in an all-ornothing way, which means large deletions like this may easily prevent the folding of what remains. Protein
chains that don’t fold at all remain floppy, like cooked spaghetti in boiling water. We don’t know for surewhether the deletion mutant is floppy, but we know its low-level function doesn’t employ the mechanism of
the true enzyme on the left because it is indifferent to the removal of amino acids that are crucial to thatmechanism.7

Having seen that the deletion mutant gives bacteria slight protection frompenicillin, we wanted to see whether selection could leverage that effect toinvent an enzyme with the structural and functional sophistication of a naturalbeta-lactamase. Despite our best efforts—supplying the great fiddler with all theopportunities we gave it previously—this time it failed, leaving us with an“evolved” protein that performed no better than the feeble one we had started
with.8Comparing this to the previous result gives a clear picture of selection’s
inability to invent. Homing was in operation in both experiments, but theoutcome was successful only when the signal being homed in on was comingfrom the right kind of source. In the second experiment there was no
sophisticated mechanism underlying the breakdown of penicillin, and this turns
out to be much more important to the evolutionary outcome than the initialsignal levels, which were similar in the two cases (Figure 7.6). Just as noise wasnoise to our robot, so fitness is fitness to selection, and this makes homing
profoundly ineffective if the signal from the right source isn’t detectable fromthe outset. Unless a working enzyme is supplied, the fiddling that selection does
so well is useless.
There are more embarrassing examples. Selection can home in on the wrong
source even when the signal from the right source is detectable from the outset,
and worse still, it can burn all bridges to the right source in its slavish pursuit of
the wrong source. This “ugly” scenario is equivalent to the robot being lured toits demise by the sound of an approaching bus, just outside a football stadium. A
collaborative project between scientists at Biologic Institute and the Universityof Wisconsin–Superior demonstrated this by examining the evolutionary fate ofbacteria carrying a faulty version of a gene that encodes one of several enzymes
needed to make tryptophan, one of the twenty amino acids used to makeproteins.9 The faulty gene carried single DNA base mutations at two locations,each of which resulted in a wrong amino acid being incorporated into the
enzyme. Both of those errors had severe functional consequences. One of themwas disruptive enough to eliminate function on its own, and the other caused
substantial but not total impairment. As a result, bacteria carrying this broken
gene were incapable of growing unless they were given enough tryptophan tosurvive.
Now, you would think selection ought to have been able to repair this faulty
gene as long as the bacteria were given enough tryptophan to grow andreproduce slowly. After all, stepping stones to full restoration seem to have been
carefully laid out. An initial mutation could have corrected the debilitating error,
bringing the benefit of partially restored tryptophan production. That advantage
should have then led to an abundance of cells with the partially repaired gene,which would have set the stage for a second mutation to correct the remaining
error. Once this happened, the benefit of normal tryptophan production would
have enabled the restored cells to flourish.

Figure 7.6 How the source of fitness, not the degree of fitness (the “signal”), determines the evolutionary
outcome. The heavy line shows (with artistic license) the strength of the fitness signal at various distancesfrom the two different sources. In both cases homing caused movement to the top of the local peak,indicated by dotted gray arrows. The end result was therefore determined by which source was being homed
in on.

I refer to these contrived circumstances as stepping stones because nature
would be incapable of catering to evolution the way these scientists did—supplying a nearly correct starting gene and giving the cells tryptophan handouts
until they no longer needed them. So evolutionary success in this artificial
scenario would do little to strengthen the case for the creative power of evolution
in the wild. Failure, though, would be an example of evolution going wrong evenunder unrealistically favorable circumstances.
It did go wrong. Not only did selection fail to restore the faulty gene, but italso led to irreversible inactivation of that gene!10 Moreover, it did this by doing
exactly what selection does well: homing in on the most accessible source of
higher fitness. Because it costs a cell something in materials and energy toconstruct protein molecules by decoding the sequence instructions on a gene,
faulty genes are a burden to cells that carry them. Silencing these genes so they
can’t be processed at all removes this metabolic burden. Restoring the genewould have brought a much greater advantage in this case, but selection isincapable of turning down immediate advantages for the sake of something wewould consider worth waiting for. The advantage of partially restoring the genewould have been just as immediate, but it would have been harder because it
would have required one particular mutation—undoing the debilitating basechange—whereas any of a great number of mutations were able to silence thegene. In the end, then, even hand-placed stepping stones couldn’t lead selection
up the right path (Figure 7.7).

Figure 7.7 How selection went badly wrong even in a case where everything seemed poised for success.
Each stepping stone represents a different version of the experimental gene, the dark spot marking the initial
version with the two mutations. Stone heights represent the fitness of bacteria carrying the respective genes.
The three stepping stones shown on the left seem to pave the way for selection to carry the bacterial
population upward to full restoration, but experimental populations never took this path. Because the genecan be silenced by any of a great many mutations—far more than the five shown—this was the preferredoutcome. Silencing mutations are evolutionary dead-ends because they typically lead to loss of the gene.

THE TAKE-HOME FROM HOMING
Having given natural selection due consideration, we conclude that it lacks thepower to invent. This isn’t to say that selection is completely useless—only thatit’s useless as an inventor. In the end, we’re left with two candidates for the roleof life’s inventor, one fitting our design intuition and the other challenging it. If
insight turns out to be the only plausible cause of invention, our intuition will
have been confirmed. Alternatively, if repetition—presumably on a scale far

beyond the familiar—turns out to have the power to invent, our intuition will
have been overturned.
In order to decide between these alternatives, we need to consider the limitsof repetition. Our noise-seeking robot was able to find a stadium only bywandering around aimlessly long enough to come within earshot, and we expect
something similar for evolution. That is, to stumble upon an invention, a species
would have to wander aimlessly long enough for this to be a likely outcome. But
is this possible? To find out, we’ll think about the limitations of blind searches in
the next chapter.

CHAPTER 8

LOST IN SPACEIn chapter 6 we saw that our design intuition explains why we perceive busywholes to be products of intent and how living things epitomize that category. In
chapter 7 we asked whether anything has the power to defy the odds—and ourintuition—by inventing life without intent. Despite all the fuss surrounding it,
natural selection lacks this power. Noting the parallel between our noise-seeking
robot’s aimless wandering and the similarly aimless genetic wandering of a
species, we realized that repetition is the only factor that can conceivably offset
the improbability of stumbling upon biological inventions by accident. Having
associated this improbability with coincidence, we still need to connect it to theearlier subjects of busy wholes and the universal design intuition. We’ll do thisin chapters 9 and 10.
In preparation for that, we turn now to the question of whether some things
might be so hard to find by aimless wandering that we should consider theiraccidental discovery to be impossible. If this turns out to be true, we’ll want toknow whether biological inventions are among these unfindable things. If they
are, we’ll know Darwin was wrong.
HUNTING FOR EGGS
The familiar way to find something is to search for it, which, in our experience,is always a goal-directed effort. Here we’ll use the word search differently. For
our purposes it will help to call any process that could potentially find somethinga search, whether or not there was a goal. In this broad sense of the word, ournoise-seeking robot in the previous chapter searched for a football stadium, andevolving species search for helpful biological inventions.
We’ll call searches like these egg-hunt searches because they have several
important characteristics in common with Easter egg hunts. The first of these isthat there definitely is something special to be found, whether or not the searcheris aware of it. The existence of recognizable “treasure” of some kind makes a
successful outcome both possible and unambiguous. Not all searches are likethat. The person combing a beach with a metal detector or sorting through a
coffee can full of old coins hopes there’s something valuable to be found, butthere is no guarantee that such a thing exists.
The second characteristic of egg-hunt searches is that they occur within awell-defined space. That is, they all start with treasure somewhere out there,
where there refers to a definite, bounded region. The smaller this region is, theeasier the search will be, but there are no limits; the region could be so large thatthe search is effectively impossible. If a watch left on a train in London fails toshow up at the lost-and-found office by the next day, we know it’s within a day’s
journey from London, but the portion of the globe that meets this condition is far
too big to search—the watch is gone.
The final characteristic of egg-hunt searches is that they always proceedwithout assistance. The only way to get the treasure is to keep looking or
wandering within the defined search space until it is found. There are no hints or
guiding signals or anything else that systematically aids success. To our noiseseeking robot, for example, the only noise that served as a guiding signal was thesound of the roaring crowd at a football stadium. Countless other noises might
have been homed in on, but none of them would have led the robot to a stadium
in any systematic way. Consequently, the robot’s wandering when it’s out ofearshot of any stadium qualifies as unguided searching. This stands in contrast to
the robot homing in on the noise from a nearby stadium, or to a child finding thehidden egg with the help of a parent saying “warmer” or “colder.”Unassisted searches are often called blind searches. We will use this term,
keeping in mind that it refers to absence of foresight or insight rather than toabsence of sight. The searcher in an egg-hunt search moves through the search
space, deliberately or not, and has the ability to make use of the treasure lying inthis space if and when it is found, but is otherwise absolutely clueless.
SEARCHING NONPHYSICAL WORLDSAll the search examples just mentioned share a property so typical of familiar
searches that we tend to overlook it: they’re based upon physical location. Our
robot moved from one physical location to the next, succeeding only by arriving
at the physical location of a football stadium. The beachcomber checks one
physical location after another, hoping one of these places will be where thedesired treasure is hiding. Coins in a coffee can may be moved around freely tofacilitate their examination, but the objective is still to physically locate coinsthat make the effort worthwhile. Even web searches come down to physicallocation by connecting the searcher to a physical server with the desired content.
What would a search that isn’t grounded in physical location look like? The
answer is that it would take place in the realm of ideas. For example, consider
the game of twenty questions, where one player thinks of an object that’s to be
guessed by the other players. The guessers take turns asking up to twentyquestions about the object, with the only permissible answers being “yes” and“no.” Notice that while this game revolves around a chosen physical object, thesearch is not for the object itself but for the thought of it, expressed by naming it.
Indeed, the same guessing game can be played with nonphysical categories, suchas occupations or family names or songs.
The space to be searched in these games is not a physical space but rather theconceptual space of possible answers—all the answers that could, as far as theguessers know from the outset, be correct. If it makes more sense, think of thesearch space as an abstract set—a group of conceptual possibilities, not a groupof physical things or a physical space where such things may be located (awarehouse, for example). As always, blind searches consist of checking one
possibility after another—deliberately or not—while staying within the search
space.
We’ll soon see that egg-hunt searches in nonphysical search spaces—thekind of searches relevant to Darwin’s evolutionary mechanism—are where thesimple meets the surreal. Searching remains utterly simple, but finding becomesincomprehensively difficult as the spaces themselves become uncannily large.
This raises an important question about the meaning of impossibility—one
we’ll need to consider in order to decide whether evolutionary invention is
impossible. On the one hand, because the thing being searched for—the searchtarget—definitely exists within the search space, it’s theoretically possible for ablind search to find this target. But on the other hand, since Darwin’s account of
invention would have to work in real life, we should reject this account if wefind it to be practically impossible.
To give us a tangible feel for magnitudes of unlikelihood, as we explore thedistinction between what is and isn’t possible, let’s look at a specific search thatwill become a helpful point of reference.

THE CUNA SEARCH
We have a better feel for physical search spaces than nonphysical ones, so ourreference will be an egg-hunt search in a physical space. Because we’reultimately trying to grasp the more extreme improbabilities of nonphysicalsearch spaces—evolutionary ones in particular—we should push our physicalpicture to the very limits of familiarity. The largest physical space we routinely
navigate is the earth’s surface, so we’ll use this as our reference search space.
Our search target will be a feature on the earth’s surface that’s just large enoughto be seen when we stand above it.
I have in mind a certain indentation, about the size of a pinhead, in the
middle of a particular bronze plaque that’s fixed to the ground. The significanceof this indentation is that it lies precisely in the “crosshairs” formed by theborders of Colorado, Utah, New Mexico, and Arizona. I’ll refer to thisindentation as the cuna target, the term being composed from the first letters of
the four state names (Figure 8.1). So our reference search—the cuna search—isa blind search of the entire surface of the earth for this cuna target, which is astandard egg-hunt search that differs from common ones only in difficulty. The
cuna target covers a mere one part in a hundred billion billion equal-sized partsof the earth’s 510 million square kilometers of surface, making this about thehardest physical search we can mentally picture.
Having a sense for how ridiculously hard the cuna search is will be helpfulwhen we look at much harder searches (evolutionary ones in particular). The
best way to refine this sense is to perform the cuna search virtually, which you
can do at the GeoMidpoint website (www.geomidpoint.com/random). This siteenables you to drop up to 2,000 pins to random points all over the globe, after
which you can view the pinned locations on Google Maps.1 By zooming in on
the cuna crosshairs, you’ll see how close the closest pin came to hitting the cunatarget. You can’t zoom in close enough to see something as small as this target,
but that won’t matter—the closest pin will be miles away.
PINNING DOWN THE COVERAGE PRINCIPLE
To give us the visual satisfaction of hitting a target, let’s do a blind search of the
globe for something bigger. How about Australia? With this huge target, we
expect a good number of pins in every batch of 2,000 random drops to be hits.
More precisely, we expect the fraction of pins landing in Australia to be nearlyequal to the fraction of the earth’s surface covered by Australia, and thisapproximation should become increasingly accurate as more pins are dropped.
So since Australia covers 1.5 percent of the earth, we should expect about 30 ofevery 2,000 pins to land there, 30 being 1.5 percent of 2,000. You can do theexperiment to check this for yourself. When I did it, 29 pins landed in Australia,
which is in line with our expectation.

Figure 8.1 The circular bronze plaque at the center of the Four Corners Monument that marks the point
where Colorado, Utah, New Mexico, and Arizona meet. The arrow points to what we’re calling the cunatarget, the tiny (approximately 2.5 millimeter diameter) indentation at the intersection of the “crosshairs.”

The intuition informing our expectation is an obvious principle of coverage:
the ease of hitting a target by accident scales with the target’s size. We applied
the same intuition in chapter 7 to calculate the likelihood of our noise-seeking
robot landing within earshot of a football stadium, and when we found thislikelihood to be very small, we appealed to repetition (repeated homing
movements) as the only way to overcome the unfavorable odds. The same thing
is being done here with repeated pin drops instead of repeated movements.
Australia is hard to hit in one random attempt, but with a hundred attempts it
becomes much easier, and with a thousand it’s almost a sure thing.
We’re now ready to recast our intuitive understanding as the coverage
principle, which works just as well for a species wandering through genetic
space as it does for pins dropped randomly to a map. To drop a pin is,
metaphorically speaking, to check one of the possibilities in a search space, andto say that the pin hit the target is to say that the target was found. In terms ofthis pin metaphor, the coverage principle may be stated as follows:If enough pins are dropped randomly over a search space, the fraction ofthem hitting any target within that space is expected to equal the fractionof the search space covered by this target.
As we’ve just seen, this accords well with actual observations when the target islarge enough to be hit easily.
In fact, this principle is so intuitively compelling that we took it to be true inchapter 7 without putting it to a test. Indeed, it must be true. So instead of casting
it as an empirical claim, we should restate the principle as a probabilistic truth.
Because probabilities are themselves fractions (fractions of complete certainty),
we can replace the first occurrence of “fraction” with “probability” and remove
the suggestion that many pins must be dropped:
If a pin is dropped randomly over a search space, the probability of it
hitting any target within that space is equal to the fraction of the search
space covered by this target.
To apply this to our reference search, we recall that the cuna target covers
one part in a hundred billion billion equal-sized parts of the earth’s surface,which can be written either as a numerator over a denominator or as a decimal
fraction:

The coverage principle states that this fraction also represents the probability ofa randomly dropped pin hitting the cuna target. We don’t need a demonstrationof this claim because we’ve deduced it from a principle we know is true.
One final adjustment will make the coverage principle more versatile. It isn’t
really necessary for the pins to be dropped randomly in order for the principle tohold. All that matters is that hitting the target isn’t systematically favored in any
way, which is one of the characteristics of an egg-hunt search. The pins must be
dropped blindly, which may be quite unlike random dropping (for example,
dropping in an orderly grid pattern) though it is no more conducive to success.2
Our final statement of the coverage principle replaces “randomly” with “blindly”
in order to reflect this:THE COVERAGE PRINCIPLE
If a pin is dropped blindly over a search space, the probability of it hitting
any target within that space is equal to the fraction of the search spacecovered by this target.
If I’ve taken you outside your comfort zone on this part of the journey, pleasehang in there! The terrain gets easier just ahead, and you’ll see that the steep
climb on this part of our hike was worth the effort. As abstract as all this talk ofsearches may seem, it will prove invaluable when we examine whether
evolutionary searches are possible.
SPACES OF SURREAL SIZE
The coverage principle is every bit as valid for searches of nonphysical spaces as
it is for searches of physical spaces. Equipped with this principle and the cunasearch, we’re ready to think about whether success is impossible for certain
nonphysical egg-hunt searches.
Let’s try to construct an impossible search to see whether we can. Using ourintuition that huge spaces make searching harder, let’s think up a nonphysicalegg-hunt search in a space that’s unimaginably large. How about the space ofpossible digital images? That should be plenty big. We’ll have to use the word
image loosely here, because the random pixels that fill most of this space aren’t
what we’d normally call images. With that in mind, let’s take our exact search
space to be this:ALL POSSIBLE IMAGES 300 PIXELS BY 400 PIXELS IN SIZE

Leaving the search target unspecified for the moment, think about the allinclusive vastness of this search space. For one thing, every photo that ever has
been taken or ever will be taken or, indeed, ever can be taken has a suitably sizedversion in this space. Moreover, in addition to all those pictures, the spacecontains everything else that we’d recognize as a graphical representation of any
kind—from circuit diagrams to wallpaper patterns to scribbled grocery lists.
The guaranteed existence of all this content might give the impression thatwe’ve just stumbled upon a digital treasure trove. After all, we have a container

of sorts (the image space) that holds too many things of value for us to begin to
number them, most of which have never been seen before. Like an archive stolen
from the distant future, this container holds portraits of all the world’s great
leaders—past, present, and future—along with snapshots of the most
newsworthy events of all time and diagrams of the best inventions of all time—
innumerable priceless surprises waiting to be stumbled upon by the first
explorers to search this rich space. What a bonanza!
Before we get too excited, though, we should remind ourselves that this is no
ordinary container. Our image space is nothing more than a concept fororganizing certain other concepts, namely the many possible images. And whileit’s true that some of these possibilities have been actualized in our physicalworld (Figure 8.2 being one example), it’s easy to show that the overwhelming
majority can’t be. Our image space is therefore intrinsically nonphysical.
The elementary math that shows this is nothing more than multiplication of
the component possibilities. Each pixel is given its hue by assigning levels (or“intensities”) of the three base colors for a digital display: red, green, and blue.
These levels are whole numbers, typically ranging from 0 (meaning no additionof that color) to 255 (meaning full addition of that color), for a total of 256
possible levels. The number of possible color specifications for a single pixel istherefore calculated as the product of the level possibilities of all three basecolors, which comes to more than 16 million colors (256 × 256 × 256 =
16,777,216).

Figure 8.2 A digital representation of the earliest presidential portrait of Abraham Lincoln, shown at a pixel
resolution of 300 (width) by 400 (height).
Abraham Lincoln, public domain.

Because an image is nothing more than an arrangement of colored pixels, we
can calculate the exact number of images in our space by multiplying those color
possibilities across each of the 120,000 pixels (300 × 400 = 120,000). Taking
just the first two pixels, there are 16,777,216 × 16,777,216 color combinations,which amounts to hundreds of trillions—already a huge number with 119,998
pixels still left to factor in! Each of these remaining pixels multiplies thepossibilities by another factor of 16,777,216, producing a final number so large it
has to be seen to be believed. My computing software does the full calculation ina fraction of a second, resulting in a book-size number—one that would take 198
pages to print!
For comparison, a single 80-character line of text would suffice to write out
the number of atoms in the universe, with the total number of physical events
over the universe’s history requiring only half a line more.3 So as large and old
as our universe is, it envelops nowhere near enough matter and has spanned
nowhere near enough time for each of the possibilities in this search space tohave been given a physical representation. The search space can never be
actualized in that way, and yet it has true properties that can be verified byanalysis, including the strange combination of incomprehensibility and exact
calculability with respect to its size. It is at once real and surreal.
FANTASTICALLY BIG NUMBERS
The distinction between numbers that are so big they can’t be represented
physically (because there aren’t enough physical things to match the number)and numbers that can be represented physically is important enough for where
we’re heading that I want us to have an easy way to spot the difference.
In everyday life, we think of numbers as being big at the point wherecounting to them by ones becomes inconvenient. A chaperone on a school field
trip easily counts a few dozen children by keeping a mental tally, but to counthundreds would require a more elaborate process. So the dividing line between
comfortable numbers and uncomfortable numbers—in this practical, everyday
sense—lies somewhere in the vicinity of one hundred.
Interestingly, this common understanding of numerical “bigness” turns out tobe handy when we try to get our heads around numbers that defy physicalrepresentation, which we’ll call fantastically big numbers. As a rough rule ofthumb, when the number of digits needed to write a number out is itself a big
number, the number represented by those digits is fantastically big. That is,numbers exceeding about a hundred digits in length also exceed physicalrepresentation, or nearly so. For example, the number of pixel colors—
16,777,216—is big but not fantastically big, whereas the number of images inour search space is fantastically big.
In fact, a much smaller search space would still be fantastically big. The
space of tiny 3-by-5 pixel “images,” for example, includes this whopping
number of possibilities: 2,348, 542, 582, 773, 833, 227, 889, 480, 596, 789, 337,
027, 375, 682, 548, 908, 319, 870, 707, 290, 971, 532, 209, 025, 114, 608, 443,
463, 698, 998, 384, 768, 703, 031, 934, 976.4 Think fantastically big whenever
you see numbers of similar or greater length, and know that these numbers arebeyond physical representation.
SEARCHER VS. SPACE
We’re now ready to fully describe our impossible search. We can think of any
search as a contest between the searcher and the search space, with larger targets
making things relatively easier for the searcher. I claim that our image search
space is so fantastically big here that we can choose a fantastically big target andstill show that the space wins the contest. If this is true, it’s an important lesson
to carry with us into the next chapter, where we’ll consider whether egg-huntsearches can conceivably invent things.
Figure 8.3 shows one of many ways to make a fantastically large target forour impossible search. Our trick is to use pixels to represent dot-matrix
characters (letters, numerals, and symbols). Fifty rows of characters with fifty
characters per row perfectly fills our 300-by-400 pixel image size, turning theimage into what looks like a small phone screen packed with characters. Let’scall any image that’s filled with characters in this way a dot-matrix screenshot,
just to give it a name. Our search target, then, will consist of:
ALL IMAGES THAT DEPICT ANY DOT-MATRIX SCREENSHOTWe know the number of these target images will be at least as large as thenumber of possible character combinations, which is staggeringly large. We canmake it even larger, though, by not requiring each character to be made of black
pixels against a white background. By experimenting, I found characters to bereadable if their color levels (red, green, and blue) are in the lower third of therange (0 to 85) while the levels for background pixels are in the upper third (170
to 255). Now, instead of using only two pixel colors (black or white) to build the
dot-matrix characters, we can use over a million.
So our contest looks like this: the searcher will check as many images fromthe search space (all possible 300-by-400 pixel images) as possible to see if any
happen to “hit” our search target by being a dot-matrix screenshot. Exactly how
this is done doesn’t concern us, as long as the process is truly blind, meaning the
choice of possibilities to check doesn’t in any way benefit from insights thatwould favor correct guesses. If you want to picture the process, think of a web
service that allows the searcher to upload an unlimited number of 300-by-400
pixel images with an email notifying the searcher immediately if one of these
uploaded images happens to be a hit.

Figure 8.3 Light and dark colors (shown in grayscale here) are used to turn a 300-by-400 pixel image into
what we’re calling a dot-matrix screenshot (50 rows of 50 characters). Each character occupies a 6-by-8
pixel rectangle (left). I used a set of 93 characters (upper and lower case letters, plus numerals and symbols)in random order to construct the example of a dot-matrix screen-shot on the right.

That’s just one way of picturing the search, though. It could look very
different. The key point is that no matter what the search looks like, every guessconsumes physical resources. Physical things have to be manipulated for a guess
to be constructed and tested, and this requires at least a little bit of physicalmaterial to be devoted to representing each guess for a little bit of time. No
matter how efficient or extensive the things that make and check guesses are,

these little bits become huge as the number of guesses becomes huge. And asabundant as physical materials and time are, they aren’t infinitely abundant. So
there comes a point where the search is so demanding that it simply can’t becompleted, no matter how the searcher tries to approach it. In the final analysis,
then, the contest boils down to a comparison of a, the number of images that canbe physically actualized (so they can be checked), with b, the number of images
that would have to be actualized in order for a dot-matrix screenshot to beamong them by chance.
We know a can’t be fantastically big because we’ve defined fantastic bigness
to mean too big to be actualized. This means the searcher is in trouble if b isfantastically big. We can estimate b by using the coverage principle along withthe commonsense rule that it takes about a gazillion tries for a one-in-a-gazillion
outcome to happen by chance (“gazillion” here stands for any specific large
number). This way of estimating b is worth stating in terms of our pin-dropping
metaphor because we’ll use the same method to decide whether evolutionary
searches are feasible. Using “reciprocal” in the mathematical sense, where thereciprocal of m/n is n/m, we have:
THE PRINCIPLE OF RECIPROCAL SCALE
The number of pins that must be dropped over a search space before aparticular target is expected to be hit blindly can be estimated as thereciprocal of the probability of success on the first drop, or—equivalently—
the reciprocal of the fraction of the search space covered by this target.
Translating from the pin metaphor, this means the number of images thesearcher will have to check before we’d expect a dot-matrix screenshot to beamong them is equal to the size of the space divided by the size of the target:

This puts the frighteningly big 198-page number in the numerator, which means
the searcher can only hope we’ve made the target large enough for the resulting
answer to not be fantastically big.
Instead of exhausting you with more multiplication, I’ll just say that the
number in the denominator—the number of possible dot-matrix screenshots—isalso fantastically big, filling about 160 pages. As huge as that is, though, it’s notnearly big enough to do the searcher any good. The trick for gauging the size ofthe answer is to subtract pages, as in Figure 8.4. This tells us that the answer—
the number of images that would have to be actualized—is a 38-page number,which we know is fantastically big. The fact that this is much smaller than it
could have been (had the target been smaller) is of no consequence. The blind
searcher can’t succeed because success would require more images to bechecked than any physical process can check. The search space wins this contest
decisively.
We can use the cuna search to get a feel for just how hopeless the situation isfor the searcher. The principle of reciprocal scale tells us that the expected
number of blind pin drops needed to hit the cuna target is about a hundred billion
billion, which is written out as a one followed by twenty zeros. For a run of nconsecutive cuna hits (if you can imagine such a thing), the number of blind
drops needed is therefore expected to be a 20n-digit number, where n is thenumber of hits in a row. The number of blind pin drops needed for four cuna hits
in a row, for example, would be an eighty-digit number, which would fill a lineof text, without commas.
We now have two ways to gauge the difficulty of very hard searches. Bothmake use of the huge number we get by applying the principle of reciprocal
scale and in particular the number of digits needed to write this huge number
out. First, dividing the number of digits by twenty tells us how hard the search isin terms of consecutive cuna hits. So, if the principle of reciprocal scale says thenumber of possibilities the searcher needs to check is a forty-digit number, thismeans the search is as difficult as dropping pins blindly until the cuna target is
hit twice in a row—astonishingly improbable, when you picture the cuna search.
Second, we know that if the number of digits is above a hundred, then afantastically big number of possibilities would need to be checked, which simply
can’t be done.

Figure 8.4 Division of extremely large whole numbers (larger divided by smaller) is represented inabbreviated form at the top, with the full length of each whole number depicted by a stack of printed paper
below. For numbers that aren’t of page length, you can use the same method with lines instead of pages.
Notice that no division has to be performed to gauge the magnitude of the result in this way.

At thirty-eight pages, the whopping number of images that would have to bechecked for the searcher to find a single dot-matrix screenshot has over 160,000
digits. Dividing this by 20, we find our blind image search to be as difficult as
dropping pins blindly until the cuna target is hit eight thousand times in a row bypure luck!
That will never happen.
The search space wins.
THE POSSIBILITY OF PHYSICAL IMPOSSIBILITY
Anyone still rooting for the searcher might seek refuge in two thoughts. The firstis the hope that when it comes to evolution, the most important searches will
prove much more favorable than this example search. In particular, if the actual
targets of interest cover a substantially higher proportion of their respective
spaces than this one does, perhaps the principle of reciprocal scale won’t
ultimately be an insurmountable obstacle. This certainly has to be given due
consideration before we reach any firm conclusions regarding evolutionary
searches, a task we’ll tackle in the next chapter.
The second potential place of refuge is the thought that the word impossible
ought to be reserved for situations where the probability of success is exactly
zero. Admittedly, this isn’t true for our example. Rather, the probability ofgetting a dot-matrix screenshot by chance in one try would be represented as azero followed by a decimal point, followed by a very long run of zeros—filling
thirty-seven pages and spilling over onto the thirty-eighth page before the first

non-zero numeral appears. That probability can be increased by allowing moretries, but the whole point is that tries can only be multiplied within hard physicallimits. Even under the most wildly optimistic assumptions, our universe—vastand ancient as it is—can’t muster enough repetitions to erase more than about ahundred of those zeros!
Keep in mind that our interest here is more practical than mathematical.
Students of math should, of course, learn the conceptual distinction between
infinitesimal fractions and zero. But to decide whether success is possible
enough to carry any real implications is to make a practical distinction, not aconceptual one. Bearing that in mind, it’s clear that some search challenges favor
the search space over the blind searcher so overwhelmingly that they should
indeed be regarded as impossible. More precisely, success should in thesesituations be regarded as a physical impossibility in order to distinguish it from a
conceptual impossibility. We’re free to tell stories about such long odds being
beaten, but we now see very clearly why tales of that kind belong in the fiction
section—where we filed the tale of oracle soup.
Whether Darwin’s account of life belongs there too remains undecided forthe moment. If the dominoes fall, his theory falls with them. Repetition would be
the first one to topple, should it prove inadequate for explaining the remarkablecoincidences needed for life to be an accident. And it may. As we have now
seen, that domino is rather wobbly.

CHAPTER 9

THE ART OF MAKING SENSE
Aiming to resolve the conflict between our design intuition and the evolutionary
story, we set off on a quest for understanding that has been like a hike up a
mountain trail. We started, at sea level, with an idea so familiar it has the feel ofsomething obviously true. This was the universal design intuition. Lingering at
low elevation for a while, we took time to appreciate the humanness of science
before starting our climb. Pressing upward, we eventually found ourselves in therarified air of the summit, where we encountered subjects that may have seemed
quite unfamiliar. The walk will be easier from now on because we have reachedthe highest point. We have only one or two more things to see at this elevation
before we work our way back down to level ground, revisiting along the way
places we’ve seen before.
On the approach to the summit, I led us on an exploration of the generalsubject of blind searches. As challenging as that topic may have been, it will
prove critical for sorting out the conflict between the evolutionary story and ourdesign intuition. In fact, the evolutionary process as described by biologists isreally nothing more than a large collection of ongoing blind searches—one forevery species in existence. There’s nothing controversial about this. By blind I
mean without foresight or understanding, just as evolutionist Richard Dawkins
did in his highly acclaimed defense of Darwinism, The Blind Watchmaker.1 And
by search I don’t mean anything inconsistent with complete blindness. The idea
is not that any species aims to acquire new features but that all species doacquire new features, supposedly, through a long process of genetic meandering
similar to the meandering of our noise-seeking robot in chapter 7. So it’s correct
to say that any remarkable biological features acquired in this way were found,
not by deliberate effort, as the hound finds the fox or as the detective finds themurderer, but rather by ordinary course of nature, as the river finds the ocean oras the lightning bolt finds its path to the ground.
The contrasting view is that what looks to be the fruit of genius always is thefruit of genius. The universal design intuition declares this to be so, andeverything in our daily experience affirms that declaration. Inventions are cleverthings, and clever things are to be had only by cleverness. Inventors dosometimes search for new ways of doing things, but they never search blindly.
Invention is, after all, about mental lightbulbs going on so that things are seenclearly for the first time. It’s nothing like the aimless groping in the dark thatcharacterizes a blind search.
HOW HUMANS INVENT
Without presuming that all invention must proceed the way human invention
does, it will help to think about how we humans invent. I realize that most of us
don’t think of ourselves as inventors any more than we think of ourselves as
scientists, but this is because we underestimate the significance of what we dowith routine ease. When we get to the bottom of what invention really is, we’ll
see that inventing is an essential part of being human.
To help us get there, I’ve broken down the process of human invention into
the three stages shown in Figure 9.1. The first of these, the mental stage, iswhere the initial idea for the invention is developed into a detailed plan ready to
be implemented. The big top-level idea must always be broken down
conceptually into smaller ideas, which may have to be further broken down
before implementation can begin. The downward steps in the first stage of
Figure 9.1 are suggestive of this progression from the high-level concept to thenitty-gritty details.

Figure 9.1 The three stages through which human invention proceeds. Shading indicates the transition frompurely mental activity (unshaded) to purely physical activity (dark shading). The mental and methodicalstages aren’t as cleanly divided as this depiction suggests, and yet there is a real progression from the purely
mental activity of conceiving to the more physically constrained activities of building and testing.

The second stage is where the resulting conceptual plan is used to construct a
physical thing. The mental work at this stage is more practically oriented than it
was in the first stage. The fully conceived plan is imposed on actual physicalmaterials, which requires both a conceptual understanding of the plan and theability to resolve all the matters of detail that arise when complex plans are
implemented for the first time. I describe this as the methodical stage, to suggest
both that it requires conscious, purposeful action and that this action must takecareful account of the properties of the physical objects and materials being
manipulated. Notice that as many steps are ascended in this second stage as weredescended in the first. The point of the first stage was to form ideas in a topdown manner, going from the high-level idea to the low-level details needed to
implement it; the point of the second stage is to form a physical device in abottom-up manner, going from the raw materials and supplies at hand to aworking prototype.
If all goes well, the high-level idea will be evident to everyone at the third
stage as they watch the finished device do what it was designed to do. This isexactly what we inferred for the pool robot back in chapter 6. Everyone
watching that device in action realizes it’s cleaning a pool, which immediately
triggers the recognition that it was consciously intended to clean pools. So
having directly observed physical activity, we infer that past conscious activity
produced the special kind of physical activity we’re witnessing, namely thebusyness of a busy whole. Upon witnessing the invention in operation, we inferthat it was constructed according to a conceived plan.
An example will help to solidify these ideas.
HOUSTON, WE’VE HAD A PROBLEMIn April of 1970, NASA’s Apollo 13 mission sent three men—Jim Lovell, Jack
Swigert, and Fred Haise—into space with the objective of landing on the moon.
On the third day of their journey, things went horribly wrong. An oxygen tank
exploded, causing major damage to the spacecraft and forcing Mission Control
in Houston to replan the remainder of the mission around a new objective: tobring the crew safely back to Earth. Despite the precarious start, Apollo 13
would become a resounding success with respect to this new objective.

Of the many critical challenges that had to be overcome in the days between
the explosion and the eventual splashdown in the South Pacific, one was toprevent lethal buildup of carbon dioxide (CO2) in the section of the spacecraft
where the astronauts were living, called the lunar module. Scrubber cartridges
were present onboard for that purpose, but the ones that were accessible to theastronauts were box-shaped, for use in the command module, whereas the lunar
module was designed to use cylindrical cartridges. With the crew’s lives at stake,engineers on the ground had to come up with a way to make the box-shaped
cartridges work with a system that was designed to use cylindrical cartridges.
Their now-famous solution to this challenge was nicknamed the “mailbox”(Figure 9.2).
Like all inventions, the Apollo 13 mailbox had its origin in thoughts. First
came the motivating thought, which was the realization that CO2 exhaled by the
astronauts would become lethal if nothing were done to remove it. Next came an
analysis of the situation that provided the most promising path for a solution. So
before any physical things were manipulated, ideas were manipulated andrefined with the aim of thinking through all the details needed for the big idea tosucceed. This is the first stage in Figure 9.1—the mental stage.
Early in this process, the engineers on the ground started to progress into thesecond stage of Figure 9.1—the methodical stage of construction. I say started
because the mental and methodical stages of invention usually overlap. It’s
almost always necessary to experiment with ideas by trying them out, and theideas are almost always refined in the process. As important as experimenting is,though, the urgency of the astronauts’ predicament demanded a speedy
conclusion. Up in space, where it really mattered, everything was riding on the
final stage of invention: the stage where the mailbox must prove its worth byworking. The astronauts therefore needed to bypass all the head scratching andexperimenting their colleagues on the ground were engaged in and, after one
successful pass through the methodical stage of construction, move straight tothe final stage.
To pull that off required an invention of another kind: a clever arrangementof words called instructions.

Figure 9.2 The Apollo 13 “mailbox,” seen toward the top of this NASA photo, was a jury-rigged invention
for removing CO2 from the lunar module. Without it, the astronauts would have perished.
Apollo 13 “mailbox,” public domain.

LANGUAGE, THE ULTIMATE MEDIUM OF INVENTIONInterestingly, the importance of crafting words wasn’t lost on the NASA
engineers, as these excerpts from the Apollo 13 air-to-ground voice transcript
clearly show:
03 08 22 13/ Mission Control:
Yes. We wish we could send you a kit and it would be kind of likeputting a model airplane together or something. As it turns out,
this contraption will look like a mailbox when you get it all put
together.
. . .
03 10 52 51/ Mission Control:. . . as you know, we’ve got a way to use those [cartridges]. And
as soon as we get them written in some good words, why, we’ll passthat along. You might be able to make one.
. . .
03 11 51 58/ Mission Control:. . . we’re getting the words together to make it easy to build oneof these things, and it looks like it will probably take two guys,
so, I think we probably ought to plan to do that later.
. . .
03 18 08 43/ Mission Control:Okay, Jim. The way I thought it might be best to do it would be tohave you gather the equipment and let us talk you through yourprocedure while you do it. Now, maybe you could give Jack theheadset and – and – get the equipment together, and we’ll talk you
through the procedure. I think it’ll be a little easier to do thatway than if you tried to copy it all down - and then go do it.2

The spoken instructions that followed this recommendation fill many pagesof the typed transcript, indicating that this was one of those situations where thedetails matter.
Considering how categorically different words are from the assorted objects
Jim Lovell was asked to gather—scrubber cartridges, duct tape, plastic bags, andcardboard—it’s remarkable that the same principles of invention apply acrossthese categories. Whether we’re inventing instructions or a mechanical device ofsome kind, we always start by conceiving, and the process of conception always
works its way from a whole concept—the big idea—down to the low-level
details that must be resolved for this idea to be implemented. However fitful thetransition from conception to implementation—however many takes and retakes
it may require—we end up with a physical thing whose definite hierarchicalstructure reveals our thought process. That is, everyone can see how we thought
about the problem by examining the hierarchical structure of the invention wecame up with to solve it. Indeed, this very structure is what causes the invention
to work.
Having said that, I should add that the most elegant inventions perform their
top-level functions so impressively that the lower-level functions usually gounnoticed. When the tennis player of chapter 6 wins her match, the talk is about
the skill of her game, not about how well her lungs or her heart performed. Yet
the fact that no one had occasion to think about her respiration or her circulationshows how proficiently those necessary physiological functions were performed.
They supported excellent tennis so well as to make themselves practicallyinvisible.
What enables inventions to perform so seamlessly is a property we’ll callfunctional coherence. It is nothing more than complete alignment of low-level
functions in support of the top-level function. Figure 9.3 illustrates thisschematically for a hypothetical invention built from two main components, bothof which can be broken down into two subcomponents, each of which can inturn be broken down into elementary constituents. Horizontal brackets group
parts on a given level that form something bigger one level up, with the upward
arrows indicating these compositional relationships. Notice that every partfunctions on its own level in a way that supports the top-level function. This
complete unity of function is what we mean by functional coherence.

Figure 9.3 The hierarchical structure of an invention, showing the functional coherence that characterizes
the relationships between parts. In this scheme the parts at intermediate levels (between the elementary
constituents and the functional whole) are referred to as components. The number of intermediate levels andcomponents depends both on the invention and, to a degree, on the way we choose to delineate its principal
parts. The invariant fact is that the many parts must perform their small functions in a particular hierarchicalway in order for the whole invention to perform its large function.

functional coherence:

the hierarchical arrangement of parts needed for anything to
produce a high-level function—each part contributing in acoordinated way to the whole
As abstract as that may sound, it has very concrete and familiar implications,
all of which will be apparent when we consider how instructions work. The
Apollo 13 mailbox instructions will continue to serve as our example, butinstead of concerning ourselves with how CO2 can be removed from air, we’ll
focus on how ideas are conveyed by language. Whether we examine written or
spoken communication, and whether we choose English or Chinese or Malagasy,
all substantial pieces of communication have the distinctive pattern of functional
coherence represented in Figure 9.3. Alphabetic written languages, for example,
use letters as the basic building blocks at the bottom level. These letters arearranged according to the conventions of spelling to form words one level up. To
reach the next higher level, words are chosen for the purpose of expressing athought and arranged according to grammatical conventions of sentence
structure in order for that thought to be intelligibly conveyed.
Whether still higher levels have to be reached depends on the objective. If
the point is to convey one simple thought, a sentence should suffice. If it’s tocarry readers through an extended thought process, many sentences will beneeded, each carefully crafted to make its own point in a way that coheres withthe preceding points and paves the way for subsequent points.

MAKING SENSE WITH LETTERS
Mission Control’s objective of enabling the Apollo 13 astronauts to construct a
device for CO2 removal called for many instructive sentences, which in turncalled for knowledge, not only of how to construct the device but also of how to
put that understanding into “good words.” According to our design intuition,
instructions like these can only come from someone who has a mental grasp of
the procedure being conveyed and of the language in which it’s to be conveyed.
We’re now beginning to see why this intuition has to be correct. To guide ourthinking here, let’s consider a hypothetical scenario. Suppose that instead ofreceiving spoken instructions from their colleagues in Houston, the astronauts
had to work from written instructions. And suppose these written instructions
had to come from a source with no understanding of the astronauts’ predicament,
no clue as to how it might be remedied, and no comprehension of language.
Imagine the responsibility for these critical instructions resting in the prehensile
hands of a monkey—perhaps a retiree from the former space-monkey days.
Equipped with a typewriter but otherwise woefully ill-equipped, this monkey
clearly would have had very little chance of producing anything resembling
adequate instructions.
That much is obvious. More interesting is whether any blind search process—whether employing monkeys or supercomputers, whether operating over daysor eons, whether confined to a spacecraft or distributed over all the planets in abillion galaxies—can produce enough sequences of alphabetic letters for one ofthem to be an effective set of instructions for building the Apollo 13 mailbox. To
help us answer this, I converted the original spoken instructions into a concise
written form that, at thirty-two lines, fills just over half a page. Although thisisn’t a lot of text, we know from chapter 8 that the corresponding space of raw
possibilities—the total number of possible ways to fill thirty-two lines—is solarge that it’s physically impossible for all of them to be actualized. The questionis whether the number of alternative ways to word the instructions might
conceivably be large enough for some blind search process to triumph over thisenormous search space. That proved not to be the case for the contest between
searcher and space that we examined at the end of the previous chapter, but wefollowed that conclusion with the thought that perhaps the most relevant targets
do cover enough of their spaces for a blind search to succeed.
Certainly, everything that can be conveyed in words can be conveyed inmany ways. As for how many ways, though, I know of no way to do thecounting. Thankfully, we can evaluate this search by a different approach.
Instead of trying to count the alternative wordings for mailbox instructions, we’ll
simply ask how rare the functional coherence is that all written instructions
require. Starting at the bottom level, where letters are strung together to makewords, the first question is: how rare are the letter combinations used in writing
when compared to possible letter combinations?
To answer this, picture two printed pages, one half-filled with intelligible
writing and the other half-filled with random typing. Both pages are covered bysheets of black paper with several small rectangular holes in them, each holelarge enough to expose just three consecutive letters. Would what we see throughthese holes reveal which page is which? If so, then coherence is discernible evenin fragments of text smaller than an average word.
Figure 9.4 shows examples of what we’d see. Inspecting the four columns ofletters revealed on the upper page, we see no examples that look as though they
can’t have come from intelligible writing. Combinations like “ngt” and “rtr”(both in the first column) might stump us for a moment, but we can easily
believe these came from English words even if we struggle to call any examples
to mind (for the curious, they came from length and cartridge, respectively). By
contrast, the lower page reveals many obviously implausible combinations,
including “qmf,” “xdc,” “wvw,” “wrm,” and “hzj,” among others. On thislower page we also see a preponderance of letter combinations that, while notdefinitely implausible, are nevertheless peculiar. The “ftv” sequence, forexample, looks as though it could perhaps exist in a compound word like
softball, but it doesn’t exist in the 93,000-word software dictionary I’m using. So
it seems we can spot the incoherence of random typing even in tiny fragments of
keystroke sequences, provided we have several fragments to inspect.
Figure 9.3 helps us understand this. In this case the elementary constituentsat the bottom level are the twenty-six letters of the alphabet plus the spacecharacter for separating typed letters into words. We perceive letter combinations
like “hzj” to be incoherent because our familiarity with English tells us they
can’t form part of any English word. In terms of Figure 9.3, these combinations
can’t be placed under a horizontal bracket at the bottom level because they can’t
form a word at the next level up.

Figure 9.4 Examples of what would be seen through the rectangular holes described in the text. Holes
expose three consecutive letter positions (some of which may be occupied by spaces) at random locations
on the two pages. The upper page has actual mailbox instructions. The lower page has random typing,simulated by representing the twenty-six alphabetic letters and the space character in proportion to the sizeof their respective keys on a typical keyboard, where the space bar is five times the size of a letter key.

As you’d expect, the prevalence of this problem makes words a rareoccurrence in random typing. Of the 248 letter groupings on the lower pageshown in Figure 9.4, only eight are recognizable words. Most of these are either
the one-letter words a or i (signifying I) or two-letter words like he and uh. The
longest word on the page happens to be the three-letter word ink. In all, these
little words make up a mere 1 percent of the page’s content.
Having considered none of the finer points of writing yet, we already have

what we need to decide whether accidental mailbox instructions are within therealm of physical possibility. The observation that 248 letter groupings resulted
in only eight actual words means that the random letters falling between
successive spaces have only about a 1-in-31 chance of being words (8/248 =
1/31). And when they do happen to be words, they tend to be very short,averaging only about two letters or three keystrokes (counting the space that
ends the word). So because it takes about 1,800 keystrokes to fill half a page,
random typing would have to produce about 600 consecutive words just to fill
half a page with words (1,800 ÷ 3 = 600). If it did, there would be no coherence
above the level of words, but the avoidance of unrecognizable letter sequences
would at least satisfy that bottom-level requirement for useful instructions.
As inadequate as this requirement is, it provides an easy way to calculate aprobability that can be used with the principle of reciprocal scale from chapter 8.
Doing this will tell us whether a blind search of keystroke combinations can findeven something as insignificant as a jumble of tiny words that fills half a page. If
this overly generous target can’t be found, then finding coherent instructions forbuilding the Apollo 13 mailbox is completely out of the question.
To calculate the probability that half a page of random keystrokes would
consist entirely of English words, we start with 1 and multiply by 1/31 (theprobability of a letter grouping being a word) over and over, a total of 600 times.
According to the principle of reciprocal scale, the number of half pages thatwould have to be filled with blind typing3 in order for one of them to consist
entirely of words is expected to be roughly equal to the reciprocal of thismultiplied fraction. Equivalently, we can start with 1 and multiply by 31 (thereciprocal of 1/31) over and over, 600 times. When that calculation is done, theprinted result fills just over eleven lines with numerals, making this a paragraphsize number instead of a book-size number—fantastically big nonetheless.
Living as we do in a universe that can’t produce two lines’ worth of physicalattempts at anything, this eleven-line number delivers an overwhelming victory
to the search space. In terms of the pin-dropping metaphor, the difficulty of theblind search finding even this meaningless jumble of short words equates to thatof blindly hitting the cuna target forty-four times in a row (four hits per line, as
noted in chapter 8).
Notice how comprehensively the blind search has been defeated. We asked
whether it could produce instructions for building the Apollo 13 mailbox, and in
the process of deducing that it can’t, we discovered something much more
profound: a blind search can’t produce any coherent piece of extended writing at

all! Nothing that puts half a page to good use is physically possible, whether
instructions, or recipes, or to-do lists, or love letters, or poems, or anything else.
IMPOSSIBLE COINCIDENCES
The best medicine for anyone wanting to find a way around this hard fact is aclear understanding of why it really is a hard fact. The most common way toimagine going around it is by what we called stepping stones in chapter 7. That
idea is certainly tempting in the present context. We often communicate in shortphrases—Over here!—or even single words—Help! So, since blind searches canfind simple targets like these, we tend to be sympathetic to the idea thatsuccesses on this modest scale, where very little functional coherence is needed,
can be built upon gradually to produce successes on much larger scales—even
the scale of complete instructions.
I think our sympathy has to do with the fact that we, as creative thinkers,
love the idea of building on modest beginnings. We do this all the time—but notwithout insight. The problem is that we have no way to turn insight off. Insightcomes so naturally to us that we supply it all the time without noticing, evenwhen it doesn’t belong. In this way we tend to help evolutionary stories along
the same way we help any other story along: by filling in the gaps and adding afavorable interpretation.
Whether or not sympathy is the explanation, stepping-stone logic is very
common in evolutionary discussions. For that reason I want to stress again why
it doesn’t work. As I said in chapter 7, blind causes are so fundamentally unlike
insight that any instance of them looking insightful would be coincidental.
Coincidences do happen, of course, but we know from experience that major
ones are much more rare and therefore more surprising than minor ones. This iscommon science at work. A three-letter word appearing in alphabet soup is
worth mentioning, a five-letter word is worth photographing, and a seven-letter
word is downright suspicious.
All we’re doing in this chapter is unpacking this intuition to show why our
firm sense that certain things can’t happen by accident is absolutely correct.
What we’re seeing is that the amount of functional coherence routinely producedby human insight truly can’t be produced by accident. The reason connects towhat we learned in chapters 7 and 8: accidental causes mimicking insight on thisscale would be a fantastically improbable coincidence, which means a physically
impossible coincidence.

Because the degree of coincidence is what makes accidental explanations
implausible, there’s no way to alleviate the problem by thinking up creative
coincidental stories. However creative we make these stories, the creativity only
dresses up the coincidence. None of these stories remove the coincidence
because the very claim that accidental causes did what insight does is thecoincidence. The problem lies with coincidence itself, and that’s why twists inthese stories, whether stepping stones or anything else, never help. Thinking
back to the hypothetical team of physicists in chapter 7—this is why we didn’t
need to know what they meant by “correlative entrainment.” As long as they
meant something lacking insight, we knew they were banking on an impossible
coincidence.
The implications for invention are clear. If the invention of a working X is awhole project requiring extensive new functional coherence, then the inventionof X by accidents of any kind is physically impossible. Why? Because for
accidental causes to match insight on this scale would be a fantastically
improbable coincidence, and our universe simply can’t deliver fantastically
improbable coincidences. The fact that much simpler things can be had byaccident is completely irrelevant. The only thing we need to know to reject all
accounts of X itself being invented by accident is that these stories all attempt toexcuse an impossible coincidence.
By now, none of this should sound new. Whether we speak of impossible
coincidences or impossible searches, the hard fact is exactly the same: high-level
functional coherence can’t be found by any blind search because this would
amount to an impossible coincidence. Only insight can hit a target like that,which is no coincidence.
MAKING SENSE WITH WORDS
Although we encountered this hard fact by looking at coherence at the low levelof letter combinations, the situation only gets worse as we move up thehierarchy. Automatic spelling correction didn’t exist in 1970, but if we imagine
it did, even with a high-powered version that converts random keystrokes into
the closest words, the astronauts would have been no better off. Like letters,
words must be arranged coherently, which involves choosing good words andputting these words in good order. It isn’t as easy to calculate the likelihood of
this happening blindly as it was for forming words from letters. Still, we caneasily see that vocabulary is tightly constrained by the writing objective.

For example, of about fourteen thousand seven-letter English words, myversion of the written instructions for the Apollo 13 mailbox uses only eleven.
No doubt other words could have been used, but not just any words. To get a feelfor how strongly the subject of the writing constrains the vocabulary, try giving
someone the words I used (against, another, between, corners, cutting, lengths,
outside, plastic, screens, secured, and tightly) and asking them to guess the
subject of the writing from which these words came. They’ll easily deduce it has
to do with some sort of construction project—one involving plastic, screens,cutting, and tight securing. The ability to make that much sense from such small
pieces of a text is a mark of coherence.
If coincidental coherence is as rare at this level of vocabulary as it was at thelevel of spelling, you’ll get a very different result when you present someone
with a random selection of seven-letter words. One example should be enough tomake the point. Here, then, are eleven seven-letter words chosen randomly fromthe 93,000-word dictionary that came with my computing software: luffing,
dickens, numbers, inbound, roofers, incisor, overlap, Brownie, genomes,
avenged, and tallier. In these words I submit there is no hint of a coherent theme.
We need go no further. Blind searching fails at all levels. As people whowrite, we know that the need for insight grows as we move up the hierarchy, andthat only makes the coincidence of blind coherence greater and greater. Anyprocess that can’t substitute for competence in either spelling or vocabularycertainly can’t substitute for competence in grammar or composition. Our design
intuition has this one exactly right. We need knowledge to write useful
instructions, and no accidental process can replace that knowledge.
Without belaboring the point, I want to show you how general thisconclusion is by taking a quick look at an example that’s very different fromlanguage.
MAKING SENSE WITH PIXELSFor this we return briefly to the subject of digital images, this time focusing on
photographs. The pattern of hierarchical functional coherence is present here as
well. Just above the bottom level of pixels, digital photographs show coherence
analogous to a painter’s brushstrokes, where colors are extended and blended.
Above that is a level where boundaries and shapes are defined. Still higher is thelevel where features and objects are recognized, and above that comes the level
where the principal subject takes full form, along with the setting in which it wasphotographed. Noteworthy photographs exhibit an even higher level, where theway in which the subject was photographed evokes an impression that goes wellbeyond mere recognition.
The universal design intuition assures us that none of this happens byaccident, and again we can use the principle of reciprocal scale to confirm this.
Using a collection of low-resolution photos (400 pixels by 300 pixels), I wrote a
program that repeatedly picks one at random and copies a 2-by-2 pixel squarefrom a randomly chosen spot. Sample set 1 of Plate 1 (which can be found at theback of the book) shows a hundred examples of these 2-by-2 squares taken froma collection of fifty-nine photos. For comparison, sample set 2 shows a hundred
2-by-2 squares taken from a completely random image. The difference between
the two sets is visually striking. As eye-catching as the random squares are, theyclearly don’t extend or blend colors the way the photographic squares do.4 For
example, about half of the photographic squares give the first impression of
being one solid color, whereas none of the random squares do. Also, the 4 pixels
making up a square are immediately discernible for only a few of thephotographic squares, and in those cases the shade variations tend to bepleasantly subtle. For the random squares the opposite tends to be the case.
Notice the parallels between this comparison of pixel squares and ourprevious comparison of letter combinations. Just as we were able to spotincoherent letter combinations in small fragments taken from random typing(Figure 9.4), so too we’re able to spot incoherent color blending in small
fragments taken from a random image. In both cases coherence at this low levelis a necessary start for building a fully coherent functional hierarchy of the kind
represented in Figure 9.3, but it’s a very meager start. Much more challenging
levels of coherence must be built upon this low level if anything of significanceis to come of it.
To see how hard it would be for a blind search to stumble upon coherence at
any of the higher levels, all we have to do is build in the lower-level coherence.
We didn’t bother to demonstrate this for written instructions because theincoherence of those random seven-letter words convinced us that accidental
word choice is as problematic as accidental letter choice. To do thedemonstration for digital images, I used two of Mathematica’s5 imageprocessing commands to transform the random image on the left side of Plate 2
into the one on the right. As a result of this processing, the new image has
coherence not just at the bottom level of color extension and blending but also at
the higher level of shape and boundary formation. That much coherence wassupplied by the processing. Anything above that would be coincidental, and as
we plainly see, there isn’t anything above that—nor would there be if we were tospend the rest of our lives generating these images.
We can show that high-level functional coherence is hopelessly lost within
the space of possible images by doing a calculation similar to the one we did forthe space of possible keystroke combinations. If we say 1 in 20 squares fromsample set 2 looks at least somewhat blended in color, as though it might havecome from a photo, then the probability of a random image consisting only ofsuch squares is calculated by starting with 1 and multiplying by 1/20 over andover, a total of 30,000 times—once for each of the squares that make up the fullimage. The resulting number is the fractional coverage of the image space bythis very lenient target, so its reciprocal is—by the principle of reciprocal scale—the number of images a blind search would have to actualize to have areasonable chance of finding that target. By now we know what this means.
Were we to do the calculation, we would find this number to be so fantastically
big as to make hitting even this uninteresting target a physical impossibility.
Since the interesting target of all possible photos is much smaller, we know thatit too is hopelessly outnumbered by images that would look completely random
to us.
THE COMMON THREAD
For us to have made sense of such an odd assortment of inventions—digital
photographs, a jury-rigged contraption for removing CO2 from a space capsule,and half a page of written instructions—suggests we hit on something very
general with the concept represented in Figure 9.3. Everyone who undertakes
projects that require well-organized solutions should see something familiar in
the hierarchical structure represented there—and that means everyone. Thenagain, so should everyone who marvels at living things.
Before being wowed with life in chapter 10, let’s round out this chapter bycompleting our hike back down to the base of the mountain we just climbed. The
simple sea-level theme connecting everything we’ve discussed is theindispensable role of knowledge in the process of invention. Starting in chapter 2
with tasks so simple we don’t even associate them with invention—the makingof an omelet or the wrapping of a present—we recognized the necessity ofknow-how even for these small accomplishments. And because they requireknow-how, our collective experience tells us they’ll never happen unlesssomeone who knows how makes them happen. This conviction we expressed as
the universal design intuition: Tasks that we would need knowledge toaccomplish can be accomplished only by someone who has that knowledge.
The value of our climb to the summit is that we now see why this intuition iscorrect. The making of an omelet is, in the terminology of chapter 6, thecompletion of a whole project. It is the bringing together of many small thingsand circumstances in just the right way to produce a big result. And we now see
more precisely what we mean by this: those small things and circumstances must
be arranged in a functionally coherent way, such that they all work together toproduce something considerably more significant than the sum of the parts.
Arrangements of this kind never happen by accident because they can’t happen
by accident. Making an omelet is easy for us not because it requires no skill but
because we’ve mastered all the many simple skills it does require. And the very
fact that each skill had to be mastered—from the cracking of eggs to the movingof objects in a coordinated way—shows that accidents are not likely to match
those skills. Of all the things that could be tugged upon in the kitchen, the handle
on the refrigerator door is only one. And of all the things that could be put inmotion within the refrigerator—were it to be opened—the carton of eggs is only
one. And of all the ways the egg carton could be moved, only a thin sliver of
those possibilities is conducive to making an omelet. And so on. In the end,
however ordinary the making of an omelet seems, the fact that a great many
appropriate actions must be taken, each with a large number of ways to go
wrong, means that fully appropriate courses of action are utterly lost within the
staggeringly large space of raw possibilities. The advantage of know-how may
seem modest at each tiny step, but after multiplying all these modest advantages,
it becomes utterly decisive.
Knowledge is the primary ingredient of every omelet.
And if this is true for things as forgiving as omelets, then it’s also true for the
much more constrained things we call inventions. The fascinating conclusionfrom our mountaintop journey is that these special things—things that can only
be made by the clever crafting of physical materials and actions, shaping themand combining them in just the right way to achieve a big result—trigger ourdesign intuition for exactly the right reason. The reason we perceive purpose ininventions—busy wholes and whole projects—is precisely the reason they can’t
occur by accident: they exhibit an organized functional coherence that can only
come from deliberate, intelligent action. They are conceived from the top down

and constructed from the bottom up. They may operate by nothing more thanphysical causes, but they certainly don’t originate that way. For them to be
stumbled upon by coincidence, lost as they are within the vast space of raw
possibilities, is simply not an outcome our universe can deliver.
SUMMING UP
In chapter 5 we asked why the tasks we need knowledge to accomplish are neveraccomplished without knowledge, and now we know why. Figure 9.5
summarizes the whole line of reasoning by which we found our answer. The coreargument is simple enough to be stated in a single sentence:
SUMMARY OF THE ARGUMENT
Functional coherence makes accidental invention fantastically improbableand therefore physically impossible.
The conclusion is summarized even more succinctly: Invention can’t happen
by accident. Invention requires know-how, and there is no substitute for knowhow.
We did it! The dominoes have fallen. The conflict is over. Our design
intuition has won!
Of course, our journey can’t be replaced with two sentences. Use thesesummaries instead to gauge whether you’ve followed the argument in full and, if
you have, as a way of quickly bringing to mind the main ideas. The reasoning
isn’t complicated, as scientific arguments go, but certain aspects will have been
unfamiliar to many readers on first reading, which can be intimidating. Hang in
there! If you had the determination to make it this far, you have what it takes tograsp the main points, with perhaps a second look at those you foundchallenging on first read. The figure legend will guide you to sections you may
want to review.
In fact, even if you think the argument is wrong, I urge you to pause for a
moment to make sure you’ve understood it correctly. I have more to say topersuade you, but this is the time to make sure the argument you disagree with isthe one I’m making.

Figure 9.5 Two ways to conclude that inventions don’t happen by accident. When we encounter even avery simple invention, like an origami crane, we automatically infer intentional design by recognizing thatknow-how was needed. This is the universal design intuition, depicted on the left. Having now carefully
examined this inference, we see that it is fully affirmed by a series of sound deductions, which for theorigami crane are given as six numbered statements. The general form of the reasoning is summarized in
the single sentence on the right. For review, the universal design intuition is described in chapter 2; theconcept of functional coherence begins to take shape in chapter 6 (see “Busy Wholes and Whole Projects”);
chapter 7 shows that any inventive power in evolution must reside in repetition, not natural selection;
chapter 8 examines the role of repetition in blind searches, showing that fantastic improbability means
physical impossibility; and chapter 9 develops the idea of functional coherence fully, connecting it toinvention and showing insight to be its only possible cause by showing accidental causes to be fantastically
improbable.

CHAPTER 10

COMING ALIVE
The conflict within has been resolved. The tug-of-war between our design
intuition and the consensus view of biological origins has been won by ourintuition—handily so. As hoped, the win was not by the strength of technicalscience, though this certainly pulled for the winning side, but by the strength ofcommon science—reasoning and observations we can trust because they’re so
closely connected to what we know from experience.
As significant as all this is, it hasn’t yet given us a satisfactory answer to our
big question: To what or to whom do we owe our existence? We have only avague answer. We know we shouldn’t wake up every morning thanking either
natural selection or blind repetition for our lives. We know we weren’t hatchedby any egg-hunt search, which means we aren’t the offspring of any accidental
cause at all. This makes purpose a key ingredient of our origin—and perhaps
many of us would be content to leave it at that.
Thomas Nagel has convinced me we should go further. As an atheist, heseeks to “explain the appearance of life, consciousness, reason, and knowledge
neither as accidental side effects of the physical laws of nature nor as the resultof intentional intervention in nature from without but as an unsurprising if notinevitable consequence of the order that governs the natural world fromwithin.”1 Because our main accomplishment to this point has been to rule out theaccidental cause that Nagel rejects, he would agree with us.
On the one hand, I view his agreement up to this point as a good thing,considering the quality of his thinking. On the other hand, because my purposein this book has been to identify the source from which we came, I as a Christian
thinker will feel as though I’ve come up short if an atheist thinker can be inagreement the whole way—even an exceptional atheist thinker like Nagel. We
need to press on with the aim of reaching a more clear understanding of thisnonaccidental source from which we came—an understanding that fits either
Nagel’s view of an impersonal power within nature or my view of a personal

power outside nature, but not both.
These next four chapters of our journey will provide this understanding
naturally without being overly forced to that end. We’ll also address the mostcommon reasons for doubting our conclusion that the design intuition has won.
Both of these aims call for a closer look at life than we were ready for in chapter
6, benefiting now from our refined understanding of invention. This chapter willserve that purpose.
TAKING INVENTION TO A WHOLE NEW LEVEL
However artfully humans have harnessed the regularities of the universe—fashioning the elements into things like smartphones and space telescopes—wecan’t escape the realization that someone has outdone us. The busy spider, theheroic salmon, the graceful orca, indeed all the living masterpieces that surroundus demonstrate that physical materials and processes can be put to use much
more elegantly than we ever have. Mind you, I say this as a lifelong technophile,
not at all to disparage human invention but rather to remind us that life occupies
a category that is unquestionably above human invention.
For example, among the more advanced products of human technology is asolar-powered underwater vehicle called Tavros 2. Operated by the University ofSouth Florida, Tavros 2 was designed to conduct monthlong missions in the Gulf
of Mexico, measuring and reporting water depth and temperature. What makes
this vehicle particularly sophisticated is that it operates autonomously, under thecomplete control of its onboard computer. Tavros 2 is programmed to rise to thesurface when it needs a solar recharge, after which it dives to its previous
location and resumes data collection. If this aquatic robot had a résumé, GPSnavigation would be listed under the Technical Skills heading, and tweeting
would be under Other Interests, this being how it sends data back to thescientists at the marine lab (or to anyone else who likes to follow nerdy tweets).
But try comparing Tavros 2 with something living. Dolphins, being ofroughly the same size, might seem like a suitable species for comparison, but nosooner do we begin the exercise than we realize how incomparable these twoinventions are. Like all robots, Tavros 2 does exactly what it was programmed todo, whereas dolphins seem to do whatever they want to do. One is a physicalmachine while the other is, by all appearances, something profoundly greaterthan that—something beyond the mere physical.
In chapter 13 we’ll explore the significance of this profound difference. Fornow, though, let’s continue to concentrate on the physical aspects of living things—aspects that resemble machines, albeit machines of a most remarkable kind.
We’ll see that the machinery of life displays functional coherence on a scalethat’s presently beyond human comprehension, to say nothing of humanimitation.
HIGH-TECH POND SCUM
We’ll start with a living “machine,” by which I mean a form of life that, unlike
dolphins, appears to operate in an entirely physical way. Far simpler than any of
the individual cells within a dolphin is a lowly form of aquatic microbial life
called cyanobacteria. Although cyanobacteria are single-celled organisms, theindividuals of some species adhere to one another to form long filaments thatinterweave into huge mat-like colonies in stagnant or slow-moving water. They
are, quite literally, the pond scum of the earth.

Figure 10.1 Tavros 2 being deployed by a University of South Florida researcher.
Tavros 2, Bgregson, used under the Creative Commons license CC BY-SA 3.0, via Wikimedia Commons.

Despite occupying that humble position in the grand scheme of life,
cyanobacteria are light years ahead of Tavros 2 in terms of their technicalsophistication. To see this, let’s do some comparing and contrasting. One notablesimilarity is that Tavros 2 and cyanobacteria are both solar powered. However,when we examine this feature in more detail, we find that the two aren’t reallycomparable. The nonliving machine needs a solar collector the size of a coffee
table, whereas the living one does very well with a collector roughly onetrillionth that size. And while the nonliving machine has only one trick forgetting sunlight—surfacing—the living one is capable of much more.
Filamentous cyanobacteria do control their depth in response to sunlight, butthey’re also able to coordinate complex sliding and oscillating movements tomake their entire colony face toward the sunlight. So in terms of sophisticationof movement for capturing sunlight, cyanobacteria have Tavros 2 beat hands
down (or maybe filaments down).2
The contrast becomes even more extreme when we consider manufacturing
capabilities. Tavros 2 has none, whereas every cyanobacterium houses an entire
manufacturing plant within its microscopic walls. Powering all the operations of
this plant is the process known as photosynthesis, which converts light energy
into chemical energy. Much of this chemical energy is used to make sugar
molecules from CO2 and water, giving off oxygen (O2) as a by-product. Sugar istherefore energy rich, which means that cells can “burn” it for calories.
Alternatively, sugar serves as a versatile carbon compound cells can use to build
the huge variety of other carbon-rich molecules needed for life.
Although we think of photosynthesis as a natural process, in the sense thatit’s happening all around us in nature, in another sense it is very unnatural. Morethan any human invention, photosynthesis is an ingenious exploitation of thenatural regularities of the universe, radically different from anything thoseregularities produce on their own. To grasp this, think of photosynthesis as thereverse of burning fuel, because that’s what it amounts to. Burning is a very
natural process, whereas unburning is not. With just a spark to get it going,oxygen readily consumes fuel molecules like sugars in its flames, forming CO2
and gaseous water. By doing just the opposite, photosynthesis earns a position as
one of those clever inventions, like air-conditioning, that harnesses natural
regularities in order to work against them. And of these two inventions,photosynthesis is more clever by far.
The challenge for me is to give a sense of this without giving the equivalentof two or three chapters of textbook biochemistry. Thankfully, that can be donein much the same way that a wonderful book called Stephen Biesty’s Incredible
Cross-Sections gives us a sense of the engineering complexity of things likerescue helicopters and space shuttles.3 Biesty artfully cuts the exterior away toshow us how all the parts are arranged inside. Let’s use a similar approach with

photosystem I, one of the major components of the cyanobacterial photosynthetic
apparatus. The parts list for this engineering marvel (Figure 10.2) shows twelve
protein parts and six smaller parts called cofactors, one of which (chlorophyll a)
is used 288 times to build the full photosystem. These essential cofactors areheld in their precise positions by the large protein framework, as shown in
Figure 10.3.
The complete photosystem I shown at the bottom of Figure 10.3 has 417
pieces, each precisely positioned for the whole device to perform its function ofgathering photons from the sun and converting their light energy into chemicalenergy. By my count, about three dozen genes in the cyanobacterial genome arededicated to building this assembly: a dozen for encoding the protein
components and two dozen more for encoding the enzymes needed to
manufacture the cofactors. The whole assembly is massive in molecular terms,
but with a diameter of just twenty-two billionths of a meter, fifteen million ofthese things could fit in an area the size of a single pixel on an iPhone Retina
display!

Figure 10.2 Parts list for building the cyanobacterial photosystem I.

For those interested in learning about how the antenna system or the electrontransfer chain (both shown in Figure 10.3) perform their respective functions
within photosystem I, good resources are available online.4 But you don’t haveto do any in-depth study to be fully convinced that photosystem I is an ingenious
nanotechnological invention. All you have to do is let the diagrams speak forthemselves.

Figure 10.3 Cyanobacterial photosystem I with two of its important components shown above.

The very fact that the terms electron transfer chain and antenna system areused by the scientists who study photosystem I tells us that this photosystem’s
overall function involves multiple subfunctions, including the transfer ofelectrons and the collection of photons by an antenna. If you do decide to delve
into the technical literature, you’ll find a host of other functional descriptors,
including docking site, primary electron donor, initial electron acceptor, andquenching carotenoids. Even if most of us have no clue what these terms mean,
we all see that the high-level function of photosystem I depends on an extensive
hierarchy of lower functions, and that should seem very familiar. This is anotherexample of hierarchical functional coherence, made particularly striking by thetiny scale on which it has been implemented. As always, we immediately
perceive this pattern to be a signature of purposeful invention.
As complex as photosystem I is, it’s only one component of the many thatmake up the whole photosynthetic system. Figure 10.4 gives us an idea of how

complex this whole system is. The figure is arranged in a hierarchical structurethat should remind you of Figure 9.3. Topping the hierarchy is the cyanobacterial
cell, shown as an actual cross-sectional image taken with an electron
microscope. Below that is the photosynthetic system, which, though it is shownalone, is just one of many systems needed to support the top-level function ofliving life as a cyanobacterial cell.
At the next level down, the photosynthetic system is composed of two
components:thethylakoid-membrane
systemandtheCO2concentrating/reacting system. The first of these is responsible for harvesting
light energy and converting this into chemical energy. The second is responsible
for using this chemical energy to “unburn” CO2. The major structures associatedwith both of these component systems are large enough to be visible in theimage at the top. The concentric bands seen around the perimeter of the cell are
the layers of light-catching thylakoid membrane. The large dark spots inside thecell are the carboxysomes, the reaction vessels in which the unburning takes
place.

Figure 10.4 The hierarchical organization of the whole photosynthetic system of cyanobacteria.
Elements from “Localization of Membrane Proteins in the Cyanobacterium Synechococcus sp. PCC7942:

Radial Asymmetry in the Photosynthetic Complexes,” Debra M. Sherman, Tracy A. Troyan, and Louis A.
Sherman, Plant Physiology © 1998 (used with permission) and from “Atomic-Level Models of theBacterial Carboxysome Shell” Shiho Tanaka et al., Science 319, 1083 (2008); DOI:
10.1126/science.1151458 (reprinted with permission from AAAS).

All of these functions require exquisite technical sophistication. The
thylakoid membrane, for example, forms compartments that are so well sealed
that even a tiny proton (a hydrogen atom stripped of its electron) can’t passthrough the barrier except by going through a sophisticated protein channel thatsystematically moves it from one side to the other. Some of these channels(photosystem II and the cytochrome b6f complex) act like tiny pumps, forcing
protons from the “low pressure” side of the compartment to the “high pressure”
side, while another (ATP synthase) acts as a turbine, extracting energy byallowing protons to flow the other way.
This is just a snapshot of the complexity of photosynthesis. Volumes havebeen written on the subject. And as amazing as the functional coherence
represented in Figure 10.4 is, it becomes even more amazing when we consider
the highest level of the hierarchy, where the many functions coalesce into one
purpose. From this top-level vantage point, we see that photosynthesis, for all its
stunning sophistication, is only one of the major functions needed forcyanobacteria to fulfill their purpose of being cyanobacteria. Ultimately, all themolecular assembly lines inside a cyanobacterial cell and all their associatedgenes and regulatory circuits do what they do in order for cyanobacteria to taketheir place among the spectacular living inventions that surround us—each so
good that they cannot be other than what they are. When viewed through thislens, photosynthesis is one of those exquisite smaller inventions that serves its
higher purpose so well as to make itself almost invisible.
And if the ability of cyanobacteria to make sugar from sunlight, air, andwater has our eyes popping and jaws dropping, as indeed it should, try to
imagine a proportionate response to the fact that they also make cyanobacteria
out of those same raw natural ingredients!5 In fact, they make sugar only as astep toward making everything else—all the strikingly complex molecules thatmust be knit together into all the astoundingly complex systems andsuperstructures needed to form a living cyanobacterium.
It boggles the mind.
We’re left to think that poor Tavros 2 is really no more worthy of comparison
to a lowly cyanobacterium than it is to an exalted dolphin. After all, raw naturalingredients like sand and metal ores and crude oil became Tavros 2 only with theskillful help of thousands of people at hundreds of industrial plants of various
kinds. With all due respect, this human invention does very little in comparison
to the human effort expended to manufacture it. The contrast with cyanobacteria
could hardly be more stark. With almost paradoxical genius, the inventor ofthese living marvels endowed them with the ability to manufacture
cyanobacteria by themselves! That is, once the first cyanobacterium was made,however that happened, the rest were manufactured by cyanobacteria exactly as
they are today—from air and sunlight and water.
Again, the mind boggles.
COHERENCE ON STEROIDS
The cyanobacterium proves itself to be a dizzyingly impressive busy whole byaccomplishing a dizzyingly impressive whole project—the manufacture of
cyanobacteria—with apparent ease. And if that is so, then the toiling spider andthe heroic salmon and the elegant orca can hardly be anything less. The sense of
awe and wonder stirred in us by the humble cyanobacterium is only the
beginning.
To leave you with a taste of the elegant complexity underlying familiar
aspects of higher life, I have in Figure 10.5 traced one branch of the mammalianvisual system from the top of its functional hierarchy down to the level of small
molecules. Again, the point is merely to see the complex functional hierarchy
that supports vision without having to understand it. However we choose torepresent this hierarchy—however finely we divide the levels or the componentsthat occupy each level—the hierarchy itself is very real and very impressive.
We’ve only scratched the surface, not just in breadth but also in depth. The
truth is that living organisms are functionally coherent in a much more profoundsense than human inventions are. Everything in an orca is completely andexquisitely devoted to the top-level purpose of being an orca. Every cell in the
body both sustains the body and is sustained by the body. Living inventions are
therefore all-or-nothing wholes—utterly committed to being what they are. The
body is alive and thriving when all its parts are working, or it is dead anddecaying when they are not. Apart from humans and the animals we tend to,nothing lingers very long between those polar extremes.

Figure 10.5 One branch of the functional hierarchy that supports vision in mammals. Filled circles indicate
the component at each level that is chosen for expansion at the next level down. To picture the fullcomplexity of the hierarchy, imagine that each of the unexpanded circles has been expanded to form a verylarge inverted tree (trunk at the top with five main branches, each dividing into many subbranches, and soon). The protein shown is rhodopsin. This protein holds a single molecule of vitamin A, seen in the middle.
When the vitamin A molecule absorbs a photon of the right color, it changes shape, causing the wholerhodopsin to change shape. This initiates a chain of responses culminating in the neural signals that areperceived as light. Although this chain is triggered by a single photon, the visual processing system filters
the signal to suppress the perception of light unless several absorption events occur in a short time in thesame region of the retina. For humans, it takes about a dozen or so photon-absorption events for light to beperceived, whereas cats and owls can see the light of just a few photons!

Cars and smartphones and pool robots are not nearly so unified in theiroperation. They do fail when a key component fails, but in most cases theremaining components are unaffected by that failure. The reason for this is thathumans don’t manufacture all-or-nothing wholes. Instead, we manufacture
things part by part and then assemble the parts into a whole. Each part is madeand tested independently, according to its own specifications, and indeed, manyof these continue to be tested and replaced periodically even after they’reincorporated into a whole. Life is nothing like that. Somehow, almost
unbelievably, living inventions play a key role in building and maintaining

themselves—all their parts formed and knitted together in unison within thewhole. Life is never anything but whole.
The mind boggles.
Unlike human inventions, living inventions are all-or-nothing wholes.
Every cell in the body both sustains the body and is sustained by the body.
Life is never anything but whole.

MAKING SENSE WITH AMINO ACIDS
We’ve seen from the laboratory experiments discussed in chapters 6 and 7 thatDarwin’s molecular fiddler is not at all adept at inventing new proteins, and in
this chapter we’ve seen how deeply functional coherence runs through biologicalsystems built from proteins. Until now, these may have seemed like separate
problems for blind evolutionary searches: the problem of finding new proteins
and the problem of finding helpful inventions that use proteins. In fact, the root
problem in both cases is the impossibility of finding the necessary functional
coherence by blind searches, because proteins, as molecular inventions, exhibit
impressive functional coherence in themselves.
Figure 10.6 helps us understand what functional coherence means in thecontext of a single protein chain. The value of ribbon diagrams like the one
shown on the left side of the figure is that we can see where the chain forms
either of the two regular conformations that characterize all folded proteins:alpha helices (shown as coils) or beta strands (shown as arrows). But that visualclarity comes at the cost of oversimplification, as the more physically accurate
stick representation on the right shows. Among the sticks we can, with someeffort, discern a jagged version of the graceful path traced out by the ribbon on
the left, but we also see what appears to be a messy jumble of darkly coloredappendages jutting out from that path in all directions. Believe it or not, thefunctional coherence of this protein lies within that complex “jumble,” and thesame goes for every other folded protein.

Figure 10.6 The role of the amino-acid appendages in forming protein structures. The three pictures each
depict a portion of the smaller of two proteins that form the photosynthetic enzyme rubisco (shown at thebottom right of Figure 10.4). The middle image is a superposition of the ribbon diagram (left) and the stick
representation (right).

As we learned in chapter 3, the different appendage types are what
distinguish the twenty amino acids. What looks like a mess to us is really an
exquisite arrangement of amino-acid appendages along the whole protein thatcoaxes what would otherwise be a long floppy chain into forming a stable threedimensional structure. Arranged sequentially in that special way, the appendages
are more comfortable fitting snugly into their folded conformation than theywould be flopping around wildly in the cellular fluid, the way a random
sequence of amino acids does. Without their snugly folded conformations, theproteins of life couldn’t perform their vital functions.6
Just how exquisite are the arrangements of amino acids that cause protein
chains to fold, then? This is what I set out to measure with the experimental
project I described at the start of chapter 5.7 My aim in that work was to measure
how improbable functional coherence is for these amino acids, in much the same
way we assessed this for letters and pixels in chapter 9. I started by making lotsof variants of the weakly functional penicillin-inactivating enzyme I describedback in chapter 7 (the one that could be optimized by selection because it was
already working as an actual enzyme). In each variant, a group of ten
appendages that form a cluster, as shown in Figure 10.7, was replaced withrandom alternatives. You can think of the appendages within these clusters as
being like letters or pixels in groups: the bottom-level parts must work together
to produce something coherent. The idea was to assess this coherence by findingout how hard it is for a random assortment of appendages to be as functionallycoherent as the appendages they replaced, meaning just coherent enough for the
enzyme to work.
Once this was determined experimentally for the four clusters shown, thenext step was to calculate the improbability of evolution stumbling upon thatminimal functional coherence not just in those four clusters but in all the clusters
needed for the protein to fold. I did this by converting the fraction of mutants
that worked in each of the four experiments into an average probability offunctional coherence per amino acid. I then multiplied this to estimate thelikelihood of a fully randomized gene having the functional coherence needed toform a structure that supports enzyme function. As I said at the beginning ofchapter 5, the result was striking. Of the possible genes encoding protein chains
153 amino acids in length, only about one in a hundred trillion trillion trillion
trillion trillion trillion is expected to encode a chain that folds well enough toperform a biological function! So as hard as it was for our noise-seeking robot inchapter 7 to find a stadium, finding a biological invention is much harder, evenat the low level of a single protein. We estimated that stadium noise may cover
one part in a hundred thousand of the earth’s surface, but the result here paints amuch bleaker picture. Instead of the earth’s surface for a search space, try
picturing a sphere the size of the visible universe—twenty-eight billion lightyears in diameter—and instead of a target that covers six thousand square
kilometers, try picturing one the size of a hydrogen atom! Now, that’s a target we
can safely write off as lost in space!8

Figure 10.7 Two of the four clusters of ten amino-acid appendages that I randomized in order to measure
the rarity of functional coherence are shown in the left picture; the other two are shown in the right picture.
The beta-lactamase enzyme consists of a single protein chain 263 amino acids long. Its full structure divides
visually into two portions called domains, which appear to be distinct units of folded structure. I focused on
the larger of these two domains, which consists of about 153 amino acids. This one is shown as a ribbon
diagram with randomized appendages shown as sticks. The other domain is shown in surface
representation.

INVENTION TOP-TO-BOTTOM

As convinced as I am that protein folds are ingenious inventions in themselves, I
don’t want to give the impression that all of life’s genius resides in proteins.
Clearly it doesn’t. As should be clear from Figures 10.4 and 10.5, the clever
arrangement of amino acids to form working proteins is just one aspect of theexquisite design of life, and one that occupies a relatively low position in thefunctional hierarchy at that.
But while the invention of new life forms is undoubtedly a loftier exercise
than the invention of new protein forms, that lofty exercise seems to require
mastery of the lower-level exercise. One of the great surprises to come fromgenome sequencing projects is how many unique genes, and therefore proteins,are present in each form of life, including forms that to us look only subtly
different. For example, a group of German scientists recently examined the
genome sequences from sixteen cyanobacterial strains in an effort to discern all
the distinct kinds of genes these strains carry.9 Since they’re all cyanobacteria,
you might think they would carry the same set of genes, with perhaps an extra
gene here or a missing gene there. The scientists found that they do share acommon set of 660 genes, meaning not that these genes are identical from one
strain to the next but rather that they are similar enough that we can be quite
certain they encode proteins that fold to the same overall structure and performthe same biological function. Much more surprising, though, was their findingthat nearly 14,000 genes are unique to individual strains! At an average of 869
unique genes per strain, this makes these bacterial strains more geneticallydifferent than alike, despite their overall external similarities.
The proportion of species-specific genes varies from one species to the next,
but their existence in large number seems to be a property of all life, not justcyanobacteria. To quote the abstract of a recent technical paper, “Comparative
genome analyses indicate that every taxonomic group so far studied contains 10–
20% of genes that lack recognizable homologs in other species.”10 In otherwords, every species has many genes that seem, at first glance, to be one-offs—
unlike any gene found anywhere else. The painstaking work of finding thestructures of the proteins these genes encode is showing that about two-thirds
turn out to resemble previously known proteins, with the remaining third being
genuinely new.11
The origin of new categories of life does therefore seem to require the originof new genes and proteins. Again, this isn’t at all to say that the two areequivalent, but only that the one entails the other, with profound implications.
Just as mastery of spelling and vocabulary is only the first step toward masteringwriting, so too mastery of protein design is only a basic step toward mastering
the design of life. The fact that mastery of this basic step is completely beyond
the reach of blind evolution is therefore evolution’s undoing. In the end, tobelieve the evolutionary story is to believe something much less plausible thanhitting the cosmic cuna target—an atomic dot on a universe-size sphere—overand over in succession by blindly dropping subatomic pins.
No one should believe that.
THE FRUITS OF COMMON SCIENCE
What we have deduced to be true of inventions generally—that they cannot
happen by accident—is all the more true of the particularly remarkableinventions we see in life. What we realized at the end of the previous chapter—that omelets are completely lost within the space of kitchen possibilities—we
can now extend to protein molecules within the space of amino-acidpossibilities. And what is true for proteins is all the more true for the higher
systems that use proteins for functions like photosynthesis and vision, and still
more true for whole organisms occupying that highest of levels where the many
functions coalesce into one purpose. Just as instructions and poems and love
letters are completely absent from the mountains of QWERTY gibberish that canbe accessed by blind searches, so it is with life. To do this activity we call living
is so remarkable a feat that it can only be done by something extraordinarily wellconceived and fashioned. Each and every new form of life must therefore be amasterful invention in its own right, embodying its own distinctive version offunctional coherence at the very highest level.
I can only see these ingenious creeping, climbing, swimming, soaring,blooming, burrowing, luring, lunging, spinning, sporulating, fleeing, andfighting inventions as having come from the mind of God. To me, nothing else
makes any sense.12 That each one occupies its own unique place in our minds
must surely reflect the fact that they were given their own places in theworkshop of that supreme mind. There is no room for nonsense there—nothought of one masterpiece smearing into another, as if brilliant ideas could be
blended like paint. That we have been chosen to behold the living wonders ofthat workshop ought to astound us, the keepers of our own workshops where welabor over much smaller projects. That we came from that workshop should
astound us all the more. Among all the wonders that make Earth their home, wealone are compelled to stop and stare, to take this whole spectacle in—five parts
inspiring to one part troubling—and to ponder it, knowing that none of it isaccidental.
The children have been right all along.

CHAPTER 11

SEEING AND BELIEVINGThe courage to defend our design intuition comes not just from the commonscience argument we’ve developed but from the bigger picture as well.
Everything seems to fit. Humans stand apart from all other living things as theone species that seeks wisdom and knowledge—the sapient species (Homosapiens). If we knowers were meant to be, then surely we were meant to know
we were meant to be. And indeed we do. Well before our formal education
begins, we have already mastered the simple science of interpreting oureveryday experiences. This science produces in our young minds the universal
design intuition. With or without parental approval, we know instinctively thatliving wonders so remarkably good at being what they are—spiders being
spiders and orcas being orcas—exist only because someone made them for the
express purpose of being what they are. If you saw this instinct as being moreheart than head before you started reading, I hope our journey has corrected thatimbalance.
Does anything not fit, then? This is an important question to ask whenever
we think we’ve come to a correct understanding of a contentious subject. It’s nota question of completeness but rather a question of contradiction. Indeed, as
we’ll see in the final chapter, acknowledging that science shows life to be
designed hardly begins to answer the important scientific questions. It merely
opens the door to a correct conception of biology—a door that has been blocked
and barred for well over a century. The weighty intellectual challenge of buildingthat long-awaited correct conception—after thinkers have filed through this doorin large number—has barely begun. And that’s perfectly fine.
The first aim for this chapter is simply to consider whether we’ve overlooked
any facts that somehow refuse to fit into this otherwise coherent picture of adesigned world. If we haven’t, my next aim will be to equip experts in common
science—like you—to stand firm in a world where certain experts in technicalscience do their best to push others around.

To begin, we look to those who’ve been working under the flag ofmaterialism, which (unsurprisingly) is also the flag of Darwinism.
THE VIEW FROM THE STANDS
According to journalist Paul Rosenberg, writing for Salon, “things could get awhole lot worse for creationists because of Jeremy England, a young MIT
professor who’s proposed a theory, based in thermodynamics, showing that the
emergence of life was not accidental, but necessary.”1 By necessary, Rosenberg
means so physically inevitable as to be unremarkable. England does seem toespouse this no-big-deal view of life’s origin. “You start with a random clump of
atoms,” he says, “and if you shine light on it for long enough, it should not be sosurprising that you get a plant.”2 Rain happens. Life happens.
What are we to make of this? In particular, what should you do if you feelcertain this MIT professor is wrong but also know you’ll never be able to follow
his argument? You could search the web to find people with Ph.D.s who dispute
his claim, but there would probably be people with Ph.D.s who dispute thedisputers as well. And so on. In the end, this technical to-ing and fro-ing gives
little aid to nonexperts, apart from the comfort of knowing that at least someexperts are on their side.
However, if the decisive matters in this discussion belong not to the technicaldisciplines but rather to common sense and common science, as I’ve claimed,
then this picture of nonscientists as spectators at a sporting event—where most
players are wearing the Darwin jersey—is all wrong. When it comes to simple
intuitive reasoning, the playing field is level, and everyone is qualified to play.
THE INCONCEIVABILITY OF ACCIDENTAL INVENTION
As common scientists move down from the stands and flood the field, the mostimportant advice for them to bear in mind is the familiar call to “keep your eyeon the ball.” We have arrived at what looks to be a decisive argument. In asentence: Functional coherence makes accidental invention fantastically
improbable and therefore physically impossible. Invention can’t happen by
accident. This is the ball, then. To become distracted by any defense of
accidental origins that doesn’t answer this argument is to take our eye off theball. Instead, we’re wondering whether there’s a single piece of work out therethat should convince us this argument is wrong.
What would this even look like? Can we be wrong to attribute functional
coherence to biological systems? I can imagine people thinking this is wrong,but only out of ignorance. Certainly ignorance as to the necessity of functional
coherence within cells existed among some biologists of Darwin’s day. Writingin 1868, nine years after the publication of On the Origin of Species, German
biologist Ernst Haeckel said the following about aquatic microorganisms heclassified under the heading Monera:
These very simplest of all organisms yet known, and which, at the sametime, are the simplest imaginable organisms, are the Monera living inwater; they are very small living corpuscles, which, strictly speaking, do
not at all deserve the name of organism. For the designation “organism,”applied to living creatures, rests upon the idea that every living natural
body is composed of organs, of various parts, which fit into one anotherand work together (as do the different parts of an artificial machine), in
order to produce the action of the whole. During late years we havebecome acquainted with Monera, organisms which are, in fact, notcomposed of any organs at all, but consist entirely of shapeless, simple,
homogeneous matter. The entire body of one of these Monera, during
life, is nothing more than a shapeless, mobile, little lump of mucus orslime, consisting of an albuminous combination of carbon. Simpler ormore imperfect organisms we cannot possibly conceive.3
As you may have guessed, cyanobacteria—the stunningly sophisticatedphotosynthetic marvels we encountered in chapter 10—are among the bacterial
species to which Haeckel referred here. He couldn’t have been more wrong
about their internal structure, and moreover, his error can’t be excused as though
no one knew better back then. Some two hundred years earlier Antonie van
Leeuwenhoek, one of the pioneers of light microscopy and the father ofmicrobiology, observed the complex powered movement of many bacterial
species in water.4 Add to this the observation of bacterial cell division and theconclusive demonstration by Louis Pasteur that bacteria only come from bacteria—all well in place before 1868—and there’s really no excuse for Haeckel tohave missed the fact that remarkable processes were going on inside these little
creatures. Indeed, the tiny scale of those processes should have brought
recognition that they had to be far more sophisticated than the artificial

mechanisms he mentioned—clocks and steam engines and the like.
Despite his blunder, the quote shows that Haeckel had a well-formed notionof functional coherence, evident in his description of a hierarchy of components
working together to form a functional whole. What he lacked was the convictionthat sophisticated functions are never achieved without functional coherence. No
one with an interest in biology makes this mistake today. That living things all
the way down to bacteria are chock-full of systems that exhibit functional
coherence all the way down to their molecular constituents is now such apervasive theme in biology as to be unmissable.
As for the connection between functional coherence and fantastic
improbability, here again we have something that can be overlooked but notrefuted. Interestingly, even one of the most ardent defenders of Darwinism inrecent times, Richard Dawkins, has not overlooked it. The first chapter of his
1986 book The Blind Watchmaker is titled “Explaining the Very Improbable.”
There he describes the connection as follows:
However many ways there may be of being alive, it is certain that there
are vastly more ways of being dead, or rather not alive. You may throw
cells together at random, over and over again for a billion years, and notonce will you get a conglomeration that flies or swims or burrows or
runs, or does anything, even badly, that could remotely be construed asworking to keep itself alive.5
The very same principle applies at levels above and below the cell. Coherent
skeletons are impossibly rare among random arrangements of bones, as arecoherent body plans among random arrangements of organs, and molecularmachines among random arrangements of folded proteins, and folded proteinsamong random arrangements of amino acids. According to our analysis, none ofthese inventions had any prospect of coming together by accident. They all
required insight.
Dawkins still thinks natural selection can do the work of insight, but weknow better. Interestingly, his own words point to the gaping hole in Darwin’s
theory, which we saw back in chapter 7. Natural selection happens only after
cells are arranged in ways that work to keep the organism alive, so selection canhardly be the cause of these remarkable arrangements. Darwin’s simplistic
explanation has failed, and the millions who have followed him have nothing but
his outdated assumption to stand on.

The stepping stones over which these followers think life has skittered fromone form to the next are definitely not explained by natural selection. Selection
steps to forms that already exist, so it doesn’t explain the forms themselves,much less the intricately engineered circumstances that would have been needed
for these forms to be connected through lines of descent. And the problem nevergoes away. Because the impossibility of accidental invention is at the root, andbecause each new form of life amounts to a new high-level invention, the originof the thousandth new life form is no more explicable in Darwinian terms thanthe origin of the first. Even if we suppose a first insect to have been formed
somehow—without trying to explain how—all the countless insects that differ
substantially from that first one would still be new top-level inventions. The
component inventions common to all insects would have had their specificrepresentations in that first insect, but a great many of these components would
have had to be substantially reworked to suit each new insect. This would havebeen a staggering feat of re-engineering in itself, to say nothing of the great
variety of new components that would have had to be invented from scratch. In
the end, each new form of life amounts to a stunning new invention, and since
the hallmark of invention is functional coherence—which accidental causes can’t
explain—we rightly see each form as a distinct masterpiece.
Accident is out of the picture. Stepping stones connecting these masterpieces
are either a figment of our storyteller imaginations or proof that God has, attimes, converted the world into an exquisite nanofabrication facility. There is no
substitute for brilliance, so either the stones are part of the brilliance or they
aren’t anything at all. The genius of life is not in question. The only question is
how The Genius of life did his work.
Because each new form of life amounts to a new high-level invention, theorigin of the thousandth new life form is no more explicable in Darwinian
terms than the origin of the first.

TOURING ENGLAND
Returning to England—Jeremy England—and my aim of liberating readers fromtheir dependence on experts, I don’t mean to suggest that nonexperts should
ignore the debate among experts. The reward for following that debate, even as acasual observer, is a sense of how things are shifting within the academy, which
is worth having. So while I hope every reader is able to say why England’s
equationlight + random atoms + time = living plant
can’t be correct, I think readers will also be interested to know how one of theworld’s leading chemists views this idea of life originating by chemical accident.
I’m referring to Jim Tour, professor of chemistry and nanoengineering at
Rice University, whom I met after a stunning presentation he gave at a meetingat Baylor University in 2009. The best way I can describe his work is to say that
he and his team do with atoms what kids do with construction toys. If you think
I’m kidding, try googling nanocar or nanodragster.
When it comes to understanding, from firsthand experience, the difficulty ofmaking atoms come together to form molecular devices, very few people canmatch Jim Tour. I certainly can’t, and I’m pretty sure Jeremy England can’teither. With all due respect to England and his theory, then, it would beinteresting to know what Tour thinks about the casual confidence so many
scientists seem to have in the ability of unguided natural processes to build
complex molecular devices.
Thankfully, we don’t have to wonder about this. Speaking of the separationof helpful products from unhelpful ones after each step in a complex synthesis
procedure (without which the procedure would fail), Tour says:
If one asks the molecularly uninformed how nature devises reactions
with such high purity, the answer is often, “Nature selects for that.” But
what does that mean to a synthetic chemist? What does selection mean?
To select, it must still rid itself of all the material that it did not select.
And from where did all the needed starting material come? And how
does it know what to select when the utility is not assessed until many
steps later? The details are stupefying and the petty comments
demonstrate the sophomoric understanding of the untrained.6
In other words, the only thing people demonstrate when they assume suchthings can happen by accident is that they don’t know what they’re talking
about.

THE MAGICIAN’S HAT
For those occasions when you don’t have someone like Tour at your side, here’s
a simple way you can test supposed proofs that accidental invention works.
Think of the illusion of pulling a rabbit out of an empty hat. What makes thistrick entertaining is that we seem to be witnessing the impossible. We know arabbit can’t come out of a hat unless it first went in, and yet we have theimpression that nothing went in except the hand now holding the rabbit. It looks
like magic in terms of this immediate impression, but a broader perspective
assures us it’s merely an illusion, even if we have no idea how the trick was
performed. After all, if anyone really had the ability to bring things into
existence out of nothing, they would find a more productive way to use theirsuperpower than by working as an entertainer.
Both the impression of magic and our ability to analyze that impression inthis way—by surveying the bigger picture—will help us know what to make ofsupposed demonstrations of the power of evolution. Think of the hat as aconceptual black box that surrounds and conceals all the inner workings of oneof these demonstrations. As with the rabbit trick, our strategy is to compare whatwent in with what came out, without worrying about what happened inside. In
doing this, we should pay particular attention to knowledge because of its
essential role in invention (Figure 11.1).
The first question to ask of a demonstration is whether it even gives theappearance that the impossible has occurred. If not, then it clearly doesn’t
address our argument. Our claim is very simple. Having noticed that we
intuitively know invention can’t happen by accident, we believe we’ve now
come to a firm understanding of why this intuition must be correct. To counter
this claim, someone would have to show that what both intuition and calculation
affirm to be impossible somehow isn’t impossible. Anyone not even pretending
to do this hasn’t understood what needs to be demonstrated.

Figure 11.1 Using the magician’s hat to test demonstrations. The beauty of this approach is that you don’t
have to know what happens inside the hat. You simply ask whether what came out—the final effect oroutcome—can be explained in terms of what went in. Examples are given in pairs to show how a correct
result requires correct identification of the inputs and outputs. Notice that only if what happened required
knowledge and no knower was present do we conclude that magic has occurred.

Of the many demonstrations I’ve encountered over the last thirty years, notone passes this test of relevance. No one has said, “Look! We’ve found a way forthe impossible to happen!” Instead, they offer unsurprising examples where
searches that should succeed do, or where selective homing that should work
does. In doing so, they ignore the fact that invention by accident requires
fantastically improbable searches to succeed. Since that is the unbelievableclaim, that is what they would have to demonstrate. And if they did? Well, theirdemonstration would be the world’s first scientifically proved, mathematicallyvalidated instance of magic. Even then, I think we would find it viscerally
impossible not to attribute the outcome to an invisible knower, which would
leave our design intuition intact.
PASSING THE HAT (OR NOT)A couple of examples will prepare you to use the hat yourself. The first is ademonstration that Richard Dawkins offered in The Blind Watchmaker, where acomputer program started with a random sequence of twenty-eight letters andspaces and ended up with the Shakespearean line METHINKS IT IS LIKE A
WEASEL, supposedly by evolution. Let’s ignore how the program worked for a
moment in order to see how the hat works. In this case, since Dawkins was asmuch a part of the demonstration as his computer, both he and his computer
went into the hat. After some time (how long is of no importance), he came out
with METHINKS IT IS LIKE A WEASEL displayed on his computer. Now, on theface of it, should anything about this amaze us? Clearly not. For a person with acomputer to produce a written sentence is nothing out of the ordinary. Sentences
magically appearing in oracle soup would amaze us (to put it mildly), but this isnothing of the kind.
That was easy.
Now that the hat did its job, a quick peek inside will be informative.
Dawkins designed his program to carry out two simple steps repeatedly. The firststep was to produce lots of copies of the parent sequence, starting with therandom one, with occasional random typos in them. In the second step, eachcopy was compared to the target sentence METHINKS IT IS LIKE A WEASEL, andthe copy with the most correct letters, however few, was selected as the parent
for making a new batch of copies, and so on. After about forty rounds of this, anexact match was found.
Dawkins knew this wasn’t blind evolution, of course. His intended point was
simply that cumulative selection, where improvements are allowed to build alittle bit at a time, can accomplish what would never be accomplished if thewhole finished thing had to appear at once. In his words, “If . . . there was a way
in which the necessary conditions for cumulative selection could have been set
up by the blind forces of nature, strange and wonderful might have been theconsequences.”7 Granted. But then strange and wonderful assumptions often
imply strange and wonderful consequences, don’t they?
Once again, what’s envisioned here is an extensive network of natural
stepping stones that happen to line up in ways that make selection takeextraordinarily insightful paths. We’ve already exposed this ploy. Accidental
stepping stones leading to these fantastically improbable destinations would
themselves be fantastically improbable. If we needed further proof that suchremarkable coincidences never happen by accident, we can thank Dawkins for
supplying it. It isn’t hard to imagine some practical need calling for a line of

Shakespeare—a homework assignment perhaps. But when we bring this to mind,
we instantly see that the following line of gibberish (presented by Dawkins as
the first selected sequence) wouldn’t meet that need:
WDLTMNLT DTJBSWIRZREZLMQCO P.

Equally unintelligible sequences meet other needs, of course—long
passwords or encrypted messages. What we can’t imagine, though, is an honestto-goodness series of these unrelated needs just happening to line up in such a
way that they connect Dawkins’s original random sequence to METHINKS IT IS
LIKE A WEASEL. That definitely won’t happen by accident, which is why
Dawkins had to line up the stepping stones himself. Somehow, though, he thinks
the implausibly complex network of stepping stones that would be needed forlife to evolve did line up by accident. And somehow he thinks his thoroughly
unremarkable demonstration should convince us of that thoroughly unbelievableclaim.
We know better. Natural stepping stones may lead to strange and wonderfuldestinations in our imaginations, but the real world is different. Nothing becomes
useful or wonderful until functional coherence is present in good measure, andwhatever helpful things the natural world may supply in good measure,functional coherence isn’t among them.
Nearly twenty years after Dawkins’s demonstration came another worth
mentioning, this one announced on the cover of Discover magazine with thewords Testing Darwin—Scientists at Michigan State Prove Evolution Works.8
What supposedly evolved was a computational function, so you would need a bitof technical knowledge to understand what came out of the hat. In just a moment
I’ll show how the hat comes through even without this knowledge, but first letme give you this assurance: the computational function that was produced wasso elementary that it wouldn’t have merited attention apart from the claim that it
evolved.9 So since computer science was one of the competencies the scientists
brought to the project, we again have a situation where what came out of the hat
is not the least bit remarkable considering what went in.
Still, one aspect of this demonstration may seem to challenge our conclusion
about functional coherence, at least at first glance. The output function in thiscase required nineteen or so elementary machine instructions to be arranged intoa working whole, and the investigators didn’t explicitly supply this arrangement,
the way Dawkins supplied his. This seems to imply that functional coherencewas produced over the course of this evolutionary simulation.
What are we to make of this? First, keep in mind that our claim is not thatblind processes are incapable of producing any functional coherence at all but
rather that they are incapable of producing it in the amounts needed for useful
inventions. We’ve already seen very small amounts of functional coherence
appear by chance, as when the word ink appeared in half a page of random
typing or when a random grouping of four pixels just happened to have blended
colors. And this can be edged upward a bit by sifting through randomness on alarger scale. Just now, I wrote a program to do this with random typing andfound the longer word bobbled, which involves nine coherent keystrokes,
including the spaces before and after. But the increase in coherence came at aconsiderable cost, as is always the case for blind searches. To find this solitary
seven-letter word, my program had to sift through more than fourteen thousand
pages of nonsense!
Serious invention requires not just a smidgen of functional coherence but
extensive amounts arranged over a hierarchy of levels, and this simply can’t
happen by accident—for any kind of invention. The action of bulldozers moving
junk heaps at the dump, for example, may well cause a ball bearing to find amakeshift socket or a lever to find a crude fulcrum or a cable to wrap itself
around a cylinder, but none of these simple arrangements do anything significant
enough to rise above the junk. Not even on a trillion trillion planets covered withjunk would an accidental robot ever rise up and flee from the bulldozers, muchless scurry around looking for parts to build a copy of itself.
Once this hard fact is grasped, the thought of quibbling over whether nine
coherent keystrokes or nineteen coherent machine instructions ought to beheralded as significant inventions becomes pointless. Both are completely
insignificant compared to what people commonly set out to accomplish withwords or with computer code, to say nothing of all these extraordinary
accomplishments we call life.
There’s more to this story, though, at least for those able to dig deeper. If you
have the ability to dissect demonstrations that “prove evolution works,” you’ll
find that researchers commonly embed their knowledge of what was needed forsuccess into their evolutionary models. In other words, there is cheating goingon here, though the researchers may not think of it as such. In a way, it’s hard not
to cheat with these simple demonstrations. The problem is that the researchers
know too much. In particular, they know how the search should be conducted if
it’s to have any chance of succeeding, and because they want it to succeed, it’s

nearly impossible for them to avoid helping it along.
For example, the scientists who reported the evolution of the computational
function had to offset the cost of useless genetic instructions in their digital“organisms” by rewarding them in proportion to the size of their genomes. As
we saw with the stepping-stone experiment at the end of chapter 7, real life
behaves very differently. Genes that don’t work are a burden, and nature has no
incentive program to offset this burden. The scientists who did the computational
project knew this but used a very unnatural version of selection anyway, just to
get the outcome they wanted. Additional instances of guidance have been
documented for that study and for several other demonstrations claiming to showthat evolution works.10
Most of us can’t dig that deeply, though. In fact, if we don’t even understandwhat came out of the hat, how are we supposed to decide whether it looks likemagic? As I said, the hat comes through even here. Instead of asking whether thedemonstration looks like magic to you, ask yourself whether it seems to look likemagic to the people who understand it. Are they acting as though they’ve
encountered a fountain of invention? Are the experts trembling withastonishment? Are investors scrambling to get a piece of the action? Are
technology companies letting all their smart people go, convinced that humaninsight has now become superfluous? Or is the response perhaps more muted?
Look in particular at the scientists who conducted the demonstration. Are theyhanging on to their day jobs—just as magicians do? If so, this is a sure sign they
didn’t really pull a rabbit out of an empty hat.
FIDDLER FOR HIRE
As a finder of inventions, Darwin’s evolutionary mechanism is a complete bust,
but as we saw in chapter 7, it sometimes comes in handy as a fiddler. The
example I described where a weakly functional enzyme was dramatically
improved demonstrated this. The starting point was ideal: a complete invention,
having all the necessary components in place and working, but not fine-tuned for
optimal performance. Fine-tuning involves the adjustment of many small details,
so trial and error is often the best way to do it. In these situations, selective
optimization—a tuning process that repeatedly selects the best variant after
introducing slight variations—is often useful.

Figure 11.2 The relationship between adjustments and the function they affect. Dotted arrows indicate thatthe function being adjusted is not caused by the adjustments, in contrast with solid arrows in Figure 9.3.
Still, it’s common for adjustments to influence the complex arrangement of parts that is the cause (notdepicted here) very significantly.

A picture may help us see that selective optimization, while useful, is nothing
like invention. The contrast between Figure 11.2 and Figure 9.3 illustrates thedifferences. Most importantly, as the experiments described in chapter 7 showed,
selective optimization only works on a preexisting function. Unlike the lowerlevel functions of Figure 9.3, the adjustments depicted in Figure 11.2 don’t cause
the high-level function; they merely tune it. This high-level function wouldn’t be
there to be tuned, apart from a functionally coherent arrangement of components
to cause it.
For example, NASA has used selective optimization to help design some of
its antennas, including the small one shown in Figure 11.3. This antenna, whichlooks like nothing more than a randomly bent paper clip mounted on a threaded
base, actually has its bends in just the right places to enable it to work well.
Antenna shapes are ideally suited to selective optimization because nearly every
shape works to some degree, and yet small adjustments have measurable effects.
Notice that this kind of optimization is really an application of human insightrather than a replacement of human insight. No computer will ever design anantenna by accident. Instead, human engineers who know all about antenna
design must carefully set the stage for computerized optimization to do exactly
what they intend for it to do. In other words, humans invented this little antenna
by bringing together everything needed for its design, including thecomputational search that refined it.

Figure 11.3 One of the small antennas designed by NASA with the help of computational selective
optimization (see www.nasa.gov/centers/ames/news/releases/2004/antenna/antenna.html).
NASA’s evolutionary antenna, public domain.

This means the antenna’s origin fails the hat test: it looks nothing like magic
because the needed understanding was supplied in the usual way. But thisrealization doesn’t detract from the value of the antenna or the value of selective
optimization. Both are clearly useful. So keep in mind that the hat test isn’t a testof usefulness or scientific validity but a test of relevance to our argument against
accidental invention. By failing the hat test, the antenna merely shows that it’s
not an invention that appeared by accident. It is an invention, of course—just not
an accidental one.
A team of scientists from Cornell and the University of Wyoming recently
presented a more entertaining example, reminiscent of something from a Pixar
film.11 Think of pulsating Jell-O cubes sticking together to form jiggling bodies
that flee from spoon-wielding children, and you get the picture (Figure 11.4).
Like Pixar inventions, these Jell-O creatures exist only in a computer-generated
world, but unlike their film-star counterparts, the Jell-O creatures had to “learn”
how to run by trial and error. Taking hints from biology, their scientist creators
used cubes of three kinds to facilitate running. One kind actively contracts andexpands in a rhythmic way, mirroring the rhythmic contraction and stretching ofleg muscles during running. Cubes of the other two kinds have passive structuralroles, one rigid like bone and the other more flexible, like cartilage.
Because the pulsing cubes all pulse to the same beat—some contracting on
odd beats and others on even—you’d think that even a random mass of cubes
would have a reasonable chance of jiggling itself in one direction, as long as it
contains a good number of pulsers. Perhaps it would, but more effective motion

requires nonrandom organization of cube types into extended regions, as
indicated by the light and dark coloring in Figure 11.4. Taking more cues from
biology, the inventors imposed rules for these nonrandom regions. Selective
optimization was then used to refine runners within the imposed constraints.
Like the NASA antenna, these Jell-O runners show how selective optimization
can be cleverly exploited within the context of a large project that’s conceived
and implemented by humans. But as useful as this is, it has the familiar look of atool in the hands of inventive humans—one more technique among countlessothers that we humans have discovered and refined to suit our inventive ends.

Figure 11.4 The lumbering running style of one example of a “soft robot.”
Soft robot image from Nick Cheney, Robert MacCurdy, Jeff Clune, Hod Lipson, “Unshackling Evolution:
Evolving Soft Robots with Multiple Materials and a Powerful Generative Coding,” Proceedings of the 15th
Annual Conference on Genetic and Evolutionary Computation, © 2013 Association for Computing
Machinery, Inc. Reprinted by permission.

Interestingly, humans weren’t the first to use this tool. Selective optimization
finds elegant application in life, the most notable example being the process ofantibody refinement (known to biologists as affinity maturation), which plays animportant role in the immune systems of vertebrates like us. The antibody shownin Figure 11.5 is a protein complex with two outward-pointing “sticky” ends thatfacilitate the immune response by binding to invaders like bacteria and viruses.
The jumble of small appendages seen on the close sticky end should remind youof jumbles you’ve seen before, as in Figures 3.5 and 10.6. Once again, these areamino-acid appendages. Like all proteins, the entire antibody is bristling withthese appendages, most of which aren’t shown in the ribbon diagram of Figure
11.5.
You and I owe much to these sticky ends because they have saved our lives,
literally, many times. Every time we get an infection, from the common cold to afestering scrape, our bodies go into high gear to fight off microscopic invaders,and antibodies are a key part of winning these fights. Like laser beams guiding
missiles to their targets, antibodies tag the invaders for destruction, and the highspecificity of their sticky ends is what enables them to do this tagging so
effectively. To achieve this specificity, our bodies use an extremely elegant
version of selective optimization, where billions of variations on the best sticky

ends found so far are produced repeatedly, with better sticky ends replacing theprevious ones until no further improvement can be made. Adding to theelegance, our bodies retain the best versions of these sticky ends from each ofthese battles so they can be deployed very quickly the next time the same
invader is encountered.
Again, selective optimization is applied here narrowly and insightfully as atool—as part of a remarkable invention (the adaptive immune system) thatcannot have arisen by accident. In every case, this tool proves valuable only by
being cleverly employed by someone who knows what it can and cannot do.
These masters of selection are the inventors, then. Selection never was. No tool
will ever go off and create a world of its own, the way Darwin thought selection
did.
Everything fits.
Selective optimization proves valuable only by being cleverly employed bysomeone who knows what it can and cannot do.

Figure 11.5 The molecular structure of an antibody. Four folded protein chains assemble to form thecomplete antibody shown here.

OF LANGUAGE AND LIFE
If you’re interested in exploring evolutionary models further, I offer a freecomputational tool developed at Biologic Institute called Stylus. Our objective indeveloping Stylus was to create a model world that captures important featuresof the world of natural proteins. In the first place, we wanted a world where
genes carry sequence instructions for making long chains, just as biologicalgenes carry the instructions for making long protein chains. That part was easy.
More challenging was the goal for these long chains to perform a great variety ofactual functions based upon their structures, just as protein chains do. The
importance of actual function is that it eliminates all the hand waving that comeswith having to pretend sequences are functional. Indeed, the only way for amodel to do justice to functional coherence is by embracing the whole point offunctional coherence, which is high-level function.
After considering several possibilities, we landed on the language analogy
represented in Figure 11.6. Like all written languages, written Chinese isfunctional to the degree that it’s both legible and meaningful, and as always,
legibility comes down to how well the characters are formed. Written language,then, provides the desired connection between structure (the shapes of lines on
paper) and high-level function (the transfer of thoughts from writer to reader).
However, whereas the shape of an alphabetic letter does nothing but trigger
recognition of that letter, the shape of a Chinese character brings meaning tomind (if you read Chinese). This is analogous to the situation with proteins,
where each protein molecule performs a distinct function according to the detailsof its structure.

Figure 11.6 Like proteins, Chinese characters must be properly formed in order to work. Keeping in mind
that the comparison is meant to be general, not specific, we see rough similarity here between the stroke
complexity of a character and the component complexity of a protein. Proteins and Chinese characters bothshow considerable variation in complexity from one to the next.
Chinese character and protein comparison, © 2008 Axe et al., PLOS One, CCY.

You recall from chapter 3 that the biological genetic code describes how cells
use the sequence information in a gene to attach amino acids in the right order tomake a protein. The trick is to read the DNA bases three at a time in codons. We
used that same trick for Stylus. Genes in the Stylus world look just like ouralphabetic representations of biological genes—long sequences of the four
letters A, C, G, and T—but instead of specifying amino-acid chains, Stylus
genes specify vector chains. Taking the place of the twenty amino acids are thetwenty vectors shown in Figure 11.7. These vectors are joined end to end to forma drawn shape as specified by the encoding gene.

Figure 11.7 The twenty vectors from the Stylus world (left) that take the place of the twenty amino acids asbuilding blocks for making long chains, and the genetic code Stylus uses to specify these vectors (right). As
with the biological genetic code depicted in Figure 3.2, hands indicate codons that terminate a vector chain.

No analogy is perfect, but this one is at least rich enough to be interesting.
For example, both proteins and Chinese characters have distinct functional forms
numbering in the thousands. And just as a great many amino-acid sequences canconstruct any one of these protein forms, so too a great many vector sequences
can make the same Chinese character. Finally, as we saw in chapter 10, highlevel functions like photosynthesis are accomplished when many functional
proteins of various kinds are brought together in just the right way. Written
language mirrors this beautifully by using its own hierarchical structure toachieve high-level functions.
The free tool, made possible by the hard work of my colleagues Brendan
Dixon and Winston Ewert, is a Stylus application you can use to perform
experiments at your own pace on your own computer.12 The application enables
you to mutate a parent Stylus gene in a variety of ways and to apply various
conditions for selecting one of the offspring to be the next parent. Stylus

automatically assesses how well the drawing produced from a given gene
represents a given Chinese character by calculating a score ranging from nearly0 (very poor resemblance) to 1 (perfect resemblance), and it provides rich visualfeedback, including pictures of the drawn characters and graphs that show howscores change over the course of an experiment.
As with most tools, Stylus can be used at a range of levels. If you just want abetter grasp of how the genetic code works or how mutations affect the
instructions carried on a gene, Stylus is a good visual hands-on tool for this. Or
you may be much more ambitious. We used Stylus to build a model genome
analogous to a small bacterial genome,13 and between the freely available genesequences from this genome and the freely available Stylus application, there areplenty of interesting research questions that can be tackled at any level.
For a quick example, recall from chapter 7 the two proteins that had weak
penicillin-inactivating ability. One of these proteins was dramatically improvedby repeated rounds of mutation and selection, whereas the other wasn’t. The
difference came down to whether the signal being homed in on was from an
actual enzyme—a protein whose structure is specially suited to penicillin
degradation—or from something much less special that happened to help thenatural breakdown of penicillin along slightly.
Figure 11.8 shows the results of a similar comparative experiment performed
with Stylus.14 Instead of proteins, we started with two vector chains, bothacquired by mutating a gene in the Stylus genome that produces a character
meaning section ( ). As in chapter 7, one of these mutant chains was much
more severely disrupted than the other, which can be seen by comparing the two
drawings in the lower left to the ideal shape. Although the computer gave very
low scores to both mutants, we see that the black one was at least partiallyrecognizable, whereas the gray one looked like a random scribble. In fact, theblack mutant was structurally complete in the sense it had all nine strokespresent; the problem was that some of the strokes had shifted out of their correct
locations (the vertical one having shrunk as well). As the black homing curveshows, those imperfections, though substantial in effect, could all be correctedby a series of single mutations, each of which improved the score. The grayscribble could also be adjusted by selecting changes that improved its score, but
in this case there was so little connection between the score and actual
readability that nothing remotely legible resulted. As with the proteins in chapter
7, selective homing was of value only when functional coherence was alreadypresent in large measure.

Nothing evolves unless it already exists.

Figure 11.8 Selective homing in the Stylus world. The character consists of nine strokes, as shown withbrush strokes. Stylus applies a mathematical test to each vector chain to compute a score, ranging from 0 to
1 (scale on left), which tells how well any vector chain represents the ideal form. Using this mathematicaldefinition of legibility instead of human judgment enables us to take advantage of the much greater“reading” speed of computers. In order for this to represent human perception reasonably well, humanassessment of legibility was used to calibrate the scoring. Stylus performs homing experiments
automatically by producing and scoring all possible genes that differ from the parent gene by one base (A,C, G, or T) and then selecting the one with the highest score as the new parent. This is repeated until nofurther improvement is possible. The dotted line shows the score (0.52) of the original gene (designated
6BB5–02), which is included with the Stylus application, along with all the genes from the publishedgenome.

CHAPTER 12

LAST THROES
Having hopefully persuaded you along our journey that our design intuition has
triumphed over the evolutionary story, I now want to enlist your help. The truth
we’ve arrived at is important enough that we have a responsibility to stand up forit. Think of this as a movement, not a battle. When a good movement prevails,
everyone wins.
Still, movements involve strategy just as battles do, and momentum is a key
part of this. One way for a movement to gain momentum is for those who’ve
joined the cause to see opponents of that cause in retreat. Unlike battles, the hope
here is that hands will reach out to those in retreat to encourage them to change
their allegiance. To that end, this chapter will focus on multiple fronts where thedefenders of materialism and Darwinism seem to be in retreat.
THE RETREAT FROM CRITICAL DIALOGUE
Darwin’s explanation of life turns out to have been wrong, but in that, it joins agreat many other ideas that have had their useful places in the development ofscientific understanding. Originally, at least, Darwin’s idea was articulated withenough clarity to ensure that it would ultimately prove true or false. Moreover,Darwin clearly identified the crucial point on which this verdict hung. In his
words, “If it could be demonstrated that any complex organ existed, which could
not possibly have been formed by numerous, successive, slight modifications,my theory would absolutely break down.”1 That is, if any of the inventions we
see in the living world can’t be acquired one tiny beneficial mutation at a time,
Darwin’s hopes for natural selection were in vain. His next words—“But I canfind out no such case”—revealed where his sympathies lay, which only confirms
he was human.
Somewhere within the long succession of his followers—all bright people
coaxed into abandoning their design intuition—Darwin’s recognition that his

idea of gradual invention was vulnerable to refutation was lost. The historicaldetails of the disappearance are too complicated to be pieced together fully, but
this is unnecessary anyway. In general terms, the human factors that put an end
to vulnerability are very familiar. The idea of natural selection as genius in slow
motion became to biologists part of the very definition of life, and with thiselevated status came immunity from criticism. To question the most central
axiom of modern biology was, and is, to excuse oneself from the company ofmodern biologists.
The familiar truth is that on matters we care about, we admit the possibilityof being wrong only with some reluctance—more as a way of showing ourselves
to be reasonable than as a way of encouraging criticism. If and when thatconcession seems unnecessary, we’re inclined to withdraw it. Then, with thepassage of time, we become so comfortable with the absence of open criticism
that we’re indignant when someone unaware of the ground rules violates them.
The natural progression, in other words, is from reluctant acceptance of criticism
in principle to resentment of criticism in practice.
As human as this progression is, it’s distinctly hypocritical when it takes holdin a community that bases itself on reason and open discourse. Faithcommunities, being explicit in their commitment to doctrine, are being true totheir core values when they correct or remove people who oppose what they
once agreed to uphold. But for the scientific community to do likewise, based as
it is on discovery instead of doctrine, is to violate its core values. The
consequences are always ugly. Lacking any special revelation, science boasts
intellectual openness as its core virtue. And what a potent virtue this has proved
to be! But when openness gives way to dogma on any particular scientific claim,
we’re left with something more like bad religion than good science.
To spot one of these ugly examples, look for two telltale signs. The first is
official denouncement of any idea that poses a threat to the dogma, and thesecond is a culture of disdain for that threatening idea. On the first point, take alook at the Wikipedia page titled “List of Scientific Bodies Explicitly RejectingIntelligent Design,” where you’ll find names of over a dozen academic andscholarly organizations in the United States that have issued statements opposing
ID, along with several others outside the United States or of international
composition. Among those listed are two of the world’s most highly esteemedscientific organizations: the Royal Society of London and the National Academyof Sciences of the United States—impressive opposition, to say the least.
These being scientific organizations, they don’t want to appear to have

rejected ID on doctrinal grounds, so their denouncements assert that ID can’t begiven a place at the table of scientific discourse because it’s fundamentally
religious. Ironically, though, their anti-ID activism has a quasi-religious
character of its own. If they actually believed the question of whether life isintelligently designed to be outside the purview of science, they would take noposition on the answer. But they do take a position. The Royal Society of
London has officially declared that “the theory of evolution is supported by theweight of scientific evidence; the theory of intelligent design is not.” Likewise,
the world’s largest scientific society, the American Chemical Society, has urged
educational authorities to “affirm evolution as the only scientifically accepted
explanation for the origin and diversity of species.” And the Royal Astronomical
Society of Canada “is unequivocal in its support of contemporary evolutionary
theory that has its roots in the seminal work of Charles Darwin and has beenrefined by findings accumulated over 140 years.”2 Nowhere under that proud
Darwinian flag that flies over the modern academy will you find an institutional
declaration to this effect: “Although life may well be the work of an intelligent
designer, this is not a matter that science can address.” That can only mean one
thing: the anti-ID activism comes down to a doctrinal stance after all.
That the hoisting of the materialistic Darwinian flag also ushered in a cultureof disdain for threatening ideas like ID becomes evident when you look a little
deeper than the position statements. Intelligent design is mentioned quite
frequently in Darwinian science journals, but always negatively and often withsome expression of condescension or contempt. Within these otherwise scholarly
pages you’ll find intelligent design described—apparently with editorial
approval—as a “myth,”3 as an “attack on biology,”4 as an “intellectual virus,”5
as an “insidious movement,”6 as “the pseudo-scientific face of religious
creationism,”7 as something that “threatens all of science and society,”8 as “aretreat to the dark ages,”9 and finally (space not permitting a full catalog of antiID epithets) as “terrifying”10—“like Frankenstein’s monster.”11
Hmm.
Despite the complete rationality of the case for the intelligent design of life,
there’s just no way to make that conclusion acceptable to people who want tobelieve science has disproved God. The truth is quite the opposite, which isdistinctly uncomfortable for some. Perhaps this explains why some people react
so viscerally—not that ID is illegitimate, but just the opposite: it’s painfully
legitimate.

THE RETREAT FROM DARWINISM
As telling as the retreat from critical dialogue is, there are several other equallysure indicators that the search for a natural explanation of living things has comeup empty. Perhaps the most striking of these is the repeated acknowledgmentfrom scientists closest to the subject that Darwin didn’t actually achieve such an
explanation. This is the gaping hole we encountered in chapter 7. In his 1904
book Species and Varieties: Their Origin by Mutation, the great Dutch botanist
Hugo De Vries stated the deficiency as follows:
In indicating the particular means by which the change of species has
been brought about, [Darwin] has not succeeded in securing universal
acceptation. Quite on the contrary, objections have been raised from thevery outset, and with such force as to compel Darwin himself to change
his views in his later writings. This however, was of no avail, andobjections and criticisms have since steadily accumulated.12
So the sudden favorable turn of scientific opinion Darwin described in thesixth edition of his book, where biologists went from believing in the separate
creation of each species to accepting his “great principle of evolution,” wasn’t
accompanied by general acceptance of natural selection as the cause.13
Accordingly, De Vries ended his book with a memorable quote describing what
we are calling the gaping hole: “Natural selection may explain the survival of thefittest, but it cannot explain the arrival of the fittest.”14
Despite huge boosts in subsequent decades from the development of amathematical theory of natural selection and the discovery of DNA as thegenetic material, Santa Fe Institute scientist Walter Fontana and Yale biologist
Leo Buss acknowledged in 1994 that the hole in evolutionary theory was still
unfilled. Repeating De Vries’s memorable quote ninety years later, Fontana andBuss titled their paper “‘The Arrival of the Fittest’: Toward a Theory of
Biological Organization.” It begins with a big concession:
The formal structure of evolutionary theory is based upon the dynamics
of alleles [i.e., gene variants], individuals and populations. As such, thetheory must assume the prior existence of these entities.15
Don’t miss the significance of this. Because all living things are among

“these entities,” Fontana and Buss are admitting here that modern evolutionary
theory doesn’t actually explain the origin of new species or even the origin of
new genes. Instead, “present theory tacitly assumes the prior existence of theentities whose features it is meant to explain.”16
If you’re wondering why some scientists get away with such startling
frankness while others are censured or excommunicated, it all comes down towhether the critic is seen as a friend of the greater cause. Scientists can say what
they want about the state of evolutionary theory if their allegiance to scientistic
materialism is intact, and the best way for them to demonstrate that is to claim tohave filled the hole, or at least made decisive progress in that direction. As withroad repair, you’re allowed to use the jackhammer with impunity as long as you
patch everything up before you leave. Using that strategy, Fontana and Buss
offered their deep criticism as a way of introducing a theory that, by theiraccount, explains how “self-maintaining organizations arise as a genericconsequence of two features of chemistry, without appeal to natural selection.”In other words, Darwin was wrong, but life is still the expected outcome of blind
chemistry, so all is well under the materialist flag.
Like those two scientists, a great many others have tried to patch the hole in
Darwin’s theory over the years, but none of these patches have proved very
durable. Interestingly, progress in biology seems to make the situation worse.
The genomic era, a period of unprecedented progress, was just getting under way
when the paper by Fontana and Buss appeared. Twenty years later came a bookby Swiss evolutionary biologist Andreas Wagner. So if the patch offered by
Fontana and Buss were sound, Wagner would have been in a good position toaffirm this. Instead, he reaffirmed the existence of the gaping hole, as evident in
his title: Arrival of the Fittest—Solving Evolution’s Greatest Puzzle. Echoing his
predecessors, Wagner concedes that “natural selection can preserve innovations,but it cannot create them.” After this, he says:
To appreciate the magnitude of this problem, consider that every one ofthe differences between humans and the first life forms on earth was once
an innovation: an adaptive solution to some unique challenge faced by aliving being.17
What Wagner calls innovations I’ve called inventions, but the point is thesame and it applies as much to spiders and whales and orchids as it does tohumans. Of the countless remarkable inventions on display in the countlessremarkable forms of life, natural selection explains none of them.
Wagner gets away with this devastating critique of Darwinism the same way
Fontana and Buss did—by offering his idea of a solution. Certainly, if Wagner’s
solution really filled the hole, it should be heralded as a remarkable achievement,in that it brought 155 years of failure to an end. Being familiar with the subjects
he deals with, I could tell you why I think he didn’t succeed, but in effect I
would be asking you to trust me over him, which none of us should findsatisfactory. Instead, my whole purpose has been to equip you to trust your own
design intuition.
Wagner ends his book with this summation of his thesis:
With a limited number of building blocks connected in a limited numberof ways, you can create an entire world. Out of such building blocks andstandard links between them, nature has created a world of proteins,regulation circuits, and metabolisms that sustains life, that has brought
forth simple viruses and complex humans, and ultimately, our culture andtechnology, from the Iliad to the iPad.18
His first sentence—where the actor is you—is surely true. Wagner wrote hisbook the same way I’m writing mine—by connecting the twenty-six alphabetic
building blocks. Software developers connect commands and then compile theseto get long lists of connected zeros and ones. The periodic table of elements
organizes the fundamental material building blocks in a way that explains thestandard chemical links between them. Those elements and their connections
make possible absolutely every physical thing we humans make, including theiPad. But as necessary as all these building blocks are for our inventive
activities, they are not the inventors. We are.19
Consequently, Wagner’s second sentence—where the actor is nature—sounds like a fairy tale to everyone whose design intuition is still intact. Andagain, unless we’ve gone very wrong in our thinking, it should sound like a fairy
tale. Alphabet soup is chock-full of building blocks, but nature is so clearly
incapable of doing what we do with building blocks that we knew immediately
the account of oracle soup couldn’t be true. As we realized back in chapter 2, anirrefutable demonstration of that mysterious soup would only convince us that aninvisible someone is arranging the letters.
The mere tale of oracle soup, however, sends no shivers down our spines forthe simple reason that we have no reason to regard it as true. Likewise for allthese tales of nature inventing. After more than a century and a half of thesestories, surely we’re entitled to ask for something more. Talk has its proper placein science, but to those hoping to convince everyone that accidental invention ispossible, I say—If you merely tell us that plants happen when light shines on
random atoms or that nature created a world of proteins, the response willprobably continue to be disappointing. Show us such magical things, and you
will have our rapt attention. Give us a demonstration that passes the hat test withflying colors. We will still be puzzled by your insistence that magic should be
regarded as ordinary, but you will have our attention.
THE RETREAT FROM TESTABILITY
Because the arguments and evidence run counter to Darwin’s idea, perhaps weshouldn’t be surprised to see defenders of that idea shrinking back fromscientific discourse. Figure 12.1 illustrates their predicament. To attribute theinvention of all complex life to a natural mechanism set in motion with theearliest simple life is to ascribe astonishing creative power to that mechanism.
Yet when my colleagues and I challenge this evolutionary mechanism to invent
on a far less impressive scale—by altering an existing enzyme to perform a new
function—we find that it fails. It’s hard to exaggerate the magnitude of thiscontradiction. Imagine a group of people insisting that a certain man can jump to
the moon. We, being skeptical, challenge this man to dunk a basketball, and wefind that he comes well short of reaching the rim. When we publish our finding,we get lots of complaints, all of the kind “We never said he could dunk abasketball . . . or at least not that basketball, on that rim!”Figure 12.1 The striking contrast between a very minor invention that isn’t feasible by Darwinian evolution(top) and the profound inventions that Darwin assumed were feasible (bottom). Shown at the upper left isenzyme B from chapter 6. In a bacterial population that already makes the very similar enzyme A (upper
right), evolutionary conversion of A to B appears not to be feasible based on our studies. The lower half ofthe figure illustrates invention at the much higher level of complex life forms. Here, evolution would have
had to invent all life from some early bacterial species supposed to be the ancestor.

In other words, recognizing the difficulty of getting their man to reach therim, to say nothing of the moon, most defenders of Darwin are trying very hardto embrace the contradiction. The thinking is that evolutionary ineptness insolving problems that no one claims were solved in the history of life doesn’t
preclude competence in solving the supposed historical problems. But the matterof competence must take priority over historical assumptions. That is, the claimthat evolution did invent proteins, cell types, organs, and life forms isscientifically legitimate only if we know evolution can invent these things.
Consequently our demonstration of evolutionary incompetence for an exampleof the least of these inventions—a new function for an existing enzyme—
undercuts the whole project of inferring evolutionary histories. If nothing canevolve its way into existence, then nothing did.
The claim that evolution did invent proteins, cell types, organs, and life
forms is scientifically legitimate only if we know evolution can invent thesethings.
When that previous statement is no longer presumed true, we know we’vereached the final stop in a staged retreat from testability. As I mentioned near theend of chapter 6, this is where the debate now stands. The current stance is thatevolution was so successful that it perfected life to the point where modern
forms no longer evolve, making the whole process even further removed fromthe category of observable phenomena. By this view, direct observation ofevolutionary invention would require access to a world that no longer exists, andbecause evolvability is presumed to have been a characteristic of that world, any
attempt to reconstruct a piece of it in the lab would be judged by whether
evolvability was confirmed. In this way refutation seems to be forestalled, but
not without considerable cost. To put it bluntly, evolutionary theory has become
immune to refutation in much the same way that the stump of a tree has become
immune to further pruning.
Strangely, after all the “anti-science” insults that have been directed at
proponents of intelligent design, we seem to be among the few who areinterested in using science to settle the matter.
THE RETREAT FROM THIS UNIVERSE
In 2007, Eugene Koonin, a prominent evolutionary biologist at the National
Center for Biotechnology Information in Maryland, gave scientists in his field adouble shock. The first shock was his frank concession that the origin of the firstcell carrying genetic instructions for making proteins is “a puzzle that defeats
conventional evolutionary thinking.”20 Having deployed this jackhammer, he
was obligated to fill the resulting hole, which he attempted to do in a most
unconventional way. Koonin delivered his second shock by appealing tocosmology—the study of the origin and behavior of the universe as a whole—topatch everything up. Specifically, to dispense with the problem of fantastic
improbability, he leveraged the idea of an infinite multiverse, which we maythink of as an infinite set of actual universes, ours being one.
Understandably, most people consider this supposed multiverse to be so far
removed from real experience that they have a hard time taking it seriously. But
while that skeptical stance should inform the discussion of where the boundaries
of science lie, truth is a bigger and more profound subject than science. For mypart, although I reject the existence of other universes, I’m not content to do so
simply on the grounds that we can’t verify their existence, because it seems
equally true that we can’t verify their nonexistence. The better question iswhether the hypothetical possibility of an infinite multiverse should change theway we explain life in this universe.
Koonin’s reason for thinking it should is based on a concept called theanthropic principle. Autobiographies of the “I lived to tell the tale” kind show
how this principle works. In these books, the author recounts circumstanceswhere death seems virtually certain, and yet the very fact that he or she lived totell the tale assures us that the odds of surviving, however slim, were somehow
overcome. In the most extreme cases, many of us would say that God intervened
and therefore chance had nothing to do with the turn of events, but the point isthat no matter how impossible the situation seems as we read the account, weknow that some remarkable occurrence must have averted death—otherwise thebook wouldn’t have been written.
The anthropic principle applies a similar idea to our existence. If we suppose,even hypothetically, that our universe is just one of infinitely many parallel
universes, and that conditions vary from one universe to the next, such that all
the innumerable physical possibilities become actual somewhere out there in themultiverse, then might we humans be like authors who lived to tell the tale? To
follow the reasoning here, start by supposing that the probability of a universe
producing intelligent beings like us by accident is greater than zero (we’ll returnto this later). Using gazillion as a placeholder for some very large number, we’ll
say this probability amounts to one in a gazillion. It follows, then, that for every
gazillion universes, one is expected to have intelligent beings who came about
by accident. And because an infinite collection of universes has an infinite
number of gazillions within it, it follows that there should be an infinite numberof these very special one-in-a-gazillion universes that are home to thinkers like
us—not by the hand of God but by the raw power of infinitude.
But what seems at first glance to be at least a provisional theoreticalpossibility doesn’t square with reality. To see this, ask yourself what we should
see in our universe if things really were as we have supposed. The answer is that

we, as beings who wonder about our origin, should see the most bare-bones
circumstances for wondering to be possible. The rationale for this answer isn’t
complicated, but the whole scenario is so strange it may take some effort to getyour head around it. As with the search spaces we discussed in chapter 8, thishypothetical multiverse would consist almost entirely of uninterestingalternatives. These would be normal universes where the fantastic improbabilityof accidental invention equates to physical impossibility, so no invention occurs.
But if we assume, first, that it’s not categorically impossible for physicalprocesses to produce beings capable of wonder and, second, that the infinite
multiverse is real, then our present act of wondering could be explained by ouruniverse being one of those fantastically rare universes where the staggering
improbability of wonderers being invented by accident just happened to be
overcome.21 Like the autobiography, our existence would be the proof.
Now, here’s where evolution comes in. If it were true that evolution works asa brilliant inventor and that intelligent beings like us are among the things it caninvent, then I would agree with Koonin. The most bare-bones explanation for us
would be that simple cellular life was formed against all odds, and evolution
took over from there. So Koonin’s appeal to a multiverse as a way of explaining
how the fantastic improbability of that first cell was overcome is perfectly
consistent with his set of assumptions.
However, once we realize how incompetent evolution is as an inventor, thiswhole multiverse explanation collapses. We do indeed find ourselves in a world
where the individuals of one species—ours—wonder how everything came tobe, but a big part of our wonder has to do with the obvious fact this is anything
but a bare-bones world. Quite the opposite. So since every one of the biologicalinventions that surround us is fantastically improbable, with evolution explaining
none and the multiverse hypothesis explaining only those absolutely necessary
for wondering to be possible, we conclude that this hypothesis fails to explain
what we see. Conceivably, we could have found ourselves wondering on an
austere planet populated by little more than lonely thinkers whose bodies arecapable only of those functions absolutely necessary for thought. And becausethat kind of planet is vastly less improbable than this sumptuously appointed
five-star accommodation we call Earth, we certainly would have found ourselves
there rather than here if we really were accidents of nature.
That we are here instead assures us we are not.

THE ELEPHANT IN THE ROOM
Because reality can’t ultimately be grounded in physical things, materialism
always fails when we ask big questions of it. This categorical inadequacy of thephysical realm makes the number of physical universes irrelevant. Physicalprocesses simply can’t be the basis of everything, no matter how much room wegive these processes to work.
A similar principle holds for our understanding of reality. Contrary to theclaim of scientism, we can’t ultimately base our knowledge of truth in science.
To see this, let’s momentarily adopt the mind-set of an absolute skeptic—
someone who doubts everything that can be doubted. No one really is anabsolute skeptic, and most of us never go to the trouble of even contemplating
absolute skepticism. It will be worth doing for a moment, though, just to see how
hopeless it would be to make skepticism our top priority.
Think with me for a minute in the first person. How do I know I existed one
minute ago? Is it enough for me to say I remember the past and see evidence of
my past? Usually this is enough, of course. At the end of a workday, I always
find a familiar car in the spot where I recall parking my car, and this seems toconfirm my recollection. While operating in absolute-skeptic mode, however, I
have to admit that these ties to my past are nothing more than present
impressions, and I can’t convince myself that my present impressions are
infallible. I believe them, but I also find myself revising these beliefs quite
regularly, as when waking from a dream, for example. So how do I know thiswhole life experience isn’t a dream that just popped into existence a momentago? Again, I find that I’m content to believe otherwise, which is a very goodthing considering I can do no better. Neither can you. We must take someessential things on faith because there really is no alternative.
My point is not that anyone is or ought to be an absolute skeptic. Rather, mypoint is that faith alone is what rescues us from the futility of absolute
skepticism. If you think science can come to the rescue instead, ask yourself
what confidence you can place in science without presupposing that you did
exist a minute ago. If your entire past is an illusion, how can this thing you call“science” not also be an illusion? The truth is that science can’t even conceivably
give us anything more certain than the faith we place in the essential
propositions undergirding science, which means science will never be theprimary path to knowing, much less the only path to knowing. Faith has always
been more fundamental to human knowledge than science, and this will neverchange.
What makes science so compelling is that we all do accept the essential
propositions. And when we add nothing to those essentials, common science andcommon sense naturally lead us to attribute life to God, as even the children of
atheists do. I can vaguely imagine a version of reality where God exists but
science and reason are silent about his existence. The conceivability of thatimaginary world makes it all the more striking that this world is so different.
Here the silence is broken.
Science can’t even conceivably give us anything more certain than the faith
we place in the essential propositions undergirding science, which means
science will never be the primary path to knowing, much less the only pathto knowing. Faith has always been more fundamental to human knowledge
than science, and this will never change.

WHERE IT ALL LANDS
There’s no way around the fact that everything resembling earthly life requires
high-level functional coherence. Nor is there any way around the fact that thismakes the sum total of all possible things that would be recognizable as earthly
life impossibly rare. In the language of chapter 8, these possible life forms arehopelessly lost in the nearly infinite space representing the ways matter could be
mindlessly arranged. What the inventor can do—seeing possibilities that areotherwise not there and seizing opportunities that only exist because they are
imagined—cannot be done by accident.
Yes, Darwin’s idea falls when we grasp this, but so does every attempt topretend that life just happened, no matter how sophisticated it may sound. If wetry to avoid God by supposing all the necessary elements for each evolutionary
step just happened to be at the right place at the right time, against all odds, then
we only push his creative work back from the creatures themselves to thecircumstances that brought them about. If we try to avoid God by supposing life
came to Earth from outer space, we only push his actions to another planet or
another galaxy. If we try to avoid him by supposing life unfolded from the initialconditions of the universe or from the laws of physics, we make these things so
ingeniously life-directed that we have only pushed his action back in time. And

if we try to avoid him by imagining our universe is only one among an infinite
number of universes, he shows himself to be present here nonetheless. That hehas acted is plain to see, and no theory can erase what we see.
All of this follows from the fantastic improbability of life having happenedby accidents of any kind. All of it declares God’s presence and involvement in
our world—breaking the silence, shouting to anyone who has ears to hear.
And as if that were not witness enough, there is more.

CHAPTER 13

FIRST WORLDI haven’t shied away from naming God as the knower who made us. I see noother way to make sense of everything we’ve encountered on our journey. By
recognizing that life can’t be an accident, we’re affirming that life was intended,
and considering the stunning genius with which this intent was carried out, I’m
compelled to see God as the genius behind it.
Still, thinking in particular of Thomas Nagel, I want to put my finger on what
it is that makes the alternative hypothesis of a purposeful but impersonal naturalorder untenable to me. As we approach the end of our journey, the time has cometo address this.
Nagel is drawn to the subject of mind, and so am I. Perhaps the most aweinspiring aspect of the outside world is that we each view it from our own insideworld. Not only that, but we are active participants in the outside world. Like
operators of diesel-powered earthmovers, we each have a seat on the inside fromwhich we see the world outside while also acting to change it. How is thispossible? Clearly it is, or we wouldn’t be here to talk about it. Still, once we getpast its familiarity, this marvelous truth ought to stir wonder and amazement inus.
The children whose simple view of life has proved superior to the view
endorsed by the Royal Society and the National Academy also have a simple
view of consciousness. Their view begins to take shape in infancy with games
like peekaboo, where small hands over small eyes form a screen thatmomentarily isolates the inside world from the outside world. With the screen inplace, the view from inside is one of darkness and mounting anticipation. Thenthe hands are flung from the eyes and the anticipation is rewarded, always withshrieks of approval. Through countless learning moments like this, children
build a connection between their inside world and the outside world, a
connection far more profound than anything technology has given us.
Further exploration deepens the connection. The child begins to recognizethat certain special participants in the outside world (Mommy, Daddy, sister,brother) are also viewing it from an inside world—their own inside world. This
understanding is imperfect at first. The child initially thinks that by covering hiseyes he closes off the outside world for everyone. Later he learns that Mommy’s
eyes are the window to her inside world just as his eyes are the window to his,and so the child’s internal model of reality is refined.
With increased internal understanding comes increased external expectations,along with consequences for successes and failures in meeting those
expectations. Learning from both, the child eventually attains full selfawareness, making decisions with the understanding that they have an effect on
the outside world, that those effects will be observed by other people, and thatthe observers may respond with decisions of their own. Of course, in coming tothis view of reality no one feels as though they’re doing science or philosophy.
Indeed, this commonsense view seems so natural that few of us give it a second
thought.
THINKERS, THOUGHTS, AND THINGS
When we ponder this view for a moment, it seems to place the components ofreality into three categories. I’ll call them thinkers, thoughts, and things. The
outside world consists entirely of things (galaxies, atoms, trees, computers, etc.),
whereas each inside world consists of the mental space in which one thinker has
thoughts. I referred to this personal space as a workshop at the close of chapter
10 because each person works upon his or her own thought projects within it.
This view stirs controversy when we take it back to the question that started
our journey: What is the source from which everything else came? Immediately
another interesting question arises. If reality presently consists of thinkers,
thoughts, and things, which of these three should we see as being primary in thesense of having been the source of the other two? As I mentioned at the outset,materialists hold things to be primary, whereas theists hold thinkers to be
primary—most notably the divine thinker we call God. Hence the tension.
The struggle for materialists has always been to explain how things could
really be primary. For things even to be the source of all things seems
impossible. The spider’s spinning apparatus is certainly a thing, but because it’s
one of those special things we call inventions, we’ve concluded that it can’t haveoriginated by accident. Only a thinker could have brought spinnerets into
existence, and a highly clever thinker at that.

Up to this point, our discussion has focused almost entirely on that one key
failure of materialism: its inability to explain inventions. Nagel and a good manyothers have pointed to another failure, which happens to be the one my own
reflections first turned to during my undergraduate days. More profound than the
failure to explain invention, this other failure is that materialism is categoricallyincapable of explaining either thinkers or their thoughts. As a student of thephysical sciences, I realized that however powerful physical and chemical
descriptions of matter are within their own domains, they can’t possibly describe
the most important aspects of us. One of my handwritten notes on that student
bulletin board mentioned back in chapter 4 summarized my reasoning asfollows:
Physical systems are governed by physical laws. With our minds we areable to control our physical bodies. Our minds can take precedence overphysical laws and are therefore nonphysical. That which is constrainedby physical laws cannot give rise to something that takes precedence
over those laws. Therefore, man did not evolve from the physical.
In other words, the problem as I saw it was not merely that the mind iscurrently beyond physical description but rather that the mind is categoricallyabove physics. The properties of matter make all mere things behave the way
they do, but somehow we stand above that. We are not mere things. Within thelimits of our capabilities, we do whatever we want to do without answering toany equation.
But while we are masters over the physical in that sense, we are slaves inanother. Our bodies are physical things, subject to physical needs and vulnerable
to physical conditions. Without food, water, and rest, they cease functioning
properly, and our minds are quick to follow. In fact, our minds are particularly
sensitive to certain material influences. The most active thinker among us can’t
stand up to a dose of propofol, a common drug for inducing general anesthesia.
So the same minds that spend their waking hours manipulating matter are
rendered completely inactive by a small amount of matter of a certain kind. The
point is not that we stand wholly above the material world, as God is said to, butrather that we occupy a position that so categorically defies material explanation
as to refute the materialist position, over and above the refutation that most of
this book was devoted to.
A simple thought experiment should convince everyone of this. Imagine

yourself seated inside a brain-imaging laboratory surrounded by complicatedequipment, some of which is connected to you by means of wired probes stuck
to your scalp and forehead. You are fully conscious, not alarmed in the least by
your surroundings, in no need of sedation (we can do this in a thought
experiment). In fact, you are calmly conversing with the brain scientist standing
before you in his white lab coat. You were thoroughly intimidated by him when
you were escorted into the lab, but the conversation soon took such an amusing
turn that all intimidation vanished.
“I’m still trying to pinpoint exactly what you mean when you say two,”he says with more than a hint of frustration.
“I keep telling you what I mean. Two is the next whole number after
one—one more than one.”“Which is one more than none.”“Exactly.”“Yes, well, that all sounds very nice, but I can assure you that every
one of your thoughts is nothing but a physical manifestation of this massof neurons that sits inside your skull, and I can likewise assure you that I
am recording and imaging absolutely everything going on in there—very
expensive equipment this is, the very latest—and yet whenever I show
you something on this display that looks very promising to meeee . . .
youuuu keep insisting it is not at all what you mean by twoooo. I might
have overlooked this if we had fared any better with the other words wetried: circle, triangle, line, around, between, love, hate, true, false, one,and none. But as things stand, I am beginning to think this whole
exercise has been a colossal waste of time—my time, that is. And no, I
most certainly do not want to know what you mean by time!”
Do you see the problem? The meaning we attach to these words is nowhere
to be found in a person’s brain, or in any other physical location, for that matter.
Of course, some of these words may describe various aspects of the brain, but todescribe a thing is not at all the same as to be indistinguishable from it—identical to it. Yes, two happens to be the number of cerebral hemispheres, but
it is also the number of Martian moons, the number of sides to a coin, thenumber of Nobel Prizes awarded to Fred Sanger, and the number of sequels to A
Fistful of Dollars. In the larger scheme, all of these are small, contingent
realities, whereas two itself towers above them as a permanent, universal,

necessary reality.
Or at least I can make no sense of anything apart from this view. To say thata statement is true is to say something significant precisely because true isanother of these necessary realities. If true were anything less—a physicalprocess in a brain lobe, or a substance that could be packed into 50-milligramtablets, or an object that could be photographed—then the lofty meaning we
attach to truth would be a mirage, and this activity we’re doing right now calledreasoning would instantly collapse into a heap of pretentious nonsense. We
vigorously insist that certain claims are true and others false because we believethat the distinction goes much deeper than whim. But if truth were nothing morethan, say, a particular pattern of neuronal firing in one’s frontal lobe, theninsisting we prefer truth over falsehood would be like insisting we install the
toilet paper roll this way and not that way. Much ado about nothing.
Indeed, our very sanity is at stake here. If the meanings we ascribe to nearly
every word we use are as completely mistaken as the scientist in our thought
experiment suggested, then every sentence uttered or written throughout thehistory of human thought has been fundamentally confused, and in thinking
otherwise we show our thoughts to be every bit as confused as our words. In fact
we couldn’t even have thoughts. The conceptual realm is, after all, where wethink we do our thinking, so if this realm doesn’t really exist in its rightful
position above the physical realm, then we’re badly deluded.
But once we reject the materialistic premise, we see irony instead of insanity.
The reality of truth makes reason possible, which in combination with physicalobservation makes science possible. No one should deny the importance of
science, but neither should anyone deny the importance of the more fundamental
realities that lend meaning to science. By doing just that, materialism andscientism invalidate the very discipline they seek to elevate.
In the end, it seems the children are right again. The inside world is every bit
as real as the outside one. Consciousness and free will are not illusions but
foundational aspects of reality, categorically distinct from the stuff of the outside
world. Following the children, if we allow ourselves to see the outside world as
an expression of God’s creative thought, everything begins to make sense. Far
from peculiarities to be explained away, consciousness and free will are at thevery center of all reality, just as they are at the center of us. We love to think andcreate and express ourselves because we were created to do so by a God who hassurrounded us with exquisite proof that he loves these same activities.

THE PRIMACY OF PERSONHOOD
Can there be any other coherent view of reality, then? On this point I findThomas Nagel’s transparency extremely refreshing. As I mentioned in chapter 1,
he wants there to be an alternative—a fully coherent view of reality where God
is absent. I have never felt that desire, but I can relate to the underlying “cosmic
authority problem” Nagel describes, at least to a degree. Hasn’t each of us
wanted to be his or her own authority, accountable to no one but ourselves? I’ve
never wished God out of existence during those moments, but I certainly havefelt his presence to be something of an inconvenience, to put it mildly. All of thisI regard as part of the human condition, and being human, I’m wholly
sympathetic.
Nevertheless, while I admire the way Nagel thinks and agree with much of
his reasoning, I find his atheistic position fundamentally untenable. Nagelaffirms that “our clearest moral and logical reasonings are objectively valid,”1
and he rejects the materialist view on the grounds that it lacks even the
categories for treating these reasonings as real. Having dispensed with thedominant academic view in that way, he seeks “alternatives that make mind,
meaning, and value as fundamental as matter and space-time in an account ofwhat there is.”2 I would say even more fundamental, but I otherwise agree withall of this, as with Nagel’s more complete description of what we should be
looking for:The hope is not to discover a foundation that makes our knowledge
unassailably secure but to find a way of understanding ourselves that is
not radically self-undermining, and that does not require us to deny theobvious. The aim would be to offer a plausible picture of how we fit into
the world.3
Well put. And yet it seems to me that Nagel’s careful probing of the
deficiencies of materialism shows the missing category to be not just moral or
logical reasoning but something considerably bigger.
As I mentioned at the start of chapter 10, Nagel is seeking a version of thenatural world that produces the things of personhood—consciousness, reason,and moral sense—as part of the expected course of events. In other words, hewants a version of nature that, once accepted, demystifies the appearance of allthese remarkable inventions we’ve been considering along our journey,

including the higher faculties of humans. Everyone sees the difficulty of
constructing what Nagel is calling for, including Nagel himself, but we don’t
want to dismiss the project just because it looks hard.
I find myself having to reject it for two other reasons. First, when I try to
imagine a way of understanding the world that meets Nagel’s conditions, I’m left
to think that the mystery he wants to eliminate can only be displaced. Humans
might be the expected outcome if this hypothesized picture of nature werecorrect, but that only makes the picture itself mysterious. Of all the attributes thisimpersonal thing we’re calling nature might have had, why would it have had theastonishing attributes needed to produce such astonishing things?
My second reason is that I honestly think Nagel is rejecting the obvious.
What is conspicuously neglected in materialism and in Nagel’s hoped-for
alternative to materialism is personhood—not as something derived but assomething fundamental. Indeed, if the aim is to understand how we fit into theworld, then the subject of we deserves as much attention as the subject of world.
Materialism has committed the glaring error of adding we in only at the very
end, as an afterthought, and Nagel should be thanked for pointing this out withadmirable clarity. But even he entertains a rather truncated and fragmented
notion of we, I think.
We know from what we’ve discussed that the cause we owe our existence tocannot be accidental. Nagel agrees, but to avoid a personal understanding of
purpose, he seeks a natural one instead, where “things happen because they areon a path that leads toward certain outcomes—notably, the existence of living,
and ultimately conscious, organisms.”4 So this cause brought us into existence
as if we were intended, and to do so this cause must have been in possession ofwhat amounts to astonishing insight. All this is clear. Add to it the fact that thiscause must have encompassed the very categories that Nagel addresses—
conscious mind and rational faculties and moral sense—and if I were in Nagel’s
shoes, I would find the resulting profile to be unnervingly personal.
Indeed, how could something that lacks personhood know the path topersonhood? How can anything intend to produce persons without firstunderstanding what this means?
If the obvious solution to all this is to acknowledge the reality of a personalGod, why go to such strained lengths to withhold this acknowledgment? Having
now dipped our toes in these intriguing waters of reconciling our inner and outerworlds, why not just dive in? In 128 pages Nagel unraveled 150 years of Westernthought just by taking seriously a few obvious aspects of humanity. Why not gofurther? Yes, we are conscious thinkers with a moral sense, but that’s hardly anadequate description. We are also friends and lovers and givers and takers anddreamers and visionaries and storytellers and philosophers and advocates andpleaders and sympathizers and sacrificers and accusers and forgivers andwarriors and peacemakers and singers and sculptors and painters and musicians
and poets and worshippers and dancers and actors and comedians and chefs andwinemakers and revelers and rescuers and healers and planners and competitors
and risk takers and thrill seekers and explorers and builders and creators andleaders and followers and yearners and regretters and reminiscers and laughers
and criers . . . and much more besides.
In other words, the overwhelming richness displayed to us by the outside
world is complemented by an equally rich inner experience—almost as if thetwo were made to go together.
Our cup overflows.
DIVING IN
Let’s take a moment to wade in the shallow end before we dive into the deepend. Have a look at Figure 13.1, where you’ll see things that are instantly
recognized as manufactured objects, even if we have no idea what they are. They
are indeed manufactured—out of a hard silica-based material similar to opal. I’ll
also tell you that each of them is tiny enough to fit on the end of a strand of
human hair. With that I think you’d agree that they are remarkable manufactured
objects, exhibiting both technological sophistication and elegance of form
(Figure 13.2 shows some close-up details). Where did these remarkablemanufactured things come from? Are you perhaps picturing a giant
nanofabrication facility in Silicon Valley? If so, you should be blown away tohear that these are actually outer casings from single-celled algae called diatoms.
It’s true. The factories that produced these exquisite pieces of tech art were theindividual algal cells that lived within them!
Sarah Spaulding, an ecologist with the U.S. Geological Survey who has
identified dozens of diatom species, describes her love of them as an obsessionthat began with her first glimpse of them through a microscope. In her words, “I
think that if only other people could see diatoms, they would be just as obsessed
as me.”5 I know the feeling. Just viewing pictures like these triggered a similar
passion in me, almost as though I’m seeing things from another world—theexquisite craftsmanship of an alien superintelligence. How much moreexhilarating it must be to know you’re the first human seeing and describing oneof these extraordinary life forms!
Here’s an interesting thought, then: What if we were meant to be exhilarated
by experiences of this kind? And furthermore, what if we were meant to know
this? What if this thrill—our inner world becoming ecstatic about our outerworld—was meant to be something even deeper and more personal than mere
discovery? What if science was meant to be like geocaching on steroids? Whatmakes finding a well-conceived geocache so delightful is not just the sense of
having found something that was hard to find—though that’s part of it—but thesense of having found something that was both meant to be found and cleverly
made hard to find. The beachcomber with the metal detector outdoes thegeocacher in terms of monetary gain, but the geocacher comes away withsomething much more valuable than lost change and jewelry. The geocacher
comes away with a personal connection to others who are unseen but tangiblysensed and appreciated—another of those beautiful moments when one person
uses his or her inner world to move the outer world in a special way for the
express purpose of touching another.

Figure 13.1 A small sample of outer casings, called frustules, which exist in about 100,000 distinct forms.

Diatom shell, SEM, Steve Gschmeissner/Science Photo Library; diatom frustle, Steve
Gschmeissner/Science Photo Library; diatom alga, SEM, Steve Gschmeissner/Science Photo Library;
diatom, SEM, Steve Gschmeissner/Science Photo Library.

Figure 13.2 Close-up pictures showing the exquisite precision of frustule craftsmanship. The magnificationis the same in both pictures, with the white bar indicating a length of ten millionths of a meter, or one
hundredth of a millimeter.
Ellerbeckia arenaria close-up, L. Bahls (2014) in Diatoms of the United States, retrieved February 23,
2016, from http://western diatoms.colorado.edu/taxa/species/ellerbeckia_are-naria.

Shrieks of approval.
You and I may never have an opportunity to collect diatoms from remotewaters or to place them under the beam of a powerful electron microscope.
That’s okay. Seize rare opportunities like those as they arise, but be assured that
we are surrounded by everyday opportunities to experience the kind of
exhilaration I am talking about. I recall endless fascination as a child watchinghouseflies frolic and groom, ants march along their invisible trails, and pill bugs
roll themselves into protective balls until danger had passed, wondering how
such small creatures could be so complete in their animal behavior. So learn
from the children. If the exhilaration is gone, I guarantee the problem isn’t thatwonders have ceased or that your advanced understanding has emptied them of
all mystery.
Don’t let the Internet replace your firsthand experience of life, but do let it
extend your experience. Having dived in, take another look at fish, for example.
And I mean just look at them, without trying to figure them out or classify them.
On second thought, do classify them, but more as a moviegoer than anichthyologist, and let the exercise provoke you to wonder. How on earth do wefind ourselves on a planet where the great emotive categories of film, story, andstage are so beautifully represented by fish, of all things? Are you in the moodfor fantasy? Try Merlet’s scorpionfish or the mandarinfish (see Plate 3). Moreinclined toward drama or romance? You can’t beat the well-known Siamesefighting fish. How about comedy? My personal favorites are the fringehead fish
and the red-lipped batfish, though the options are numerous. Horror? Lots ofpossibilities here as well. My picks would be the giant stargazer and thefangtooth. And of course we’ve already considered the mighty salmon as themaster of epic tragedy.
What’s going on here? Why this strong resonance between the physicalappearance of fishes and our own emotional makeup? And why is this so typicalof life? We can’t help noticing not just that life comes in a staggering variety offorms but also that so many of these forms strike a chord deep within us, as
though they were meant to do just that. So for us to conclude merely that eachdistinct form of life had to be invented would be to grasp something with thehead only to miss something bigger with the heart. In life we have proof not justthat a great Inventor exists but, more significantly, that a great Creator exists—
someone who invested not just intellectually but also emotionally, just as we
invest in our creations.
CLOSUREThe first world, then, seems to be not the world of mere thinkers but the world of
persons, complete with personhood and personalities. Certainly this is the richestworld, not just comparatively but categorically, which makes nonsense of any
thought that a lesser one brought this greater one into being.
When we take this to be the right picture of reality, the conclusions we havedrawn become even more potent. We decided that insight and purpose are
essential ingredients for invention, and in this way we distinguished theintentional from the accidental, all the while sensing this distinction to be of
profound significance. Now we see just how profound it is. Inventors are not justinventors but creators, and creators are not just creators but persons. And
however insistent the materialists have been that a person is nothing more than aspecial arrangement of ingredients from the periodic table, we now know withcategorical certainty that this cannot be. Our own thinking can’t possibly be
reduced to any physical process because it collapses the moment we suppose
otherwise. We are persons, dwellers in the richest of all worlds, and this richworld of personhood we each inhabit had to come from a source where riches ofthis kind are well known.

We have our answer, then, and we can thank the children for declaring it. The
source from which everything else came is not a what but a who. Of the millionsof species participating in this remarkable adventure called life, only ours has
been given the ability to grasp this most crucial truth. We can and we do, froman early age. Perhaps we also should grasp it, and having grasped it, perhaps weshould hold on to it. Maybe we should pay less heed to the internal tensions thatwould pry this truth from us and more to the truth itself. This truth does, after all,have every appearance of being good, so maybe we resist it for no good reason.
If personhood is at the very center of reality, and if the resonance between us and
our Creator is as deep as we have seen, then friendship with him can’t be far off.
Who knows? He might even understand our cosmic authority problem.

CHAPTER 14

THE NEW SCHOOL
Reflection is valuable near the end of a successful journey. Thinking back, westarted with what seemed like very little. We had nothing but the unresolved
question of where we came from and the determination to follow the truth to theanswer. The problem wasn’t that we had no answer but rather that we had two
answers that contradicted each other. In our childhood, if not since, our design
intuition assured us that life could only be the handiwork of God, or someone
like him. As universal as this intuition is, though, it is almost universally
opposed by the technical experts on life. None of us have been able to erase theintuition, but many of us have struggled to defend it against this professional
opposition—or even to know whether it ought to be defended.
Summoning our courage, we set out to see whether there might be more to
this humble intuition than meets the eye. Everything in our experience told us
this had to be so. Some things really are too good to happen by accident, and if
experience affirms this principle even for mundane things like bricks and shoes,
how can exquisite things like spiders and orcas be exceptions?
Having now added to our experience this journey we’ve nearly completed,
we see that—far from being exceptions—living things are the most striking
examples of this principle. No high-level function is ever accomplished without
someone thinking up a special arrangement of things and circumstances for thatvery purpose and then putting those thoughts into action. The hallmark of allthese special arrangements is high-level functional coherence, which we now
know comes only by insight—never by coincidence.
This vindication of our design intuition has been one of the major
accomplishments along our journey, but there have been others. Having been
reminded of how human scientists are, we’ve learned to let go of the utopian
version of science, which never resembled real science anyway. Likewise, withthe affirmation of our design intuition came the realization that scientificthinking is part of what we all naturally do. The community of professionalscientists gets some things right and some things wrong, just as every othercommunity does. All humans are scientists, and all scientists are human.
Topping off these accomplishments is the weighty realization that the great
Cause of everything clearly reveals himself not as an impersonal force but as avery personal God. Even this fits with the universal design intuition. Creation is
only ever accomplished by drawing upon what exists, and personhood, so
fundamental to our existence, must therefore have come from someone in whom
it already existed. Persons can only have come from a personal God.
We had the right answer to our big question back in our childhood, though
for many of us it was misplaced somewhere between then and now. Thankfully,
what was lost has now been found: We owe our existence to the personal God
who understands our existence. We were never alone.
Nothing I say in the remaining pages will match the importance of thisrediscovered truth, so I won’t even try for that. I hope instead to help us start tothink about the breadth of its importance. When I said at the start that who weare has everything to do with how we ought to live, I didn’t mean this in amoralistic sense. Certainly, the nihilistic message that David Barash preaches tohis students is false, but as we’ve begun to see, God’s presence and the deep
connection we have with him through personhood has much more exciting
implications than the reality of right and wrong.
To give us a taste of this, I want to end by giving us a glimpse of how
exciting the transformation of biology would be if a true understanding of its
place within the big picture were to take hold. And if biology can be transformedin this way, why not other pursuits as well? Laying claim to these prizes will
require much hard work, but in the few remaining pages I hope at least toconvince you that prizes of this transformative kind are really out there waiting
to be claimed—well worth the labor this will require.
We’ll start by thinking not about biology but about another field—one thatwas bursting with the excitement of newness not so long ago.
MIND OVER MATTERIn the mid-1930s the foundations of an entire discipline took shape in the mindof a young Englishman by the name of Alan Turing. Calculating machines had
been conceived and built earlier, but Turing’s invention was altogether different
and better. Where others had invented interesting things, he invented theinteresting idea that suddenly made everything click. His conceptual machine,immortalized as the Turing machine, became the defining model for the
programmable calculating machines we know as computers (Figure 14.1).
Turing hit the mark so perfectly that everything else, including much of ourcommon knowledge about computers, turns out to be incidental. We think ofcomputers as electronic devices with keyboards and displays on the outside andsilicon chips on the inside because in our experience this is what they are. But
these familiar objects are only one way of giving physical form to a Turingmachine. In fact, long before Turing was born, Charles Babbage designed digitalcomputing machines with rotating gears and cylinders. Such things are longforgotten, but interest in modes of computing having nothing to do with siliconchips lives on. Bringing sense to all of this is Turing’s insightful way ofunderstanding the essential elements common to all forms of digitalcomputation.

Figure 14.1 A Turing machine (conceptual) that computes by inverting pennies arranged in a long row.
Anything that can be switched between two distinguishable physical states can be used instead of pennies,
which is why we think of computation in terms of symbols (zeros and ones) instead of physical states. Froman initial start-up state, the machine “reads” the penny under the pointer and then does whatever thecorresponding action rule says. Actions may include inverting that penny and/or changing the internal state
before moving to the next penny, either left or right as specified by the rule. In essence, the row of pennies
functions as memory for input and output, and for performing the computation. The machine is like theCPU of a modern computer; it has a fixed architecture that can be put into any of a large number of
temporary internal states, after which it automatically moves itself from state to state by applying its built-in
action rules to the whole state (including the state of the penny being read). Although the vast majority ofpossible Turing machines do nothing interesting, a special subset known as universal Turing machines arecapable of performing any algorithmic computation, provided they are “programmed” with a row of pennies
carrying the necessary information, along with enough additional pennies for adequate working memory.
Like all interesting inventions, universal Turing machines require extensive functional coherence, making
them fantastically rare within the immense space of possible Turing machines.1

We’ve become dependent on chip-based computing in recent decades, butwe’ve always been more directly dependent on another kind of computing, thisbeing the kind that occurs inside our brains. I’m referring not to mental
calculation but rather to the physical processes carried out by the gray matter
inside our skulls. For example, for the light that enters our eyes to be translated
into a conscious visual scene, it must first be processed by an extraordinarily
sophisticated network of neurons in the occipital lobe at the back of our heads.
You might suppose the secrets of this signal processing have yielded to modern
brain research, but the truth is that the details remain completely mysterious. “In
the deepest sense, we do not know how information is processed, stored, or
recalled” in the brain, said the experts at a recent workshop on brain function.2
The staggering complexity of the brain’s structure, with its hundred trillion
neural connections, is certainly one reason for the slow progress, but I have tothink that false preconceptions are another. Materialism, in particular, hasconstrained thinking within brain science as severely as it has elsewhere. Even
the title of that workshop—From Molecules to Minds—is a proclamation of theview that mental processes are grounded in molecular processes.
Many outstanding experts see through this. For example, Jeffrey Schwartz, ascientist in the Department of Psychiatry at UCLA School of Medicine, has
written a book—The Mind and the Brain—that “challenges the idea that we are
merely biologically programmed automatons and proves that we have the[mental] power to shape our brains.”3 People like Schwartz, make me think it’s
possible for the materialistic view to be displaced from its underserved positionof authority.
At the same time, I can see how people get caught up in the materialistic
view of the mind. Even when computer technology was in its infancy, the idea ofcomputers being “thinking machines” had a certain seductive appeal. They doseem to think, at least in the sense of arriving at answers we arrive at only after
much thought. Since brains are physical things, should we doubt they arethinking things as well, making thought more sophisticated and less mechanicalthan computation, but no less physical?
However plausible this may appear when approached from that angle, theprevious chapter’s thought experiment exposes the underlying fallacy. The plain
fact is that we consciously ground our thoughts in conceptual realities, not inphysical realities. So to claim that the underlying reality of our thought process
is physical is to claim that what is actually happening when we think is
profoundly different from what we think is happening when we think. Since theconceptual realm is where thinking must occur, if it is to occur at all, theproposition that this realm is not fundamentally real would, if taken seriously,
force us to abandon reason as a hopeless pursuit.
Thankfully, we have a much more satisfactory alternative. When we accept
the fundamental reality of the conceptual realm, we see that computers don’t
really think after all. Like can openers and mousetraps and robotic pool cleaners,
they give the impression of knowing what they’re doing only because theirinventors, who really did know what they were doing, imparted genuine
cleverness to their designs. As we saw in chapter 9, the hierarchical structures ofthese inventions reveal how their inventors thought. Far from being exceptions
to this principle, computers and the applications they run are striking examples
of it.
The human brain is different, though. Being the most remarkable componentof the human body, it is arguably the most outstanding physical invention ever toexist. Even more spectacularly, the brain is the one physical invention that serves
as an interface between the physical and conceptual worlds.
Take a moment to let the significance of this send shivers down your spine.
This universe has within its vast swirling wisps of scattered elements a fixed
number of connecting points between the immense realm of things and theinfinite realm of thoughts. You know this because one of these connecting points
is humming with activity right now, inside your skull, enabling you toreconstruct thoughts from physical symbols on paper or on an electronic display.
In purely material terms, these connecting points are as nothing—vastly
outnumbered, outweighed, and outpowered by the stars in our galaxy, which isonly one of a hundred billion galaxies. But that assessment flips the moment wetake all of reality into account. Significance isn’t measured in kilograms or lightyears because, like truth, it belongs to the realm of ideas. Significance istherefore weighed only by those capable of weighing ideas. Once we recognize
this, the profound importance of these special locations in our universe becomesapparent. These connecting points are the places—the only places—where theworld of atoms and the world of ideas are made to shake hands. Poet meetsmuse. Sculptor touches stone. Melody finds strings. Ideas flow to paper. Thirst is
quenched. Loneliness ended.
Absolutely everything of momentous importance in our universe is occurringat these special points, which is why we name and cherish the possessor of each
one—why we celebrate their births and mourn their passing. If the galaxies out
there were capable of grasping the meaning of the universe, their attention would
be fixed on one little planet circling an ordinary star situated in a minor arm of

an otherwise ordinary spiral galaxy. What is present on that one little planet
makes this particular galaxy—the one named after milk—utterly extraordinary.
TWO ROADS
A sobering realization presents itself at this point, followed by an exciting one. Ifmaterialism continues to dominate the sciences, then brain research will continue
to be driven by the pursuit of something unreal, namely the molecular basis ofmind. In that case we will have missed a huge opportunity to learn about what isreal. Of course, any number of facts and physical details will be discovered andcataloged as we continue down this old road, but the full significance of thosefacts can’t possibly be grasped while we labor under a false understanding ofwhat a brain is. On the other hand, if the blinders could somehow be removed
and this whole caravan of effort redirected to a new road—one that starts withsimple truths about life and follows these to technical truths—might we see hugeadvances in a short time? Might we even find that the facts that have alreadybeen cataloged add up to something much bigger and more coherent wheninterpreted through the right lens? The possibility is intriguing (Figure 14.2).
And what about the rest of biology? After all, the old materialist road has agreat many side paths branching off, where specific aspects of life are studied. If
we imagine the new road, some distance away, we see similar branching paths.
Signs marked Cyanobacteria, and Diatoms, and Proteins, and thousands of othersubjects line both main roads. Scientists who access their work from either ofthese two roads would be asking many of the same questions and using mostly
the same methods to answer those questions. The search for new diatom species
and the methods for visualizing their intricate outer casings, for example, would
be identical in the two communities. And yet we anticipate major differences on
the paths marked Brain Function.
What accounts for the major differences?
For one thing, biologists who have traveled the materialist road to their
specializations never ask why things are as they are, at least not in the deepest
sense of the word. If diatom and orca and human are nothing more than leaves
drifting on water, dispersed from a common starting place by fluctuating
currents, then questions of purpose are misplaced. We can talk about how thisleaf came to be here and that leaf there, but since matters of how generally
borrow their significance from matters of why, this isn’t a particularly inspiring
line of inquiry. To add another dollop of dull, Darwinian answers to the howquestion all start to sound pretty similar after you’ve heard a few of them. As far
as I can tell, the only reason for excitement on the path marked Evolution is thatno one really can view life in this hohum way. Life is so arrestingly compellingthat it becomes the spice in what would otherwise be a depressingly bland dish.

Figure 14.2 New-road and old-road interpretations of Figure 9.1. By denying all conceptual aspects ofbiological invention, the materialist view cuts off consideration of an invention’s significance. Withsignificance off the table, and purpose with it, there isn’t much to be said about an invention beyond how it
works and the effects it has.

WINE WITHOUT COST
This profound disconnect between a Darwinian understanding of life and a true
understanding deserves more attention than I can give it here. I’m reminded of

the Dawkins-sponsored ads that appeared on the sides of London buses,
declaring in bright colors, “There’s probably no God. Now stop worrying andenjoy your life” (Figure 14.3). Interesting logic. You are a meaningless byproduct of the percolating ooze in some ancient pond, soon to return to the deadchemicals that burped your ancestors out, sooo . . . go enjoy your life! As strange
as this advice seems to people who don’t see things the way Dawkins does, it
begins to make sense if you pretend that the enjoyment of good things carries noobligation to appreciate their source. For most of us there is much to enjoy inlife, and moreover this bounty is so familiar that many of us take it for granted.
Having done just that, atheists of the Dawkins variety feel free to pair this wineof pleasure with whatever dish of explanation they find most convenient, nomatter how grotesquely incompatible the two may be. You and I may be repelledby the food on their plates, having reasoned that it robs life of all hope andmeaning, but that’s only because we take these implications far more seriously
than they do. For them the plate is just an excuse to keep getting refills on thewine.
I have a great deal more respect for Nagel’s version of atheism, where thedesire to drink the wine on one’s own terms is acknowledged, but not without arecognized obligation to live off the food on one’s own plate. To take thisobligation seriously is both admirable and admirably risky—in the end there
may not be a dish that justifies taking the wine on one’s own terms.
The situation in biology parallels the Dawkins disconnect, I think. Allbiologists are impressed by life. If they weren’t, they wouldn’t have devoted
themselves to studying it. The problem is that life’s splendor is so obvious theytend to take it for granted, pushing it to the background to make room for theiracademic theorizing. But instead of following the implications of their theories
to their logical ends, biologists compartmentalize. Yes, orcas are the product ofblind material forces that had no ability to conceive them, and yes, they take ourbreath away whenever we watch them. Never mind how these two affirmations
fit together. Just pretend they do. Life is meaningless. Isn’t it beautiful?

Figure 14.3 Richard Dawkins posing with ad creator Ariane Sherine in front of one of the London buses
carrying the “peaceful and upbeat” message.
“Atheist Bus Campaign Launch,” Zoe Margolis, used under the Creative Commons license CC BY 2.0, via
Wikimedia Commons.

TWO SCHOOLS
Only a very few research scientists have the opportunity to work against that
disjointed view by openly studying life as something clearly and cleverly
designed. I am one, and I can count the others on my fingers.4 There are more
who would like to have this opportunity, as shown every now and then by apaper that gets past the policing system of an establishment science journal. A
recent example is a description of the architecture of the human hand as being“the proper design by the Creator to perform a multitude of daily tasks in a
comfortable way.”5 Infractions like this almost always bring out the whistleblowers, which almost always brings a reprimand. Everyone must decide forhimself or herself what they can do under the shadow of the materialist flag,knowing that if they press too hard they may lose even the small opportunities
they once had.
Real case histories bear this out, time and again. Two months after this paperon the human hand was published, it was retracted—not by the authors but by
the journal (PLoS One), and not for any technical error that could be described,
but because of “concerns with the scientific rationale, presentation andlanguage.”6 This sounds very much like the vague language of prejudice.
Consistent with that, the retraction mentions only one specific objection:“Following publication, readers raised concerns about language in the article that

makes references to a ‘Creator.’”7 Evidently PLoS One marches on command
whenever a whistle is blown.
Now, if there were a well-known and consistently applied rule forbiddingreferences to deity in science papers, then I suppose actions of this kind would
be excusable. Instead there is a glaring double standard. A decade ago, seventeen
pages of the journal Gene were devoted to a rant against intelligent design that
had plenty to say about God—all negative, of course. In the peer-reviewed pagesof this establishment journal, Emile Zuckerkandl was allowed to speak his mind
with no interference from the thought police. “Kronos is a God who cannot bedenied by any other God. Nor was he by the God of the Jews . . . no God can be
almighty.”8 Ten years on, this one still hasn’t been retracted. Maybe nobody
raised concerns.
I suppose I could have turned this book into a sustained protest against theculture that gives rise to all this injustice. That’s not the book I felt had to be
written, though. Instead, my aim has been to show you that there’s a much morecompelling view of life than the materialist view and that this compelling viewalso happens to be innate—known by us from early childhood and stubbornly
persistent thereafter, such that to deny it requires sustained effort. To achieve myaim I’ve focused first on life generally and then on humanity specifically, hopingthat when people see how durable the simple truths about all life and abouthuman life are, they will be inspired to search out those further truths we needfor an adequate grasp of reality. In other words, I hope to have begun the processof inquiry, not to have completed it.
With respect to life generally, widespread participation in this ongoing searchwould give new vitality to the study of life. In the first place, those whyquestions that have no place on the old road become the intellectual core of the
new road. Until this road becomes more populated, though, some imagination
will be needed to picture the way things could be. One way to get a feel forbiology’s new road is by comparing an engineering discipline, where whys are astaple, with an imaginary old-road version of itself. To do this, imagine that allof humanity has suddenly suffered a highly selective form of amnesia that erased
all knowledge of computers. To top off this pretend disaster, suppose all
documented knowledge about computers vanished—everything from websites totextbooks to videos. A moment ago humans had a deep understanding ofcomputers, but now we find ourselves in a state of ignorance, marveling at thesecomplex machines and wondering how they work.
As more and more technically minded people start examining thesemysterious electronic devices, two schools of thought begin to emerge. The oldschool (on the old road) adopts the view that computers happened by accident,
through a happy but unintended convergence of circumstances, whereas the newschool appeals to the universal design intuition, arguing that because computersshow all the hallmarks of inventions, they must have been invented. Students ofboth schools initially spend their time observing what computers do before
moving toward experimentation, where they try to understand how the various
parts enable them to do what they do.
This is where we begin to see the different schools leading their students in
two very different directions. Students in an old-school computer science labfind themselves surrounded by dusty displays of half-dissected computers withfaded labels naming the major parts. The place of honor at the front of the roomis given to a most impressive display: a collection of microchips arranged
according to the number of legs they have, each carefully impaled with a pin andidentified by a handwritten Latin name. Working in pairs, the young computerscientists pry little pieces off boards taken from dead computers, carefully
sketching them in their laboratory notebooks, knowing they will have tomemorize the technical names and locations of each for Friday’s test. The big
research universities are abuzz with much more advanced work, of course.
Thermal imaging is used to see how much heat the various computer parts
produce in real time and how this depends on the application being run. These
big-time scientists can even read the zeros and ones from an entire hard disk andtest the effects of changing a zero to a one, or vice versa. All very high tech.
Nevertheless what eludes all these old-school computer scientists, despite
their hard work, is the hefty matter of understanding what a computer is. To
know what a computer is made of and what kinds of things it can do is one thing.
To know what it is, is another. The first is of some value, but that value will beseverely limited without the second. Had the young Alan Turing been brought up
in this imagined world, much would have been lost. All thinkers are given acontext in which to think, and when part of that context is the unquestioned
assumption that the things being studied were caused only by other things, thenthe ideas that may have been the real cause are bound to be overlooked.
Shortsightedness of this kind begins with a failure of conviction. When weabandon our design intuition we lose the most potent alarm that would tell us thewrong road has been taken. Having silenced that alarm, workers on the old roadmay continue for any number of generations, assuring themselves of theirproductivity by pointing to the continual growth of knowledge, without everpausing to contemplate the distinction between knowledge and understanding.
Ironically, the inadequacy of the old-school perspective perpetuates the oldschool work by guaranteeing that the goal of complete knowledge will never bereached.
The old road has no end.
GLIMPSING THE NEW
I have a strong feeling the new road has no end either, but here the lack of an end
is a very good thing. We see hints of the new road even now, as thoughoccasionally a scientist takes a side path from the old road so far that they comewithin a stone’s throw of the new road, maybe without realizing it. I think ofPrinceton physicist William Bialek, who heads a research team that measures
how well various biological functions are performed relative to the lofty
standard of physical perfection. He says:
Strikingly, when we do this (and there are not so many cases where it has
been done!), the performance of biological systems often approaches
some limits set by basic physical principles. While it is popular to view
biological mechanisms as an historical record of evolutionary anddevelopmental compromises, these observations on functional
performance point toward a very different view of life as having selected
a set of near optimal mechanisms for its most crucial tasks. . . . The ideaof performance near the physical limits crosses many levels of biologicalorganization, from single molecules to cells to perception and learning in
the brain, and I have tried to contribute to this whole range of problems.9
In other words, in design situations where human engineers would want to push
the limits of physical possibility if they could, we often find that biologicalsystems operate at or near those limits.
There’s more subtlety to this claim than I can unpack in a few words, andsome may be inclined to dismiss it for that reason. To fully grasp the point, youhave to look quite deeply into actual design constraints and objectives. For
example, gazelle legs don’t propel gazelles to speeds remotely approaching the
speed of light (the absolute physical speed limit), but then neither would humanengineers set out to make an all-terrain vehicle that moves anywhere near thatspeed. On the other hand, the eyes of cats do approach the physical limit ofsingle-photon sensitivity, and the antennae of certain male moths do achieve
single-molecule sensitivity to sex pheromones, and certain enzymes do approach
the physical limit of proficiency—processing their reactant molecules as fast as
diffusion can deliver them. To anyone with an appreciation of design challenges,
the long list of believe-it-or-not facts like these coming from biology is truly
astounding.
Since all these facts came out of the old school, firmly situated on the oldroad, you may be wondering about the benefit of relocating biology to a newschool on the new road. Here I go back to our mental picture. The greatest loss
suffered by our imaginary old-school computer scientists is not a shortage of
observations made as outsiders peering into their subject but rather their having
excluded themselves from becoming insiders—from grasping their subject
deeply enough to become participants in it. Now, by suggesting that thematerialist commitment has likewise excluded biologists from participating intheir discipline, I don’t mean biologists would be designing and building newlife forms if Darwin hadn’t taken us down the wrong road.10 I mean that
biologists ought by now to have grasped what life is with enough clarity toinspire a much deeper intellectual appreciation of life. That insight, completely
missing from today’s biology, would shed new light on every subdiscipline. For
something so fundamental not to have this comprehensive effect isinconceivable.11
Consider popular wisdom about genes and DNA. Just as most people thinkscientists have figured out how the brain works, so too they think scientists havefigured out how DNA works. By my casual observation, most nonscientists—and some scientists as well—think the blueprint from which every livingorganism was formed is written on that individual’s genome in the language ofgenes. Accordingly, geese honk because they have the honk gene, andhyperactive dogs yap because they have the hyperactive-dog gene. Likewise, by
this popular view people who can sing or whistle received these abilities byreceiving the corresponding genes. The master template for specifying all our
attributes became public with the publishing of the human genome, supposedly,
so all that remains is to finish the task of assigning traits to genes and toempower every person to read and interpret his or her own personal blueprint.
Coming from that viewpoint, most of us would be shocked to know theactual state of ignorance with respect to DNA. The view that most aspects ofliving things can be attributed neatly to specific genes has been known by
geneticists to be false for a long time, this being the first common DNA myth tofall. A second, which has fallen only quite recently, is that scientists even have aclear understanding of what a gene is. Without exaggeration, a recent article in
Science and Education stated that “the gene concept is currently in crisis.”12 It
turns out that the simple picture of a gene as a section of DNA that encodes aprotein, as described in chapter 3, no longer holds for anything but bacteria. To
give you an idea of how far current thinking has moved from that simple view inrecent years, consider this excerpt from a prominent article in Genome Research:
One metaphor that is increasingly popular for describing genes is to thinkof them in terms of subroutines in a huge operating system (OS). That is,
insofar as the nucleotides of the genome are put together into a code thatis executed through the process of transcription and translation, thegenome can be thought of as an operating system for a living being.
Genes are then individual subroutines in this overall system that are
repetitively called in the process of transcription.13
The fact that ideas like this or like those of William Bialek can be expressed
under the materialist flag is a good thing. The problem comes when people wantto take such radical thoughts seriously. For example, if genomes really are like
operating systems, then the thought of them carrying the blueprints for building
the bodies of their possessors is as wrong as the thought of the iPhone operating
system carrying the plans for manufacturing the iPhone itself. And if we allow
ourselves to take that idea seriously, then the thought of genetic mutations
having changed a primordial organism into all modern forms of life is seen to be
confused over and above its mistaken reliance on accidental causes. For an
iPhone 5 to be converted into an iPhone 6 by upgrading its operating system iscategorically impossible—with or without insight. Extending that principle tolife would take us beyond our conclusion that modern life can’t be the product ofaccidental mutations—implying it can’t be the product of mutations at all.
So if this is where the thoughts go, are we allowed to go with them?
My point—my plea—is that scientists ought to be encouraged not only todevelop ideas that touch biology so deeply but also to take those ideas seriously
enough to test and extend them. Efforts of this kind ought to be hailed as thesurest sign that the scientific community is alive and well. If we can agree on
that, then there are bright days ahead. Indeed, I am convinced that the very bestdays in the study of life were not the days that catapulted that laboratory under
the direction of Max Perutz to lasting fame—the days when life’s smallest pieces

were revealed to humanity for the first time. The very best days, still to come,will be those when all the pieces come together under a set of organizing
principles by which they suddenly make sense.
Biology awaits its Turing machine.
COMMON GOOD
That the deepest questions in biology have not yet been answered means they arestill asking to be answered. Anyone who cares to examine the facts carefully will
see that the old answers were wrong. They have now been erased, in our minds
anyway, and we must sit down to take the test again, with new minds and new
resolve. Having learned much since Darwin’s day, we have every reason for
optimism this time. Speaking as a scientist, I can’t think of a more attractive
message to convey to young people of technical ability.
Speaking as a human, though, I see something even more beautiful. Yes, thedeepest questions in the scientific study of life are up for grabs, and this isexciting for the technically minded. But the deepest truths of life itself, and of
human life in particular, were never really up for grabs. These were neverrestricted to the most clever. Some things, of course, can only be seen bystanding on the shoulders of giants, but the most crucial things have always been
seen best by standing on the ground.

ACKNOWLEDGMENTS
A big thank you to the many people who’ve helped me in various ways. Thanks
first to my agent, Giles Anderson, for his work at the early stages to get the bookunderway. My editor, Katy Hamilton, oversaw the whole project at HarperOne
and, with executive editor Mickey Maudlin, recommended structural changes tothe manuscript that turned out to be extremely helpful. Thank you both! NoëlChrisman’s attention to detail improved the book considerably at the copyedit
stage, for which I’m very grateful. And thanks to Ann Edwards, Anna
Paustenbach, and Jane Chong of HarperOne and to Rob Crowther of Discovery
Institute for the care and insight they brought to the task of increasing the book’s
visibility.
I thank Brian Gage for directing the illustration work and Anca Sandu foradding her creative talent to the project (along with her patience). Thanks also to
Rachel Aldrich for her work on image acquisition.
I deeply appreciate the time many people took to read the manuscript, in partor in whole, and to offer their comments. Titus Kennedy, Casey Luskin, George
Montañez, Steve Zelt, Steve Fuller, Bill Dembski, Jonathan Wells, Rebecca
Keller, Mariclair Reeves, Jacob Koch, Grant Gates, Ann Gauger, Fraser Ratzlaff,
Chuck Wallace, and Eric Garcia are all to be thanked for this, as are Jim andPaula Thomas for generously giving me a beautiful place to read the manuscript
myself.
I’m very grateful to Jim Wiggins for supporting this project, and to the
Biologic board for giving me the time to complete it: Steve Meyer, Ted
Robinson, Scott Webster and former board member Chuck Anderson—a friend
who didn’t live to see the book published but who was a huge inspiration along
the way.
Special thanks to my brother Ron for his ongoing interest in this work and to
my father, Rick, for his unfailing and enthusiastic support and inspiration.
Among the young people who’ve been an inspiration to me as I’ve thought
about the design intuition are my niece, Jordan, and my own three children—
Noelle, Caitlyn, and Ryan (credit for the Undeniable title going to Caitlyn, by

the way).
A “gazillion” thanks to Anita—my wife and best friend—for gently steering
me when I’ve needed it most.
And finally, quoting my Ph.D. thesis: “I should express my gratitude to anddependence upon the One who made both the universe and the mind with which
I seek to comprehend it. I have accomplished nothing of significance apart from
Him, nor will I ever.”NOTES
Chapter 1: The Big Question
1. Francis Crick, What Mad Pursuit: A Personal View of Scientific Discovery (New York: Basic Books,
1988), 138.
2. All editions of Darwin’s book are freely available online. The Darwin Online site is the best resource:
http://darwin-online.org.uk/EditorialIntroductions/Freeman_OntheOriginofSpecies.html.
3. Charles R. Darwin, The Origin of Species by Means of Natural Selection, or the Preservation of
Favoured Races in the Struggle for Life, 6th ed. (London: John Murray, 1872), 424.
4. Thomas Nagel, Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost
Certainly False (Oxford: Oxford Univ. Press, 2012).
5. There are clear signs that the days of the materialist flag are numbered. According to Robert Koons(University of Texas at Austin) and George Bealer (Yale University): “Materialism is waning in a
number of significant respects—one of which is the ever-growing number of major philosophers who
reject materialism or at least have strong sympathies with anti-materialist views.” Robert C. Koons andGeorge Bealer, eds., introduction to The Waning of Materialism (Oxford: Oxford Univ. Press, 2010).
6. Thomas Nagel, The Last Word (Oxford: Oxford Univ. Press, 1997), 130–31.

Chapter 2: The Conflict Within
1. Darwin to Joseph Hooker, 1871, as recorded in a footnote in The Life and Letters of Charles Darwin,
Including an Autobiographical Chapter, ed. Francis Darwin, vol. 3 (London: John Murray, 1887), 18.
2. Alison Gopnik, “See Jane Evolve: Picture Books Explain Darwin,” Mind and Matter, Wall Street
Journal,
April
18,
2014,
http://online.wsj.com/news/articles/SB10001424052702304311204579505574046805070.
3. A teleological explanation is an explanation in terms of purpose. The source of the quote is Art Jahnke,“The Natural Design Default: Why Even the Best-Trained Scientists Should Think Twice,” Bostonia,
Winter/Spring 2013, www.bu.edu/bostonia/winter-spring13/the-natural-design-default/.
4. Plutarch, “Fortune,” trans. Frank Cole Babbitt, in Moralia, vol. 2, Loeb Classical Library (Cambridge:
Harvard Univ. Press, 1928), 87.

Chapter 3: Science in the Real World
1. “Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution,” The Wistar InstituteSymposium Monograph Number 5, ed. P. S. Moorhead and M. M. Kaplan (Philadelphia: Wistar
Institute Press, 1967).

2. Michael Denton, Evolution: A Theory in Crisis (London: Burnett Books, 1985). Other significant books
during this period include C. Thaxton, R. L. Olsen, and W. L. Bradley The Mystery of Life’s Origin:
Reassessing Current Theories (Dallas: Lewis and Stanley, 1984) and A. E. Wilder-Smith The Natural
Sciences Know Nothing of Evolution (Master Books, 1981).
3. Scientists call the appendages side chains, which is confusing because most of them don’t look likechains, whereas the proteins made by connecting amino acids do look like chains. I will stick withappendages for that reason.
4. Some proteins need help during folding to avoid interference from the many other proteins that crowd
the cell interior. Cells use special proteins called molecular chaperones to assist folding, some of which
form specialized compartments in which new protein chains can fold without interference. The
compartment-forming chaperones are called chaperonins.
5. Because any of the four bases (A, C, G, and T) can be placed at any base position, the number ofpossible sequences in a run of consecutive bases is calculated by multiplying by 4 repeatedly—one 4
for each base position. This means a run of two bases allows 16 possibilities (4 × 4 = 16), which isn’t
enough to specify each of the 20 amino acids. Life therefore uses codons of three consecutive bases,
bringing the number of possibilities to 64 (4 × 4 × 4 = 64).
6. Denton, Evolution, 327.
7. Denton, Evolution, 323.
8. D. D. Axe, N. W. Foster, and A. R. Fersht, “Active Barnase Variants with Completely Random
Hydrophobic Cores,” Proceedings of the National Academy of Sciences USA 93 (1996): 5590–94.
9. D. D. Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme
Exteriors,” Journal of Molecular Biology 301 (2000): 585–95.
10. Transcribed from “Standing Up in the Milky Way,” Cosmos: A Spacetime Odyssey, Fox, aired March 9,
2014,
www.dailymotion.com/video/x25wxcj_cosmos-a-spacetime-odyssey-episode-1-season-1standing-up-in-the-milky-way_tv.

Chapter 4: Outside the Box
1. D. D. Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme
Exteriors,” Journal of Molecular Biology 301 (2000): 585–95.
2. E. M. Brustad and F. H. Arnold, “Optimizing Non-natural Protein Function with Directed Evolution,”
Current Opinion in Chemical Biology 15 (2011): 201–10.
3. M. Altamirano et al., “Directed Evolution of New Catalytic Activity Using the α/β-Barrel Scaffold,”
Nature 403 (2000): 617–22.
4. M. Altamirano et al., “Retraction: Directed Evolution of New Catalytic Activity Using the α/β-Barrel
Scaffold,” Nature 417 (2002): 468.
5. “The God Lab: Advocates of Intelligent Design Have a New Strategy, and It Has Science at Its Centre,”
New Scientist, December 16, 2006, 8–11.
6. “Top School’s Creationists Preach Value of Biblical Story over Evolution,” Guardian, March 8, 2002,
www.theguardian.com/uk/2002/mar/09/schools.religion.
7. “Creationism
Row
ReachesUK,”
New
Scientist,
March
14,
www.newscientist.com/article/dn2045-creationism-row-reaches-the-uk.html#.VIJV976QTO9.

2002,

8. “More Than Three-Quarters of a Century after the Scopes Monkey Trial, Darwin’s Opponents Aren’tEven Thinking of Giving Up,” Creation vs. Evolution, part 1, Newsday, March 11, 2002.
9. “Six Days of Creation: The Search of Evidence; A Widening Movement against Evolutionary Theory
Seeks Scientific Support,” Creation vs. Evolution, part 2, Newsday, March 12, 2002.
10. Personal e-mail from Douglas Axe to Bryn Nelson, Tuesday, March 5, 2002.
11. D. D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,”
Journal of Molecular Biology 341 (2004): 1295–315.
12. For an extended example of whistle-blowing, see Barbara Forrest and Paul R. Gross, Creationism’s
Trojan Horse: The Wedge of Intelligent Design (Oxford: Oxford Univ. Press, 2004). Forrest’s research
for this book led her to me in 2000 and again in 2001, at which point it became clear that she wanted
me to say my 2000 Journal of Molecular Biology paper had no implications for ID. After I refused togive her a statement to that effect, she and Gross gave their readers their own assurance in a rather
panicked tone: “There is nothing in that article—certainly nothing explicit by any stretch of the verb’s
meaning—to ‘support’ ID. No working molecular or cell biologist, among several colleagues we haveconsulted, has reported otherwise.” See page 41 (emphasis in original).
13. David P. Barash, “God, Darwin and My College Biology Class,” New York Times, September 27, 2014,
www.nytimes.com/2014/09/28/opinion/sunday/god-darwin-and-my-college-biology-class.html?_r=0.

Chapter 5: A Dose of Common Science
1. Michael Denton, Evolution: A Theory in Crisis (London: Burnett Books, 1985).
2. Alison Gopnik, “See Jane Evolve: Picture Books Explain Darwin,” Mind and Matter, Wall Street
Journal,
April
18,
2014,
http://online.wsj.com/news/articles/SB10001424052702304311204579505574046805070.
3. E. M. Brustad and F. H. Arnold, “Optimizing Non-natural Protein Function with Directed Evolution,”
Current Opinion in Chemical Biology 15 (2011): 201–10.

Chapter 6: Life Is Good
1. Charles Darwin, On the Origin of Species by Means of Natural Selection, 1st ed., chap. 4 (London:
John Murray, 1859), 84.
2. A. K. Gauger and D. D. Axe, “The Evolutionary Accessibility of New Enzyme Functions: A Case
Study from the Biotin Pathway,” BIO-Complexity, no. 1 (2011): 1–17.
3. M. A. Reeves, A. K. Gauger, and D. D. Axe, “Enzyme Families: Shared Evolutionary History or
Shared Design? A Study of the GABA-Aminotransferase Family,” BIO-Complexity, no. 4 (2014): 1–16.
4. Charles R. Marshall, “When Prior Belief Trumps Scholarship,” Science 341 (2013): 1344.
5. Stephen C. Meyer, Darwin’s Doubt: The Explosive Origin of Animal Life and the Case for Intelligent
Design (San Francisco: HarperOne, 2013).
6. In chapter 10, we’ll see that genomic data contradict Marshall’s suggestion. I let this go here in order tomake a different point.
7. O. Khersonsky and D. S. Tawfik, “Enzyme Promiscuity: A Mechanistic and Evolutionary Perspective,”
Annual Review of Biochemistry 79 (2010): 471–505.
8. R. Mukhopadhyay, “Close to a Miracle: Researchers Are Debating the Origins of Proteins, ASBMB
Today 12, no. 9 (2013): 12–13.

Chapter 7: Waiting for Wonders
1. Associated Press, “Seahawks Fans Set Noise Mark,” ESPN, December 3,
http://espn.go.com/nfl/story/_/id/10071653/seattle-seahawks-fans-set-stadium-noise-record.

2013,

2. Richard Dawkins, The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without
Design (London: Longman, 1986).
3. Graham Bell, Selection: The Mechanism of Evolution, 2nd ed. (Oxford: Oxford Univ. Press, 2008).
4. People who’ve done the math on natural selection have also come to a modest view of its power. For
those interested, two key findings have led to this modest view. The first is that factors other than
genetic fitness tend to dominate in determining which individuals pass their genes to subsequent
generations. This is reflected in the fact that the effective sizes of natural populations (i.e., the sizes ofideal populations lacking these competing factors that would carry the same genetic diversity as thewild populations) tend to be much smaller than the actual populations (see, for example, T. F. Turner, J.
P. Wares, and J. R. Gold, “Genetic Effective Size Is Three Orders of Magnitude Smaller Than Adult
Census Size in an Abundant, Estuarine-Dependent Marine Fish,” Genetics 162 [2002]: 1329–39). The
second finding is that the likelihood of a newly generated beneficial mutation becoming established in
an ideal population is only twice the fractional fitness advantage. Since these advantages tend to bevery slight and since real populations are far from ideal, likelihoods for real populations turn out to be
surprisingly small. Calculated as twice the fractional fitness advantage multiplied by the ratio of theeffective population size to the actual population size (M. Kimura, “Diffusion Models in Population
Genetics,” Journal of Applied Probability 1 [1964]: 177–232), the likelihood of the first possessor of a
new beneficial mutation passing that mutation to the entire species can easily be less than one in a
million. This improbability is further compounded by the rarity of beneficial mutations in the firstplace. Worse still, these widely acknowledged problems are all overshadowed by an even larger
problem that isn’t widely acknowledged, namely the irrelevance of the beneficial mutations that do
happen from time to time to the invention of anything remarkable. This book focuses on this more
fundamental problem.
5. D. D. Axe and A. K. Gauger, “Model and Laboratory Demonstrations That Evolutionary Optimization
Works Well Only If Preceded by Invention: Selection Itself Is Not Inventive,” BIO-Complexity, no. 2(2015): 1–13.
6. D. D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,”
Journal of Molecular Biology 341 (2004): 1295–315.
7. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds.”
8. Axe and Gauger, “Model and Laboratory Demonstrations.”
9. A. K. Gauger et al., “Reductive Evolution Can Prevent Populations from Taking Simple Adaptive Paths
to High Fitness,” BIO-Complexity, no. 2 (2010): 1–9.
10. Gauger et al., “Reductive Evolution.”

Chapter 8: Lost in Space
1. Choose “Select whole earth”; type “2000” in the “No. of points” box; click “Get random point(s)”;click “See it on map.”
2. Strictly speaking, systematic egg-hunt searches become progressively less blind as the search continues
because each wrong guess is crossed off the list of remaining possibilities. However, the advantage ofsystematic searching like that only becomes significant in cases where a substantial fraction of thepossibilities can be tested. Since we’re interested in cases where this isn’t true, we won’t need to
distinguish systematic searching from blind searching.
3. I mean physical events divided down to the scale of atomic interactions. Larger physical events are farless numerous and are generally composed of these atomic-level events, so this is a very generous way
to estimate the maximum number of physical events that might accomplish something of interest. The
estimate starts with the fact that a chain of cause-and-effect involving atomic interactions can’t
propagate effects faster than the speed of light. The time for light to travel an atomic distance (oneangstrom) therefore sets a lower limit on the time interval needed for a physical event on this scale.
There have been about 1036 of these event intervals in the 14 billion-year history of the universe. The
maximum number of physical events over the history of the universe is calculated by multiplying thisnumber of event intervals (1036) by the number of atoms (1080), resulting in a number (10116) thatfills just under one and a half lines of text.
4. A 1-pixel search space has 16,777,216 color possibilities. Every time we increase our search space by 1
pixel, we must multiply by 16,777,216. A 3-by-5 pixel rectangle contains 15 pixels, so we’re
multiplying that first 16,777,216 by 16,777,216 fourteen times.

Chapter 9: The Art of Making Sense
1. Richard Dawkins, The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without
Design (London: Longman, 1986).
2. NASA, Apollo 13 Technical Air-to-Ground Voice Transcription (Houston: Manned Spacecraft Center,
April 1970), www.hq.nasa.gov/alsj/a13/AS13_TEC.PDF.
3. In effect, we used random typing to estimate the fraction of the search space covered by the overly
generous target. Once we have that fraction, the principle of reciprocal scale tells us how many blind
attempts (which need not be random) are needed for success to be expected.
4. Low pixel resolution was used to avoid exaggerating the color extension. The point is that we see thesubject matter of photos even when the pixel resolution is minimal, not because the pixels are invisibly
small but because they work together in a visually coherent way.
5. Mathematica is a symbolic mathematical computation program developed by Wolfram Research,
available at www.wolfram.com/mathematica.

Chapter 10: Coming Alive
1. Thomas Nagel, Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost
Certainly False (Oxford: Oxford Univ. Press, 2012), 32.
2. For a beautiful video of the sliding movements in one cyanobacterial species, see “Oscillatoria in
Motion” from the YouTube collection of Bruce Taylor (www.youtube.com/watch?v=IP4ir0wumpw).
3. Richard Platt and Stephen Biesty, Stephen Biesty’s Incredible Cross-Sections (New York: Alfred A.
Knopf, 1992).
4. For the technically inclined, I highly recommend this review article: I. Grotjohann and P. Fromme,“Structure of Cyanobacterial Photosystem I,” Photosynthesis Research 85 (2005): 51–72.
5. In addition to sunlight, air, and water, this larger project calls for traces of various minerals that arepresent in all natural bodies of water.

6. The term intrinsically disordered proteins refers to a class of proteins that exploits a partially (orcompletely) unfolded state to perform certain biological functions. Specific functions always require a
degree of amino-acid sequence specificity, though this may be lower for these less structured proteins.
However, since all life is absolutely dependent on a large number of precisely folded proteins, these are
my focus. The arguments and evidence I present with respect to folded proteins are unaffected by theexistence of proteins that don’t fold.
7. D. D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,”
Journal of Molecular Biology 341 (2004): 1295–315.
8. A successful blind search for a folded protein of this size isn’t quite fantastically improbable, so we
can’t say that it’s physically impossible. However, we can say that it’s biologically impossible byMichael Denton’s 1 in 1040 criterion. Since the invention of proteins is a biological problem, Denton’scriterion is more relevant. It makes little difference, however, because accidental inventions requiring
just two new proteins are impossible by both standards.
9. C. Beck et al., “The Diversity of Cyanobacterial Metabolism: Genome Analysis of Multiple
Phototrophic Microorganisms,” BMC Genomics 13 (2012): 56.
10. K. Khalturin et al., “More Than Just Orphans: Are Taxonomically Restricted Genes Important in
Evolution?” Trends in Genetics 25, no. 9 (2009): 404–13.
11. L. Jaroszewski, “Exploration of Uncharted Regions of the Protein Universe,” PLoS Biology 7, no. 9(2009): e1000205.
12. Some readers may prefer to credit highly intelligent life from another planet with the invention ofearthly life. The first problem with this, if it’s an attempt to avoid God, is that these hypothetical supergeniuses would themselves have had to be invented by an intelligent creator. In the end, there’s no way
around the fact that the first intelligent planetary life must have been created by an intelligence outside
the universe, which sounds very much like God. The second problem is the categorical impossibility ofanyone but God creating minds (a point to be picked up in chapter 13). Having now given you myreasoning, I won’t hesitate to name God as the intelligent designer from this point forward. I do,
however, want to stress that I am speaking for myself, not for the community of people who affiliate
with ID.

Chapter 11: Seeing and Believing
1. Paul Rosenberg, “God Is on the Ropes: The Brilliant New Science That Has Creationists and theChristian
Right
Terrified,”
Salon,
January3,
2015,
www.salon.com/2015/01/03/god_is_on_the_ropes_the_brilliant_new_science_that_has_creationists_and_the_christian_right_terrified.
2. Quoted in Natalie Wolchover, “A New Physics Theory of Life,” Quanta, January 22, 2014,
www.quantamagazine.org/20140122-a-new-physics-theory-of-life/.
3. Ernst Haeckel, The History of Creation, vol. 1, Project Gutenberg, www.gutenberg.org/files/40472.
4. C. E. Dobell, Antony van Leeuwenhoek and His “Little Animals” (New York: Harcourt, Brace, 1932).
5. Richard Dawkins, The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without
Design (New York: Penguin, 1988), 9. Emphasis in original.
6. Quoted by permission from a pre-edit version of J. M. Tour, “Why Is Everyone Here Lying?”
Inference: International Review of Science 2, no. 2 (2016).
7. Dawkins, The Blind Watchmaker, 49. Emphasis in original.

8. Discover, February 2005.
9. The evolved function was the equality function, which compares two binary input numbers and returns
a 1 at positions where they match and a 0 at positions where they don’t match. See R. E. Lenski et al.,“The Evolutionary Origin of Complex Features,” Nature 423 (2003): 139–44.
10. The first of the following papers is an analysis of the demonstration featured in Discover magazine. W.
Ewert, W. A. Dembski, and R. J. Marks II, “Evolutionary Synthesis of NAND Logic: Dissecting a
Digital Organism,” in Proceedings of the 2009 IEEE International Conference on Systems, Man, andCybernetics (Piscataway, NJ: IEEE Press, 2009), 3047–53; G. Montañez et al., “A Vivisection of the ev
Computer Organism: Identifying Sources of Active Information,” BIO-Complexity, no. 3 (2010): 1–6;
W. Ewert, W. Dembski, and R. J. Marks II, “Climbing the Steiner Tree: Sources of Active Information
in a Genetic Algorithm for Solving the Euclidean Steiner Tree Problem,” BIO-Complexity, no. 1(2012): 1–14; and W. Ewert, W. A. Dembski, and R. J. Marks II, “Active Information in Metabiology,”
BIO-Complexity, no. 4 (2013): 1–10.
11. N. Cheney et al., “Unshackling Evolution: Evolving Soft Robots with Multiple Materials and a
Powerful Generative Encoding,” GECCO ’13, July 6–10, 2013, Amsterdam, The Netherlands.
12. www.biologic.org/stylus.
13. D. D. Axe, P. Lu, and S. Flatau, “A Stylus-Generated Artificial Genome with Analogy to Minimal
Bacterial Genomes,” BIO-Complexity, no. 3 (2011): 1–15.
14. D. D. Axe and A. K. Gauger, “Model and Laboratory Demonstrations That Evolutionary Optimization
Works Well Only If Preceded by Invention: Selection Itself Is Not Inventive,” BIO-Complexity, no. 2(2015): 1–13.

Chapter 12: Last Throes
1. Charles R. Darwin, The Origin of Species by Means of Natural Selection, or the Preservation of
Favoured Races in the Struggle for Life, 1st ed. (London: John Murray, 1859), 189.
2. “List of Scientific Bodies Explicitly Rejecting Intelligent Design,” Wikipedia, last accessed May 7,
2016; https://en.wikipedia.org/wiki/List_of_scientific_ bodies_explicitly_rejecting_Intelligent_Design.
3. “An Intelligently Designed Response,” editorial, Nature Methods 4, no. 12 (December 2007): 983.
4. P. Shipman, “Being Stalked by Intelligent Design,” American Scientist 93 (2005): 502.
5. E. Zuckerkandl, “Intelligent Design and Biological Complexity,” Gene 358 (2006): 2–18.
6. “An Intelligently Designed Response,” 983.
7. P. Ball, “What a Shoddy Piece of Work is Man,” Nature online (May 3, 2010):
doi:10.1038/news.2010.215.
8. Marshall Berman, “Intelligent Design: The New Creationism Threatens All of Science and Society,”
APS News, October 2005, 8.
9. G. Weissmann, “The Facts of Evolution: Fighting the Endarkenment,” FASEB Journal 19 (2005):
1581–82.
10. Shipman, “Being Stalked by Intelligent Design,” 502.
11. G. Petsko, “It Is Alive,” Genome Biology 9 (2008): 106.
12. Hugo De Vries, Species and Varieties: Their Origin by Mutation (Chicago: Open Court Publishing,1904), 4.

13. This sudden turn was discussed in chapter 1.
14. De Vries, Species and Varieties, 825–26. De Vries attributes the quote to a Mr. Arthur Harris, without
citing a source. I have added emphasis to underscore the point.
15. W. Fontana and L. W. Buss, “‘The Arrival of the Fittest’: Toward a Theory of Biological Organization,”
Bulletin of Mathematical Biology 56, no. 1 (1994): 1–64. Emphasis added.
16. Fontana and Buss, “‘The Arrival of the Fittest,’” 2.
17. A. Wagner, Arrival of the Fittest: Solving Evolution’s Greatest Puzzle (New York: Current, 2014), 5(emphasis in original) and 14.
18. Wagner, Arrival of the Fittest, 215–16.
19. Here, I should amplify a thought I alluded to in chapter 6, which is that the physical universe is itself astunningly brilliant and beautiful invention. The point is that it’s not an inventor.
20. E. V. Koonin, “The Cosmological Model of Eternal Inflation and the Transition from Chance toBiological Evolution in the History of Life,” Biology Direct 2 (2007): 15.
21. In chapter 13, we’ll see why the first assumption is incorrect. Once this is established, the existence ornonexistence of the multiverse becomes irrelevant.

Chapter 13: First World
1. Thomas Nagel, Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost
Certainly False (Oxford: Oxford Univ. Press, 2012), 31.
2. Nagel, Mind and Cosmos, 20.
3. Nagel, Mind and Cosmos, 25.
4. Nagel, Mind and Cosmos, 67.
5. Sarah
Spauldingbiography,
Diatomsofdiatoms.colorado.edu/about/participant/spaulding_sarah.

theUnitedStates,http://western

Chapter 14: The New School
1. Roger Penrose does an excellent job of developing this point in The Emperor’s New Mind: Concerning
Computers, Minds, and the Laws of Physics (Oxford: Oxford Univ. Press, 1989).
2. “Grand Challenge: How Does the Human Brain Work and Produce Mental Activity?,” in From
Molecules to Minds: Challenges for the 21st Century; Workshop Summary (Washington, D.C.: National
Academies Press, 2008), www.ncbi.nlm.nih.gov/books/NBK50989/.
3. J. M. Schwartz and S. Begley, The Mind and the Brain: Neuroplasticity and the Power of Mental Force(ReganBooks, 2003). Quoted from description on back cover.
4. I would be delighted to find that I’ve exaggerated the scarcity of biologists at research institutions who
are free to work outside the confines of materialism. Like me, nearly everyone in this small collectionof scientists must go outside the big establishment institutions to be free from their influence.
5. M.-J. Liu et al., “Biomechanical Characteristics of Hand Coordination in Grasping Activities of Daily
Living,” PLoS One 11, no. 1 (2016), doi:10.1371/journal.pone.0146193.
6. PLoS One Staff, “Retraction: Biomechanical Characteristics of Hand Coordination in Grasping
Activities of Daily Living,” PLoS One 11, no. 3 (2016), doi:10.1371/journal.pone.0151685.

7. PLoS One Staff, “Retraction.”
8. E. Zuckerkandl, “Intelligent Design and Biological Complexity,” Gene 358 (2006): 2–18.
9. William Bialek biography, Princeton University website, www.princeton.edu/~wbialek/wbialek.html.
10. Although scientists have for decades been able to make designed changes to the DNA carried by someorganisms, this comes nowhere close to conceiving and designing a new form of life. In fact, having
concluded that mind can’t have a material basis, we conclude that it’s impossible for humans to invent
minds, and therefore equally impossible for humans to invent organisms with minds. We invent
thoughts directly, some of these thoughts inspiring our material inventions. Minds, however, are neithermaterial things nor thoughts; rather, minds are immaterial entities that have thoughts.
11. A common mistake is the thought that the new school can’t be launched until it has physicaldescriptions of the origins of the various forms of life to replace the physical description offered by theold school. The insistence that there is nothing to be said about life apart from physical descriptions ofphysical processes is precisely the claim being challenged by the new school. By opening the door tothe much more intellectually rich questions surrounding the ideas behind life, the new school launches
itself in a completely different direction. The old question of what the various origins events would
have looked like if they had been captured on video doesn’t rank very high on the new school’s
priorities.
12. L. M. N. Meyer, G. C. Bomfim, and C. N. El-Hani, “How to Understand the Gene in the Twenty-First
Century?” Science and Education 22, no. 2 (2011): 345–74.
13. M. B. Gerstein et al., “What Is a Gene, Post-ENCODE? History and Updated Definition,” Genome
Research 17 (2007): 669–81, http://genome.cshlp.org/content/17/6/669.full.pdf+html.

CREDITS
Grateful acknowledgment is given to those credited for the use of their work in this book. All otherillustrations are by Anca Sandu with art direction by Brian Gage.
Cover design: © HarperCollins
Cover photography: Mark Bridger | Getty Images | ShutterstockINDEX
The pagination of this electronic edition does not match the edition from which it was created. To locate a
specific entry, please use your e-book reader’s search tools.
accidental invention, 14, 98–102, 160, 189–94, 196
accidents, 14, 17, 57, 86, 160–61
alphabet soup, 16, 64, 99, 100, 152, 223–24
Altamirano, Myriam, 41–43, 45–46, 50
American Chemical Society, 218
amino acids, 27–30, 33–35, 178–82
amoebas, 65–66
animal behavior, 55
animals, 75, 80
antennas, 170–74, 205–6
anthropic principle, 228–29
antibodies, 208–9
anti-faith scientists, 44“anti-science”, 54
Apollo 13 accident, 139–42
appearance of the impossible, 196
Arrival of the Fittest—Solving Evolution’s Greatest Puzzle (Wagner), 222“‘Arrival of the Fittest’: Toward a Theory of Biological Organization, The” (Fontana & Buss), 220–21
atheism, 6–9, 163–64, 232, 242–46, 263
Australia, 119
authoritarian science, 40, 62
authority, 14
automatic spelling correction, 153
awkwardness, 7
Babbage, Charles, 257
Babraham Institute, 54
bacteria, 46, 104–10, 191. See also cyanobacteria
balance, 60
Barash, David, 55, 255
Baylor University, 194
beachcombers, 114, 116, 248
Bell, Graham, 96
beta-lactamase, 104
Bialek, William, 269, 272
Biesty, Stephen, 168
big question, 3, 9–11, 163, 254bio-critic, 77–78
biological functions: perfection of, 269–70; proteins and, 27–31, 57, 81–84; selection and, 96–98
Biologic Institute, 51, 81, 108, 210
biology, 11, 255, 260–61, 266–73
Blair, Tony, 52
blind searches, 115, 135–36, 146–51, 154, 179
Blind Watchmaker, The (Dawkins), 96, 136, 192, 198–200
brain function, 239–40, 257–60, 261
brain research, 257–58, 260
Buss, Leo, 220–22
busy wholes, 68–71, 113
Centre for Protein Engineering (CPE), 1, 41, 43, 46, 50, 51
chance, 21, 30, 83, 201
children, 19, 61, 66, 185, 236, 242, 249, 251
Chinese characters, 210–12
coincidence, 100–103, 151–53
coincidental coherence, 154commitment, 75–77
common good, 273–74
common science, 10–11, 60–61, 96, 184–85, 189, 232
common sense, 60, 189, 232
completed projects, 69
completeness, 188
complexity, 22–23, 30
computational function demonstration, 201–4
computers, 255–56, 267–68“conditions of life”, 80
connecting points, 259–60
consciousness, 44, 65–66, 165, 235–38
contradiction, 188conviction, 268
Cornell University, 206‘correlative entrainment’, 99–100, 152
cosmic authority problem, 8, 242, 251
cosmology, 227–28
Cosmos: A Spacetime Odyssey (television series), 37
counterintuitive evolutionary alternatives, 62
coverage principle, 119–22
creationism, 48, 219
creators, 250
Crick, Francis, 3, 10, 32
critical dialogue, 216–19
cuna search, 117–18, 131
cuna target, 118, 121, 132, 150, 184
curiosity, 9cyanobacteria, 167–75, 183, 191, 261
Darwin, Charles, 3–5, 14, 17, 190, 216
Darwinism: Dawkins defense of, 136, 192; impoverished view of life and, 71; materialism and, 188;

peculiar aspect of, 18; prior challenges to, 39; reconciling with high view of life, 72–79; retreat from,
219–24; teaching of alternatives in state-funded schools, 46, 52–54; Wagner critique of, 222–23. See
also evolution; evolutionary theory; natural selection
Darwin’s Doubt (Meyer), 84
data, 60
Dawkins, Richard, 96, 192, 198, 263–64
Dawkins computer demonstration, 198–201
Dembski, William, 46, 53
Denton, Michael, 26, 30–31, 57
deoxyribonucleic acid (DNA), 30, 105, 108, 271–72
designer, 47–48
design intuition: affirmation of, 254; counterintuitive evolutionary alternatives, 62; gene sequences and, 27;
higher version of, 44; internal conflict and, 10, 14–15, 17–19, 22, 25; knowledge and, 158–60; as law,
20–21, 64; principle of reciprocal scale and, 155; protein sequences and, 27–31; science of interpreting
our everyday experiences and, 187; scientific consensus and, 64; scientific facts and, 59; truth and, 63–
64; use of observation and calculation, 87–88; validation through firsthand experience, 60; vindicationof, 254; whole projects, 68–69
De Vries, Hugo, 220
diatoms, 246–47, 261
digital images, 123–25, 127–28, 155–57
discernment, 69
Discover (magazine), 201
discovery, 217
Discovery Institute, 46
Dixon, Brendan, 212
doctrine, 217
dolphins, 165
Eden, Murray, 25
egg-hunt searches, 114–15
electron transfer chain, 170–74
embellishment problem, 49, 54
England, Jeremy, 188, 194–96
England’s equation, 194
enzymes, 35, 41–42, 81–83, 85–86, 104–7
evidence, 14
evolution: catch-22, 86; core idea, 74; Darwin on, 5; human behavior and, 55; incompetent, 230–31;
laboratory version of, 41–42; molecular control systems and, 14; personifying, 80; process of, 79–81.
See also natural selection
evolutionary biology, 74
evolutionary models, 210
evolutionary theory: critique of, 220–24; defense of by scientific organizations, 218; formal structure of,221; gaping hole in, 97, 192, 220– 21; major obstacles for, 81; natural selection and, 94; refutation of,
227; retreat from testability, 224–27; use of observation and calculation, 87–88. See also Darwinism;
evolution; natural selection
Evolution: A Theory in Crisis (Denton), 26
Ewert, Winston, 212
exhilaration, 247–49“extreme functional sensitivity”, 53

faith, 232–33
faith communities, 217
fantastic improbability, 191, 228–30, 234
feedback loop, 13
Fersht, Alan, 1–2, 41, 43, 45–46, 50–53, 57
fiddler, 103–4, 204–9
fine-tuning, 204
fluid view of life, 74–75
Fontana, Walter, 220–22
football, 88–92“Fortune” (Plutarch), 21–22
free will, 165–66, 235–36, 238, 242
functional coherence: accidental invention and, 160, 189–90; in biological systems, 178–81; hierarchicalstructure of, 143–44, 155, 157, 171, 174, 202, 233, 254; impossible coincidences and, 151–53;
invention and, 200–202; life and, 184; in models, 210; necessity of, 200; selective homing and, 214;
written instructions and, 146
gaping hole (in evolutionary theory), 97, 192, 220–21
Gauger, Ann, 81, 85
Gene (journal), 266
gene regulatory networks (GRNs), 84–85
genes, 27, 30, 271–72
genetic space, 92–93, 95
Genesis, 48
Genome Research (journal), 272
genome sequences, 93, 95, 182–83
geocachers, 248
GeoMidpoint website, 118
giant panda, 77–78
goal-directed efforts, 114
God: accidents and, 17, 193; anthropic principle and, 228–29; atheism and, 6–9; children and, 19, 185, 232,
242, 251; Dawkins-sponsored ads, 263–64; design intuition and, 253; as divine thinker, 185, 237;
evolution and, 233–34; in scientific literature, 265–66; inventions coming from mind of, 184–85; asknower who made us, 185, 235; life and, 232; outside world as expression of creative thought, 242;
personal, 245, 254–55; as product of human imagination, 6; relation to material world, 239; science and,48, 219; theist belief in, 7“The God Lab”, 51
God-like designer, 19, 55
Gopnik, Alison, 19, 62
gravity, 60
Guardian (newspaper), 52
Haeckel, Ernst, 190–91
Haise, Fred, 139
hands, 265
hat test, 196–98, 206
Hawking, Stephen, 1
Herchel Smith Professor of Organic Chemistry, 50
high view of life, 76–78
homing, 91–95, 104, 107–8, 110–11, 214

Hooker, Joseph, 17
human behavior, 9, 55, 255
human invention, 136–38
ignorance, 63
impossibility, 98–99, 117, 132–34
impossible coincidences, 151–53
innovations, 222
insight, 63, 100, 151–52, 192
instructions, 141–42, 144, 146, 154intelligent design (ID): approach, 48–49; creationism versus, 48; denouncements of, 217–19, 266; hostiletreatment by British news media, 46–47; scientific organizations and, 218–19
intent, 65–70, 88, 113, 138
Internet, 249
intuition. See design intuition
inventions: accidental invention, 14, 98–102, 160, 189–94, 196; accidents and, 160–61; Apollo 13 mailbox,
139–42, 145; as clever things, 136; coming from mind of God, 184–85; functional coherence of, 142–
43; hierarchical structure of, 143; human invention, 136–38; impossible coincidences, 151–53; language
as ultimate medium of, 141–45; life and, 11; living inventions, 176–78; materialism and, 237–38;
natural selection and, 96–97; process of conception, 142; purpose in, 160; as special things, 237–38;
top-to-bottom, 182–84
inventors, 250
iPad, 223
iPhone, 272–73
Jell-O creatures, 206–7
Journal of Molecular Biology (JMB), 36, 53
Kelemen, Deborah, 19, 62
Kendrew, John, 32
killer whales. See orcas
knowledge, 21, 42, 69–70, 145, 154, 158–60, 187, 196
Koonin, Eugene, 227, 230
laboratory case studies, 81–84, 103–10, 180–82
Laboratory of Molecular Biology (LMB), 31–33, 36, 41, 45, 51
language, 141–45, 210–14
letters, 145–51
life: Darwin’s view of, 74–77; downgrading view of, 77–79; experience and, 247–50; God and, 232; highview of, 76–78; identity of designer, 47–48; improbabilities and, 98–99; invention of new life forms,
182–84, 194–95; inventions and, 11; language and, 210–14; molecular underpinnings of, 27; asnecessary, 188; old textbook definition of, 76; origin of new categories of, 183–84; physical perfectionof, 269–70; primordial soup and, 17–18
living inventions, 176–78
logical reasonings, 243
Lovell, Jim, 139, 142
magic, 196–98“mailbox”, 139–42, 144, 145, 154
Marshall, Charles, 84–85

materialism, 6, 188, 215, 231, 237–38, 242–45, 258, 260–63
matter, 6, 238, 255–60
mechanical stage, 138
media storm, 52–54
mental stage, 137–38, 139–40
methodical stage, 138, 140
Meyer, Stephen, 84
microbiology, 191
Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost Certainly False(Nagel), 6
Mind and the Brain, The (Schwartz), 258
mind over matter, 255–60
molecular control systems, 14
molecular processes, 2
moral reasonings, 243
multiverse, 228–31
mutation, 104–7
mutations, 74, 81, 83, 273
Nagel, Thomas, 6–9, 163–64, 235, 242, 263
National Academy of Sciences, 218, 236
National Aeronautics and Space Administration (NASA), 139, 205, 207
National Center for Biotechnology Information, 227
natural cause, 244–45
natural order, 235
natural selection: common science and, 10–11; criticism of, 216–17; deficiency of theory, 220–24, 281–82;
development of mathematical theory of, 220–21; as a fiddler, 103–4; protein folds and, 81; homing
action of, 93–96; human behavior and, 55; insight and, 192; inventions and, 96–97; origin and, 3;
process of, 79–81, 88; unguided natural processes and, 195; as victim of its own success, 84–85. See
also evolution
nature, 223
Nature (journal), 45–46
neo-Darwinian theory symposium, 25–26
new school of thought, 266–73
New Scientist (magazine), 51
Newsday (newspaper), 52–53
Newton’s laws of motion, 61
nonphysical worlds, 115–17
nontechnical arguments, 59, 63–64
numbers, 125–26
objective truths, 48
observation, 87–88, 227
old school of thought, 267–69
omelet making, 158–59
open science, 62–63
oracle soup, 16–19, 26–27, 61, 87, 99, 224
orcas, 72–74, 75, 81, 165, 176, 187, 253, 264
origin: big question of, 3, 9–11; natural selection and, 3, 85–86
On the Origin of Species (Darwin), 4–5, 190

Pasteur, Louis, 191
peekaboo, 236
peer pressure, 5
penicillin, 104–7
perfection, 76–80, 269–70
periodic table of elements, 223
personhood, 242–46, 250, 255
persons, 250, 254
Perutz, Max, 32, 34, 36, 62, 273
photosynthesis, 167–75
photosystem I, 168–71
physical bodies, 239
physical impossibility, 132–34, 233–34
physical limits, 269–70
physicists, 99–100, 152
physics, 238
pin drops, 118–21, 129–30
pixels, 123–25, 127–28, 155–57, 201
PLoS One (journal), 265
Plutarch, 21
pool robots, 66–70
possibility of physical impossibility, 132–34, 233–34
practical know-how knowledge, 21
primordial soup, 17–18, 87
principle of reciprocal scale, 130, 131, 155protein evolution, 43
protein folds, 81, 180, 182
proteins, 27–31, 57, 81–86, 104–10, 179–82, 261
public opinion, 62
purpose, 19, 174, 244, 261
rabbit trick, 196
rain, 67
random mutations, 83
random typing, 147–51, 202
reality: categories of, 237–42; principle for our understanding of, 231–32
reason, 232, 241reasoning, 241, 243
reciprocal scale, 129–30
Reeves, Mariclair, 81, 85
reflection, 253religion, 54
repetition, 91–92, 101–2
reproducers, 74
Rice University, 194
robotic football fans, 88–92
Rosenberg, Paul, 188
Royal Astronomical Society of Canada, 218
Royal Society of London, 218, 236

salmon, 72–74, 75, 165, 176
Sanger, Fred, 32, 240
Santa Fe Institute, 220
Schützenberger, Marcel, 25
Schwartz, Jeffrey, 258
science: acceptance of essential propositions, 232–33; authoritarian science, 40; claims of helpful
coincidences, 97–98; common science, 10–11; embellishment problem, 49, 54; existence of God, 232;
experience and, 247–48; faith and, 232–33; open science, 62–63; role of observation in, 241–42;
scientific method, 37, 48–49; scientific proof, 45; technical/nontechnical arguments and, 59; utopian
science, 37, 39–40, 44
scientific communities, 217
scientific discourse, 224
scientific facts, 59
scientific organizations, 218
scientific thinking, 254
scientism, 7, 49, 231, 242
scientists, 60–61, 254
searches: blind searches, 115, 135–36; coverage principle, 119–22; cuna search, 117–18; egg-hunt searches,
114–15; fantastically big numbers, 125–26; gauging difficulty of very hard searches, 130–32;
multiverse, 229; nonphysical worlds, 115–17; possibility of physical impossibility, 132–34; spaces ofsurreal size, 122–25
search for extraterrestrial intelligence (SETI), 44–45
search target, 117
Seattle Seahawks, 89
Selection: The Mechanism of Evolution (Bell), 96
selective optimization, 204–5, 207, 208
significance, 92, 96, 261–62
skepticism, 17–18, 30–31, 38, 43, 62–63, 101–2, 231–32
skilled work, 69
software developers, 223
spaces of surreal size, 122–25
Spaulding, Sarah, 246
Species and Varieties: Their Origin by Mutation (De Vries), 220
species-specific genes, 183
spiders, 66–68, 75, 88, 165, 176, 187, 237, 253
sponges, 80, 81
Stephen Biesty’s Incredible Cross-Sections (Platt & Biesty), 168
stepping stones, 97–98, 109–10, 151, 193–94, 200, 203
storage tube investigation, 45–46
storytelling experiment, 16
Stylus computational tool, 210–14
subprojects, 70
sugar, 168, 175
Super Bowl XLVIII, 89
Swigert, Jack, 139
Tavros 2, 165, 166, 167, 175
Tawfik, Dan, 85
technical arguments, 59
tennis player, 70–71, 142–43

testability, 224–27
theism, 7–8
thermodynamics, 188
thermostats, 13
things, 237–38
thinkers, 237–38, 250
thought experiment, 239–40, 258
thoughts, 237–38, 258–59
thylakoid membrane, 174
Tour, Jim, 194, 196
truth, 48–49, 63–64, 228, 241, 251
tryptophan, 108–10
Turing, Alan, 255–56
Turing machine, 256–57, 273
two roads, 260–63
Tyson, Neil deGrasse, 37, 39
Ulam, Stanislaw, 25
unassisted searches, 115
understanding, 15
underwater vehicle, 165
universal design intuition. See design intuition
universe, 227–31
University of South Florida, 165
University of Wisconsin– Superior, 108
University of Wyoming, 206
U.S. Geological Survey, 246
utopian science, 37, 44
van Leeuwenhoek, Antonie, 191
vector chains, 212–14
Wagner, Andreas, 222–23
Watson, James, 32
Weizmann Institute, 85
whole projects, 68–71, 158–59, 176
wholes, 67–71, 76, 176
Wikipedia, 217
wine, 263–64
words, 153–55“wow factor”, 65
written language, 144, 210–12
Zuckerkandl, Emile, 266

COLOR PLATES

Plate 1 The visual effects of bottom-level pixel coherence and incoherence. To avoid compression artifacts,
uncompressed TIFF files were used for all photos.

Plate 2 A random image (left) and a nonrandom image (right), obtained by processing the first image with
the Mathematica commands ImageResize and Colorize.

Plate 3 Fish by genre. Top row: Merlet’s scorpionfish (Rhinopias aphanes) and mandarinfish (Synchiropus
splendidus). Second row: Siamese fighting fish (Betta splendens). Third row: fringehead fish (Neoclinus
blanchardi) and red-lipped batfish (Ogcocephalus darwini). Bottom row: giant stargazer (Kathetostoma
giganteum) and fangtooth (Anoplogaster cornuta). Unlike the other fish shown, the Siamese fighting fish
have been bred in captivity in order to bring out their full potential. Because of this, some may say they’reless compelling as a demonstration of the emotional connection between us, their observers, and God, theircreator. To me this only makes them more compelling, in that it seems we’ve been invited to participate, ina very small way, in the creative process itself.
Merlet’s scorpionfish, Georgette Douwma/Science Photo Library; mandarinfish, Dollar Photo Club © Olga
Khoroshunova; Siamese fighting fish, © visarute angkatavanich / 500px; fringehead fish, Chris
Newbert/Minden Pictures/National Geographic Creative; red-lipped batfish, NatalieJean/Shutterstock; giant
stargazer, Joe Belanger/Shutterstock; fangtooth, Dante Fenolio/Science Photo Library.

ABOUT THE AUTHORDOUGLAS AXE, Ph.D., is the director of Biologic Institute, a nonprofit
research organization launched by Discovery Institute in Seattle. After his
undergraduate studies at U. C. Berkeley and doctoral work at Caltech, he held
postdoctoral and research scientist positions at the University of Cambridge, theCambridge Medical Research Council Centre, and the Babraham Institute in
Cambridge. His work and ideas have been featured in many scientific journals,
including the Journal of Molecular Biology, the Proceedings of the National
Academy of Sciences, and Nature, and in such books as Signature in the Cell andDarwin’s Doubt by Stephen C. Meyer and Life’s Solution by Simon Conway
Morris.
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COPYRIGHT

Pages 289–90 constitute a continuation of this copyright page.
UNDENIABLE. Copyright © 2016 by Douglas Axe. All rights reserved under International and PanAmerican Copyright Conventions. By payment of the required fees, you have been granted thenonexclusive, nontransferable right to access and read the text of this e-book on-screen. No part of this text
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into any information storage and retrieval system, in any form or by any means, whether electronic ormechanical, now known or hereafter invented, without the express written permission of HarperCollins ebooks.
FIRST EDITION
Illustrations credits on pages 289–90.
ISBN 978–0–06–234958–3
EPub Edition May 2016 ISBN 9780062349606
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