trentmkelly/LessWrong-43k huggingface dataset:
Knowledge ready for Ankification
by lukeprog — 2012-02-02T18:58:54.021Z

Spaced repetition is a powerful learning tactic, and Anki is a good tool for it. There are some LW-relevant Anki decks here. But I wish there were more.

Which sets of knowledge are (1) likely useful to LWers, and (2) straightforward to encode into Anki decks without needing to be familiar with that field?

Some examples:

Purves et al.'s glossary of cognitive neuroscience (preferably including a brain-image for each brain anatomy term).

The meaning of each concept in the LW wiki.

The meaning of each bolded term in AIMA.

Which other sets of knowledge would you like to see Ankified? Please link to the actual knowledge set you'd like to see encoded.
Two Kinds of Irrationality and How to Avoid One of Them
by ChrisHallquist — 2012-02-02T18:13:08.743Z

It seems to me that there are two kinds of human irrationality. One could be called "bug" irrationality, not referring to insects but rather bugs in the design of our minds, ways in which our minds could be better designed. This category includes things like hyperbolic discounting (also called myopic discounting), as well as general failures to correctly apply laws of logic and probability. It's often worth making an effort to correct for this kind of irrationality, but I think some of the discussion of it is overly pessimistic. From an evolutionary point of view, the main reason that this kind of irrationality exists is probably just that flawed rules of thumb which usually work out okay can be more efficient than more rigorous methods.

As Yvain once wrote, "most people are rational enough for their own purposes." Because of that, I don't think this kind of rationality is our biggest worry, and it's not what this post is about. But if you want to do much more reading on the view of this side of irrationality that I've just sketched, I recommend reading various papers by psychologist Ricard Samuels and philosopher Stephen Stich, such as Ending the Rationality Wars, Rationality & Psychology, and Reason and Rationality.

The worst examples of human irrationality, in my view, are what could be called "feature" irrationality. Meaning, when irrationality is a feature of our mind, something evolution designed into our minds. Why would evolution do this? Here is Stephen Pinker's explanation from How the Mind Works:

[Psychologist Robert] Trivers, pursuing his theory of the emotions to its logical conclusion, notes that in a world of walking lie detectors the best strategy is to believe your own lies...

Everyone has heard of "reducing cognitive dissonance," in which people invent a new opinion to resolve a contradiction in their minds. For example, a person will recall enjoying a boring task if he had agreed to recommend it to others for paltry pay... As originally conceived of by the psychologist Leon Festinger, cognitive dissonance is an unsettled feeling that arises from an inconsistency in one's beliefs. But that's not right: there is no contradiction between the proposition "The task is boring" and the proposition "I was pressured into lying that the task was fun." Another social psychologist, Eliot Aronson, nailed it down: people doctor their beliefs only to e

...
Teaching rationality made me better (at research and other things)
by Academian — 2012-02-02T18:10:06.463Z

Hi all,

I just wanted to loudly recommend the position to design and write rationality curriculum --- to anyone who is interested --- as a potential way to make yourself more awesome. After helping teach mini-camp last year, I definitely experienced a huge increase in motivation for my own research, and in turn, productivity. Somehow, giving serious thought to rationality advice for a large group and *actually delivering it* made be internalize even more deeply some things I thought I'd already absorbed completely.

... and my sense that more is possible is still tingling :)

So yeah, definitely give it a shot if you think you might be good at it!
Looking for information on cryonics
by Metus — 2012-02-02T12:33:02.181Z

Disclaimer: English is a foreign language for me. If you find any mistakes please inform me.

I am currently looking for information on cryonics since I have the intention to sign up. My current organization of choice is the Cryonics Institute with their one-time fee of $1,250 at sign-up and $28,000 for cryo-preservation which is an excellent offer given my age. I understand that most people choose to pay for cryopreservation by life-insurance. Since the cost of cryopreservation is lower than the €30,000 most insurers here in Germany take as minimum payout I still would have money left and wonder if I could put this money in some kind of trust to pay for "revival" and have some money in that future. Do any of you have plans like that and could share their information?

Also, do I understand correctly that the $28,000 at the Cryonics Institute are for cryopreservation only and that $88,000 figure is for cryopreservation, standby and transport to Michigan? In that case I of course need to get life insurance with higher pay-out but at my age that should not be a problem.

Are there any other institutes that offer cryopreservation of at least the brain that I should consider? I know of Alcor (expensive, I do not see the benefits) and KryoRus (seems cheap and require continuous funding that could be handled by a trust fund). Are there more I should know of?

If you have ideas, information I should consider or question I need to have answered, please feel free to reply in the comments.
On Saying the Obvious
by Grognor — 2012-02-02T05:13:43.030Z

Related to: Generalizing from One Example, Connecting Your Beliefs (a call for help), Beware the Unsurprised

The idea of this article is something I've talked about a couple of times in comments. It seems to require more attention.

As a general rule, what is obvious to some people may not be obvious to others. Is this obvious to you? Maybe it was. Maybe it wasn't, and you thought it was because of hindsight bias.

Imagine a substantive Less Wrong comment. It's insightful, polite, easy to understand, and otherwise good. Ideally, you upvote this comment. Now imagine the same comment, only with "obviously" in front. This shouldn't change much, but it does. This word seems to change the comment in multifarious bad ways that I'd rather not try to list.

Uncharitably, I might reduce this whole phenomenon to an example of a mind projection fallacy. The implicit deduction goes like this: "I found <concept> obvious. Thus, <concept> is inherently obvious." The problem is that obviousness, like probability, is in the mind.

The stigma of "obvious" ideas has another problem in preventing things from being said at all. I don't know how common this is, but I've actually been afraid of saying things that I thought were obvious, even though ignoring this fear and just posting has yet to result in a poorly-received comment. (That is, in fact, why I'm writing this.)

Even tautologies, which are always obvious in retrospect, can be hard to spot. How many of us would have explicitly realized the weak anthropic principle without Nick Bostrom's help?

And what about implications of beliefs you already hold? These should be obvious, and sometimes are, but our brains are notoriously bad at putting two and two together. Luke's example was not realizing that an intelligence explosion was imminent until he read the I.J. Good paragraph. I'm glad he provided that example, as it has saved me the trouble of making one.

This is not (to paraphrase Eliezer) a thunderbolt of insight. I bring it up because I propose a few community norms based on the idea:

Don't be afraid of saying something because it's "obvious". It's like how your teachers always said there are no stupid questions.

Don't burden your awesome ideas with "obvious but it needs to be said".

Don't vote down a comment because it says something "obvious" unless you've thought about it for a while. Also, don't shun "obvious" ideas.

...
[SEQ RERUN] Categorizing Has Consequences
by MinibearRex — 2012-02-02T04:45:26.260Z

Today's post, Categorizing Has Consequences was originally published on 19 February 2008. A summary (taken from the LW wiki):

You see patterns where none exist, harvesting other characteristics from your definitions even when there is no similarity along that dimension. In Japan, it is thought that people of blood type A are earnest and creative, blood type Bs are wild and cheerful, blood type Os are agreeable and sociable, and blood type ABs are cool and controlled.

Discuss the post here (rather than in the comments to the original post).
This post is part of the Rerunning the Sequences series, where we'll be going through Eliezer Yudkowsky's old posts in order so that people who are interested can (re-)read and discuss them. The previous post was Fallacies of Compression, and you can use the sequence_reruns tag or rss feed to follow the rest of the series.
Sequence reruns are a community-driven effort. You can participate by re-reading the sequence post, discussing it here, posting the next day's sequence reruns post, or summarizing forthcoming articles on the wiki. Go here for more details, or to have meta discussions about the Rerunning the Sequences series.
Mini-Review: 'The Oxford Handbook of Philosophy of Cognitive Science'
by lukeprog — 2012-02-01T21:48:11.562Z

Today I had the pleasure of wading through Oxford's new Handbook of Philosophy of Cognitive Science. The book consists of review chapters on the following topics:

Cognition (computationalism vs. embodied cognition, mental representation)

Consciousness

The nature of thought (concepts, language and thought)

Specific mental phenomena (perception, attention, emotions)

Meta-theoretic issues (the assumptions of cognitive science, relationships between disciplines)

Conceptual issues (the relation between concepts used by psychology, neuroscience, and philosophy)

First-order empirical issues (theory of mind, language, culture and cognition)

Traditional philosophical issues (rationality, metaphilosophy)

Below, I'll summarize a few of the chapters I found most useful and interesting.

In "Consciousness and Cognition," Robert van Gulick begins by listing 10 different things that is often meant by the term "consciousness." He then explains that some regard consciousness as more basic than cognition, while others see consciousness as dependent on cognition. (I take the latter view.) Van Gulick then surveys three main categories of theories of consciousness: philosophical theories (including Dennett's "multiple drafts" theory), cognitive theories (including Baars' "global workspace" theory and Tononi's information integration theory), and neurobiological theories (including Dehaene & Naccache's neuronal version of global workspace theory and Lamme's "local recurrence" model). Van Gulick concludes by surveying some of the methods used in consciousness studies.

In "Embodied Cognition," Lawrence Shaprio attempts to explain the difference between computational and embodied theories of cognition. Computational theorists treat the mind as a computational system, and seek to infer the algorithms by which the mind transforms inputs into outputs. (I'll add that at some level of organization this must be true, for physics appears to be computational and the mind runs on physics.) And what do embodied theories claim?

After reading the chapter, I remain confused as to how embodied approaches are supposed to be non-computational. For example, Shapiro quotes Ester Thelen explaining embodied cognition this way: "...to say that cognition is embodied means that it arises from bodily interactions with the world [and] depends on the kinds of experiences that come from havin...
Rationality Quotes February 2012
by  — 2012-02-01T21:03:56.231Z

Here's the new thread for posting quotes, with the usual rules:

Please post all quotes separately, so that they can be voted up/down separately. (If they are strongly related, reply to your own comments. If strongly ordered, then go ahead and post them together.)

Do not quote yourself.

Do not quote comments/posts on LW/OB.

No more than 5 quotes per person per monthly thread, please.
Automatic programming, an example
by Thomas — 2012-02-01T20:55:18.448Z

Say, that we have the following observational data:

Planet
Aphelion
000 km
Perihelion
000 km
Orbit time
days

Mercury
69,816
46,001
88

Venus
108,942
107,476
225

Earth
152,098
147,098
365

Mars
249,209
206,669
687

Jupiter
816,520
740,573
4,332

Saturn
1,513,325
1,353,572
10,760

Uranus
3,004,419
2,748,938
30,799

Neptune
4,553,946
4,452,940
60,190

Pluto
7,311,000
4,437,000
90,613

The minimal, the maximal distance between a planet and the Sun (both in thousands of kilometres) and the number of (Earth) days for one revolution around the Sun. Above is only the empirical data and no binding algorithm among the three quantities. The celestial mechanics rules which go by the name of the Kepler's laws. Can those rules be (re)invented by a computer program and how?

The following program code will be put into a simulator:

//declarations of the integer type variables
$DECLAREINT bad perihelion aphelion orbit guess dif temp zero temp1

//table with the known data in a simulator friendly format
$INVAR perihelion(46001) aphelion(69816) orbit(88)
$INVAR perihelion(107476) aphelion(108942) orbit(225)
$INVAR perihelion(147098) aphelion(152098) orbit(365)
$INVAR perihelion(206669) aphelion(249209) orbit(687)
$INVAR perihelion(740573) aphelion(816520) orbit(4332)
$INVAR perihelion(1353572) aphelion(1513325) orbit(10760)
$INVAR perihelion(2748938) aphelion(3004419) orbit(30799)
$INVAR perihelion(4452940) aphelion(4553946) orbit(60190)
$INVAR perihelion(4437000) aphelion(7311000) orbit(90613)

// variables orbit and bad can't be touched by the simulator
//to avoid a degeneration to a triviality
$RESVAR orbit bad

//do NOT use if clause, while clause do not set direct numbers ...
$RESCOM if while val_operation inc_dec

//bad is the variable, by which the whole program will be judged
//a big value of bad is bad. By this criteria programs will be wiped out
//from their virtual existence. A kind of anti-fitness
$PENVAL bad

//do show the following variables when simulating
$SHOWVAR bad,orbit,guess,dif

//penalize any command with 0 (nothing) and every line by 1 point
$WEIGHTS commands=0 lines=1

//minimize the whole program to 20 lines or less
$MINIMIZE lines 20

$BES

//the arena, where algorithms will be
//created and the fittest only will survive

$EES

//testing area where the simulator has no write access to
//here the bad (the penalized variable) is calculated
//bigger th

...
Mini-review: 'Proving History: Bayes' Theorem and the Quest for the Historical Jesus'
by lukeprog — 2012-02-01T19:20:19.988Z

I recently received an advance review copy of historian and philosopher Richard Carrier's new book, Proving History: Bayes' Theorem and the Quest for the Historical Jesus.

The book belongs to a two-volume work on the Historical Jesus that argues for two major claims:

Correct historical method is Bayesian. (The first book.)

The application of this method to our data concerning the Historical Jesus strongly suggests that Jesus never existed. (The second book.)

Claim #1 might provoke a yawning "Yes, of course..." from many scientists and philosophers, but both claims are currently heretical in the field of Jesus Studies, which shows many signs of being an unsound research program in general. The book is written for a mass audience, but is also aimed at historians in general. It is, as far as I know, the first book to lay out the detailed case for why historians should be using Bayesian methods. (For an overview of the other methods historians typically use, see Justifying Historical Descriptions.)

Though the Bayesian revolution of the sciences has already slammed into archaeology and a few other fields of historical inquiry, it has not yet overwhelmed mainstream historical inquiry. Carrier's book may be seen as the first salvo in that attack, but this makes me wish his case had not been presented in the context of such a parochial and disreputable sub-field of history as Jesus Studies. No chapter in the book discusses the evidence concerning the historicity of Jesus in much detail, and it clearly isn't necessary to make Carrier's points, so why poison the presentation of such a clear and powerful case (in favor of Bayesian historical methods) by marinating it in such a disreputable field (Jesus Studies), and with anticipation of a startling conclusion almost everyone disagrees with (Jesus myth theory)? (For the record, I take Jesus myth theory pretty seriously, but most people don't.)

Chapter 3 is a tutorial on Bayes' Theorem, similar to Carrier's Skepticon IV talk. Chapter 4 provides an analysis of non-Bayesian methods of historical analysis, showing that they are wrong in exactly the degree to which they depart from the Bayesian method. Chapter 5 provides a similar analysis of typical "Historicity Criteria" used in Jesus Studies, e.g. "multiple attestation." The final chapter tackles some more detailed issues with the application of Bayes' Theorem, for ex...
von Neumann probes and Dyson spheres: what exploratory engineering can tell us about the Fermi paradox
by Stuart_Armstrong — 2012-02-01T13:50:56.712Z

Not entirely relevant to the main issues of lesswrong, but possibly still of interest: my talk entitled "von Neumann probes and Dyson spheres: what exploratory engineering can tell us about the Fermi paradox".

Abstract: The Fermi paradox is the contrast between the high estimate of the likelihood of extraterritorial civilizations, and the lack of visible evidence of them. But what sort of evidence should we expect to see? This is what exploratory engineering can tell us, giving us estimates of what kind of cosmic structures are plausibly constructable by advanced civilizations, and what traces they would leave. Based on our current knowledge, it seems that it would be easy for such a civilization to rapidly occupy vast swathes of the universe in a visible fashion. There are game-theoretic reasons to suppose that they would do so. This leads to a worsening of the Fermi paradox, reducing the likelihood of "advanced but unseen" civilizations, even in other galaxies.

The slides from the talk can be found here (thanks, Luke!).
[Link] Reconstructing Speech from Human Auditory Cortex
by  — 2012-02-01T12:50:59.681Z

Link to full paper.

Abstract (emphasis mine):

How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acoustic information in speech sounds can be reconstructed from population neural activity. We found that slow and intermediate temporal fluctuations, such as those corresponding to syllable rate, were accurately reconstructed using a linear model based on the auditory spectrogram. However, reconstruction of fast temporal fluctuations, such as syllable onsets and offsets, required a nonlinear sound representation based on temporal modulation energy. Reconstruction accuracy was highest within the range of spectro-temporal fluctuations that have been found to be critical for speech intelligibility. The decoded speech representations allowed readout and identification of individual words directly from brain activity during single trial sound presentations. These findings reveal neural encoding mechanisms of speech acoustic parameters in higher order human auditory cortex.
Deciding what to think about; is it worthwhile to have universal utility function?
by Dmytry — 2012-02-01T09:44:20.543Z

The hunter-gatherer example in the Is risk aversion really irrational? got me thinking about the real world issues with 'maximizing utility' and any other simple rule approach to decision making.

The elephant in the room is that universal, effective utility of anything could be very expensive to calculate if you employ any foresight (consider thinking several moves ahead). And once you start estimating utility in different ways depending to the domain, the agent's behaviour stops being consistent with plain utility maximization. At same time, the solution space of the problems is often very big, meaning that you have immense number of potential choices and you need to perform a lot of utility estimations really quickly to pick the best solution. Think of Chess or Go. The computing time could be better spent elsewhere.

The hunter-gatherer in example can think about the traps and other hunting tools and invent a new one, instead of trying to figure out probability theory or something of this kind.

Inventing a new trap is a case where the number of potential decisions is extremely huge.

I faintly recall a fiction story I've read where a smart boy becomes tribe leader - by inventing a better bear trap, not so much by being utterly rational at correctly processing small differences in expected utility when it comes to bets.

He can also think more about berries and look if there's evidence that other mammals are eating those berries; some plant that is not poisonous to other mammal is very unlikely to hurt a human; some plant that is not eaten by other mammals is very likely to be poisonous to humans as well. He can even feed the berries to some mammal he'd keep alive (i'd imagine keeping animals alive was a fairly straightforward approach to meat preservation).

At the same time, even if that hunter gatherer knew enough math to try to formally calculate his odds, the probabilities are unknown. Indeed there are probability distributions for different degrees of getting sick of berries or not (and different symptoms of sickness), et cetera. We today are just beginning to think how to improve his odds using formal mathematics, and we're still not sure how to accomplish that, and it is clear that it is going to be very computationally intensive.

As a singular example, I can easily come up with good solutions for that hunter-gatherer by looking into the big solution space tha...