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shubhamg2208
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lexicap

	WEBVTT

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	You've studied the human mind, cognition, language, vision, evolution, psychology, from child to adult,

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	from the level of individual to the level of our entire civilization,

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	so I feel like I can start with a simple multiple choice question.

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	What is the meaning of life? Is it A, to attain knowledge, as Plato said,

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	B, to attain power, as Nietzsche said, C, to escape death, as Ernest Becker said,

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	D, to propagate our genes, as Darwin and others have said, E, there is no meaning,

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	as the nihilists have said, F, knowing the meaning of life is beyond our cognitive capabilities,

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	as Stephen Pinker said, based on my interpretation 20 years ago, and G, none of the above.

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	I'd say A comes closest, but I would amend that to attaining not only knowledge, but fulfillment

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	more generally. That is, life, health, stimulation, access to the living cultural and social world.

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	Now, this is our meaning of life. It's not the meaning of life, if you were to ask our genes.

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	Their meaning is to propagate copies of themselves, but that is distinct from the

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	meaning that the brain that they lead to sets for itself. So, to you, knowledge is a small subset

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	or a large subset? It's a large subset, but it's not the entirety of human striving, because we

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	also want to interact with people. We want to experience beauty. We want to experience the

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	richness of the natural world, but understanding what makes the universe tick is way up there.

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	For some of us more than others, certainly for me, that's one of the top five.

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	So, is that a fundamental aspect? Are you just describing your own preference, or is this a

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	fundamental aspect of human nature, is to seek knowledge? In your latest book, you talk about

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	the power, the usefulness of rationality and reason and so on. Is that a fundamental

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	nature of human beings, or is it something we should just strive for?

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	Both. We're capable of striving for it, because it is one of the things that

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	make us what we are, homo sapiens, wise men. We are unusual among our animals in the degree to

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	which we acquire knowledge and use it to survive. We make tools. We strike agreements via language.

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	We extract poisons. We predict the behavior of animals. We try to get at the workings of plants.

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	And when I say we, I don't just mean we in the modern west, but we as a species everywhere,

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	which is how we've managed to occupy every niche on the planet, how we've managed to drive other

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	animals to extinction. And the refinement of reason in pursuit of human well being, of health,

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	happiness, social richness, cultural richness, is our main challenge in the present. That is,

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	using our intellect, using our knowledge to figure out how the world works, how we work,

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	in order to make discoveries and strike agreements that make us all better off in the long run.

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	Right. And you do that almost undeniably in a data driven way in your recent book,

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	but I'd like to focus on the artificial intelligence aspect of things, and not just

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	artificial intelligence, but natural intelligence too. So 20 years ago in the book, you've written

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	on how the mind works, you conjecture, again, am I right to interpret things? You can correct me

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	if I'm wrong, but you conjecture that human thought in the brain may be a result of a network, a massive

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	network of highly interconnected neurons. So from this interconnectivity emerges thought,

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	compared to artificial neural networks, which we use for machine learning today,

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	is there something fundamentally more complex, mysterious, even magical about the biological

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	neural networks versus the ones we've been starting to use over the past 60 years and

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	become to success in the past 10? There is something a little bit mysterious about

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	the human neural networks, which is that each one of us who is a neural network knows that we

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	ourselves are conscious, conscious not in the sense of registering our surroundings or even

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	registering our internal state, but in having subjective first person, present tense experience.

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	That is, when I see red, it's not just different from green, but there's a redness to it that I

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	feel. Whether an artificial system would experience that or not, I don't know and I don't think I

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	can know. That's why it's mysterious. If we had a perfectly lifelike robot that was behaviorally

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	indistinguishable from a human, would we attribute consciousness to it or ought we to attribute

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	consciousness to it? And that's something that it's very hard to know. But putting that aside,

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	putting aside that largely philosophical question, the question is, is there some difference between

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	the human neural network and the ones that we're building in artificial intelligence will mean that

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	we're on the current trajectory not going to reach the point where we've got a lifelike robot

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	indistinguishable from a human because the way their so called neural networks are organized

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	are different from the way ours are organized. I think there's overlap, but I think there are some

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	big differences that their current neural networks, current so called deep learning systems are in

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	reality not all that deep. That is, they are very good at extracting high order statistical

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	regularities. But most of the systems don't have a semantic level, a level of actual understanding

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	of who did what to whom, why, where, how things work, what causes, what else.

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	Do you think that kind of thing can emerge as it does so artificial neural networks are much

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	smaller the number of connections and so on than the current human biological networks? But do you

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	think sort of go to consciousness or to go to this higher level semantic reasoning about things?

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	Do you think that can emerge with just a larger network with a more richly, weirdly interconnected

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	network? Separate it in consciousness because consciousness is even a matter of complexity.

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	A really weird one. Yeah, you could sensibly ask the question of whether shrimp are conscious,

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	for example. They're not terribly complex, but maybe they feel pain. So let's just put that

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	part of it aside. But I think sheer size of a neural network is not enough to give it

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	structure and knowledge. But if it's suitably engineered, then why not? That is, we're neural

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	networks. Natural selection did a kind of equivalent of engineering of our brains. So I don't think

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	there's anything mysterious in the sense that no systemated of silicon could ever do what a human

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	brain can do. I think it's possible in principle. Whether it'll ever happen depends not only on

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	how clever we are in engineering these systems, but whether even we even want to, whether that's

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	even a sensible goal. That is, you can ask the question, is there any locomotion system that is

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	as good as a human? Well, we kind of want to do better than a human ultimately in terms of

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	legged locomotion. There's no reason that humans should be our benchmark. They're tools that might

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	be better in some ways. It may be that we can't duplicate a natural system because at some point,

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	it's so much cheaper to use a natural system that we're not going to invest more brain power

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	and resources. So for example, we don't really have an exact substitute for wood. We still build

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	houses out of wood. We still build furniture out of wood. We like the look. We like the feel. It's

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	wood has certain properties that synthetics don't. There's not that there's anything magical or

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	mysterious about wood. It's just that the extra steps of duplicating everything about wood is

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	something we just haven't bothered because we have wood. Likewise, cotton. I'm wearing cotton

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	clothing now. It feels much better than polyester. It's not that cotton has something magic in it,

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	and it's not that we couldn't ever synthesize something exactly like cotton,

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	but at some point, it's just not worth it. We've got cotton. Likewise, in the case of human

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	intelligence, the goal of making an artificial system that is exactly like the human brain

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	is a goal that we probably know is going to pursue to the bitter end, I suspect, because

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	if you want tools that do things better than humans, you're not going to care whether it

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	does something like humans. So for example, diagnosing cancer or predicting the weather,

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	why set humans as your benchmark? But in general, I suspect you also believe that even if the human

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	should not be a benchmark and we don't want to imitate humans in their system, there's a lot

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	to be learned about how to create an artificial intelligence system by studying the humans.

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	Yeah, I think that's right. In the same way that to build flying machines, we want to understand

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	the laws of aerodynamics, including birds, but not mimic the birds, but they're the same laws.

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	You have a view on AI, artificial intelligence and safety, that from my perspective,

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	is refreshingly rational, or perhaps more importantly, has elements of positivity to it,

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	which I think can be inspiring and empowering as opposed to paralyzing. For many people,

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	including AI researchers, the eventual existential threat of AI is obvious, not only possible but

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	obvious. And for many others, including AI researchers, the threat is not obvious. So

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	Elon Musk is famously in the highly concerned about AI camp, saying things like AI is far

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	more dangerous than nuclear weapons, and that AI will likely destroy human civilization.

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	So in February, you said that if Elon was really serious about AI, the threat of AI,

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	he would stop building self driving cars that he's doing very successfully as part of Tesla.

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	Then he said, wow, if even Pinker doesn't understand the difference between narrow AI

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	like a car and general AI, when the latter literally has a million times more compute power

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	and an open ended utility function, humanity is in deep trouble. So first, what did you mean by

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	the statement about Elon Musk should stop building self driving cars if he's deeply concerned?

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	Well, not the last time that Elon Musk has fired off an intemperate tweet.

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	Well, we live in a world where Twitter has power.

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	Yes. Yeah, I think there are two kinds of existential threat that have been discussed

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	in connection with artificial intelligence, and I think that they're both incoherent.

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	One of them is a vague fear of AI takeover, that just as we subjugated animals and less

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	technologically advanced peoples, so if we build something that's more advanced than us,

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	it will inevitably turn us into pets or slaves or domesticated animal equivalents.

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	I think this confuses intelligence with a will to power that it so happens that in the

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	intelligence system we are most familiar with, namely Homo sapiens, we are products of natural

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	selection, which is a competitive process. And so bundled together with our problem solving

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	capacity are a number of nasty traits like dominance and exploitation and maximization of

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	power and glory and resources and influence. There's no reason to think that sheer problem

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	solving capability will set that as one of its goals. Its goals will be whatever we set its goals

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	as, and as long as someone isn't building a megalomaniacal artificial intelligence,

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	then there's no reason to think that it would naturally evolve in that direction.

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	Now you might say, well, what if we gave it the goal of maximizing its own power source?

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	That's a pretty stupid goal to give an autonomous system. You don't give it that goal.

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	I mean, that's just self evidently idiotic. So if you look at the history of the world,

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	there's been a lot of opportunities where engineers could instill in a system destructive

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	power and they choose not to because that's the natural process of engineering.

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	Well, except for weapons. I mean, if you're building a weapon, its goal is to destroy

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	people. And so I think there are good reasons to not build certain kinds of weapons. I think

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	building nuclear weapons was a massive mistake. You do. So maybe pause on that because that is

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	one of the serious threats. Do you think that it was a mistake in a sense that it should have been

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	stopped early on? Or do you think it's just an unfortunate event of invention that this was

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	invented? Do you think it's possible to stop, I guess, is the question on that? Yeah, it's hard to

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	rewind the clock because, of course, it was invented in the context of World War II and the

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	fear that the Nazis might develop one first. Then once it was initiated for that reason,

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	it was hard to turn off, especially since winning the war against the Japanese and the Nazis was

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	such an overwhelming goal of every responsible person that they were just nothing that people

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	wouldn't have done then to ensure victory. It's quite possible if World War II hadn't happened

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	that nuclear weapons wouldn't have been invented. We can't know. But I don't think it was, by any

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	means, a necessity any more than some of the other weapon systems that were envisioned but never

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	implemented, like planes that would disperse poison gas over cities like crop dusters or systems to

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	try to create earthquakes and tsunamis in enemy countries, to weaponize the weather,

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	weaponize solar flares, all kinds of crazy schemes that we thought the better of. I think

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	analogies between nuclear weapons and artificial intelligence are fundamentally misguided because

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	the whole point of nuclear weapons is to destroy things. The point of artificial intelligence

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	is not to destroy things. So the analogy is misleading. So there's two artificial

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	intelligence you mentioned. The first one was the highly intelligent or power hungry. Yeah,

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	an assistant that we design ourselves where we give it the goals. Goals are external to the

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	means to attain the goals. If we don't design an artificially intelligent system to maximize

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	dominance, then it won't maximize dominance. It's just that we're so familiar with homo sapiens

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	where these two traits come bundled together, particularly in men, that we are apt to confuse

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	high intelligence with a will to power. But that's just an error. The other fear is that

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	we'll be collateral damage that will give artificial intelligence a goal like make paper clips

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	and it will pursue that goal so brilliantly that before we can stop it, it turns us into paper

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	clips. We'll give it the goal of curing cancer and it will turn us into guinea pigs for lethal

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	experiments or give it the goal of world peace and its conception of world peace is no people,

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	therefore no fighting and so it will kill us all. Now, I think these are utterly fanciful. In fact,

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	I think they're actually self defeating. They first of all assume that we're going to be so

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	brilliant that we can design an artificial intelligence that can cure cancer. But so stupid

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	that we don't specify what we mean by curing cancer in enough detail that it won't kill us in the

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	process. And it assumes that the system will be so smart that it can cure cancer. But so

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	idiotic that it doesn't can't figure out that what we mean by curing cancer is not killing

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	everyone. So I think that the collateral damage scenario, the value alignment problem is also

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	based on a misconception. So one of the challenges, of course, we don't know how to build either system

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	currently, or are we even close to knowing? Of course, those things can change overnight,

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	but at this time, theorizing about is very challenging in either direction. So that's

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	probably at the core of the problem is without that ability to reason about the real engineering

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	things here at hand is your imagination runs away with things. Exactly. But let me sort of ask,

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	what do you think was the motivation, the thought process of Elon Musk? I build autonomous vehicles,

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	I study autonomous vehicles, I study Tesla autopilot. I think it is one of the greatest

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	currently application, large scale application of artificial intelligence in the world.

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	It has a potentially very positive impact on society. So how does a person who's creating this

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	very good, quote unquote, narrow AI system also seem to be so concerned about this other

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	general AI? What do you think is the motivation there? What do you think is the thing?

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	Well, you probably have to ask him, but there and he is notoriously flamboyant, impulsive to the,

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	as we have just seen, to the detriment of his own goals of the health of a company.

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	So I don't know what's going on in his mind. You probably have to ask him. But I don't think the,

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	and I don't think the distinction between special purpose AI and so called general AI is relevant

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	that in the same way that special purpose AI is not going to do anything conceivable in order to

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	attain a goal, all engineering systems have to are designed to trade off across multiple goals.

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	When we build cars in the first place, we didn't forget to install brakes because the goal of a

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	car is to go fast. It occurred to people, yes, you want to go fast, but not always. So you build

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	and brakes too. Likewise, if a car is going to be autonomous, that doesn't program it to take the

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	shortest route to the airport. It's not going to take the diagonal and mow down people and trees

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	and fences because that's the shortest route. That's not what we mean by the shortest route when we

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	program it. And that's just what an intelligence system is by definition. It takes into account

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	multiple constraints. The same is true, in fact, even more true of so called general intelligence.

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	That is, if it's genuinely intelligent, it's not going to pursue some goal single mindedly,

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	omitting every other consideration and collateral effect. That's not artificial and

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	general intelligence. That's artificial stupidity. I agree with you, by the way,

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	on the promise of autonomous vehicles for improving human welfare. I think it's spectacular.

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	And I'm surprised at how little press coverage notes that in the United States alone,

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	something like 40,000 people die every year on the highways, vastly more than are killed by

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	terrorists. And we spend a trillion dollars on a war to combat deaths by terrorism,

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	about half a dozen a year, whereas every year and year out, 40,000 people are

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	massacred on the highways, which could be brought down to very close to zero.

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	So I'm with you on the humanitarian benefit.

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	Let me just mention that as a person who's building these cars, it is a little bit offensive to me

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	to say that engineers would be clueless enough not to engineer safety into systems. I often

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	stay up at night thinking about those 40,000 people that are dying. And everything I try to

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	engineer is to save those people's lives. So every new invention that I'm super excited about,

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	every new, all the deep learning literature and CVPR conferences and NIPS, everything I'm super

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	excited about is all grounded in making it safe and help people. So I just don't see how that

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	trajectory can all of a sudden slip into a situation where intelligence will be highly

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	negative. You and I certainly agree on that. And I think that's only the beginning of the

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	potential humanitarian benefits of artificial intelligence. There's been enormous attention

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	to what are we going to do with the people whose jobs are made obsolete by artificial

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	intelligence. But very little attention given to the fact that the jobs that are going to be

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	made obsolete are horrible jobs. The fact that people aren't going to be picking crops and making

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	beds and driving trucks and mining coal, these are soul deadening jobs. And we have a whole

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	literature sympathizing with the people stuck in these menial, mind deadening, dangerous jobs.

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	If we can eliminate them, this is a fantastic boon to humanity. Now, granted,

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	we, you solve one problem and there's another one, namely, how do we get these people a decent

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	income? But if we're smart enough to invent machines that can make beds and put away dishes and

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	handle hospital patients, I think we're smart enough to figure out how to redistribute income

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	to a portion, some of the vast economic savings to the human beings who will no longer be needed to

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	make beds. Okay. Sam Harris says that it's obvious that eventually AI will be an existential risk.

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	He's one of the people who says it's obvious. We don't know when the claim goes, but eventually

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	it's obvious. And because we don't know when we should worry about it now. It's a very interesting

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	argument in my eyes. So how do we think about timescale? How do we think about existential

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	threats when we don't really, we know so little about the threat, unlike nuclear weapons, perhaps,

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	about this particular threat, that it could happen tomorrow, right? So, but very likely it won't.

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	Very likely it'd be 100 years away. So how do, do we ignore it? Do, how do we talk about it?

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	Do we worry about it? What, how do we think about those? What is it?

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	A threat that we can imagine, it's within the limits of our imagination, but not within our

	22:19.600 --> 22:25.760
	limits of understanding to sufficient, to accurately predict it. But what, what is, what is the it

	22:25.760 --> 22:31.280
	that we're referring to? Oh, AI, sorry, AI, AI being the existential threat. AI can always...

	22:31.280 --> 22:34.400
	How? But like enslaving us or turning us into paperclips?

	22:35.120 --> 22:38.800
	I think the most compelling from the Sam Harris perspective would be the paperclip situation.

	22:38.800 --> 22:44.000
	Yeah. I mean, I just think it's totally fanciful. I mean, that is, don't build a system. Don't give a,

	22:44.000 --> 22:50.400
	don't... First of all, the code of engineering is you don't implement a system with massive

	22:50.400 --> 22:55.040
	control before testing it. Now, perhaps the culture of engineering will radically change,

	22:55.040 --> 23:00.320
	then I would worry, but I don't see any signs that engineers will suddenly do idiotic things,

	23:00.320 --> 23:05.440
	like put a, an electrical power plant in control of a system that they haven't tested

	23:05.440 --> 23:14.720
	first. Or all of these scenarios not only imagine a almost a magically powered intelligence,

	23:15.360 --> 23:20.000
	you know, including things like cure cancer, which is probably an incoherent goal because

	23:20.000 --> 23:25.440
	there's so many different kinds of cancer or bring about world peace. I mean, how do you even specify

	23:25.440 --> 23:31.360
	that as a goal? But the scenarios also imagine some degree of control of every molecule in the

	23:31.360 --> 23:38.480
	universe, which not only is itself unlikely, but we would not start to connect these systems to

	23:39.200 --> 23:45.840
	infrastructure without, without testing as we would any kind of engineering system. Now,

	23:45.840 --> 23:53.920
	maybe some engineers will be irresponsible and we need legal and regulatory and legal

	23:53.920 --> 23:59.440
	responsibility implemented so that engineers don't do things that are stupid by their own standards.

	23:59.440 --> 24:08.560
	But the, I've never seen enough of a plausible scenario of existential threat to devote large

	24:08.560 --> 24:14.720
	amounts of brain power to, to forestall it. So you believe in the sort of the power en masse of

	24:14.720 --> 24:19.520
	the engineering of reason as you argue in your latest book of reason and science to sort of

	24:20.400 --> 24:26.160
	be the very thing that guides the development of new technology so it's safe and also keeps us

	24:26.160 --> 24:32.480
	safe. Yeah, the same, you know, granted the same culture of safety that currently is part of the

	24:32.480 --> 24:38.960
	engineering mindset for airplanes, for example. So yeah, I don't think that, that that should

	24:38.960 --> 24:44.800
	be thrown out the window and that untested, all powerful systems should be suddenly implemented.

	24:44.800 --> 24:47.360
	But there's no reason to think they are. And in fact, if you look at the

	24:48.160 --> 24:51.760
	progress of artificial intelligence, it's been, you know, it's been impressive, especially in

	24:51.760 --> 24:56.960
	the last 10 years or so. But the idea that suddenly there'll be a step function that all of a sudden

	24:56.960 --> 25:02.160
	before we know it, it will be all powerful, that there'll be some kind of recursive self

	25:02.160 --> 25:11.200
	improvement, some kind of fume is also fanciful. Certainly by the technology that we that we're

	25:11.200 --> 25:16.720
	now impresses us, such as deep learning, where you train something on hundreds of thousands or

	25:16.720 --> 25:22.720
	millions of examples, they're not hundreds of thousands of problems of which curing cancer is

	25:24.320 --> 25:30.560
	typical example. And so the kind of techniques that have allowed AI to increase in the last

	25:30.560 --> 25:37.600
	five years are not the kind that are going to lead to this fantasy of exponential sudden

	25:37.600 --> 25:43.680
	self improvement. So I think it's kind of a magical thinking. It's not based on our understanding

	25:43.680 --> 25:49.200
	of how AI actually works. Now, give me a chance here. So you said fanciful, magical thinking.

	25:50.240 --> 25:55.280
	In his TED Talk, Sam Harris says that thinking about AI killing all human civilization is somehow

	25:55.280 --> 26:00.400
	fun intellectually. Now, I have to say as a scientist engineer, I don't find it fun.

	26:01.200 --> 26:08.560
	But when I'm having beer with my non AI friends, there is indeed something fun and appealing about

	26:08.560 --> 26:14.720
	it. Like talking about an episode of Black Mirror, considering if a large meteor is headed towards

	26:14.720 --> 26:20.640
	Earth, we were just told a large meteor is headed towards Earth, something like this. And can you

	26:20.640 --> 26:25.840
	relate to this sense of fun? And do you understand the psychology of it? Yes, great. Good question.

	26:26.880 --> 26:33.440
	I personally don't find it fun. I find it kind of actually a waste of time, because there are

	26:33.440 --> 26:39.840
	genuine threats that we ought to be thinking about, like pandemics, like cybersecurity

	26:39.840 --> 26:47.040
	vulnerabilities, like the possibility of nuclear war and certainly climate change. This is enough

	26:47.040 --> 26:55.280
	to fill many conversations without. And I think Sam did put his finger on something, namely that

	26:55.280 --> 27:03.120
	there is a community, sometimes called the rationality community, that delights in using its

	27:03.120 --> 27:10.160
	brain power to come up with scenarios that would not occur to mere mortals, to less cerebral people.

	27:10.160 --> 27:15.360
	So there is a kind of intellectual thrill in finding new things to worry about that no one

	27:15.360 --> 27:21.200
	has worried about yet. I actually think, though, that it's not only is it a kind of fun that doesn't

	27:21.200 --> 27:27.280
	give me particular pleasure. But I think there can be a pernicious side to it, namely that you

	27:27.280 --> 27:35.280
	overcome people with such dread, such fatalism, that there's so many ways to die to annihilate

	27:35.280 --> 27:40.160
	our civilization that we may as well enjoy life while we can. There's nothing we can do about it.

	27:40.160 --> 27:46.560
	If climate change doesn't do us in, then runaway robots will. So let's enjoy ourselves now. We

	27:46.560 --> 27:55.200
	got to prioritize. We have to look at threats that are close to certainty, such as climate change,

	27:55.200 --> 28:00.320
	and distinguish those from ones that are merely imaginable, but with infinitesimal probabilities.

	28:01.360 --> 28:07.120
	And we have to take into account people's worry budget. You can't worry about everything. And

	28:07.120 --> 28:13.920
	if you sow dread and fear and terror and and fatalism, it can lead to a kind of numbness. Well,

	28:13.920 --> 28:18.240
	they're just these problems are overwhelming and the engineers are just going to kill us all.

	28:19.040 --> 28:25.760
	So let's either destroy the entire infrastructure of science, technology,

	28:26.640 --> 28:32.080
	or let's just enjoy life while we can. So there's a certain line of worry, which I'm

	28:32.080 --> 28:36.160
	worried about a lot of things engineering. There's a certain line of worry when you cross,

	28:36.160 --> 28:42.800
	you allow it to cross, that it becomes paralyzing fear as opposed to productive fear. And that's

	28:42.800 --> 28:49.760
	kind of what you're highlighting. Exactly right. And we've seen some, we know that human effort is

	28:49.760 --> 28:58.080
	not well calibrated against risk in that because a basic tenet of cognitive psychology is that

	28:59.440 --> 29:05.120
	perception of risk and hence perception of fear is driven by imaginability, not by data.

	29:05.920 --> 29:11.200
	And so we misallocate vast amounts of resources to avoiding terrorism,

	29:11.200 --> 29:16.240
	which kills on average about six Americans a year with a one exception of 9 11. We invade

	29:16.240 --> 29:23.920
	countries, we invent an entire new departments of government with massive, massive expenditure

	29:23.920 --> 29:30.800
	of resources and lives to defend ourselves against a trivial risk. Whereas guaranteed risks,

	29:30.800 --> 29:36.720
	you mentioned as one of them, you mentioned traffic fatalities and even risks that are

	29:36.720 --> 29:46.240
	not here, but are plausible enough to worry about like pandemics, like nuclear war,

	29:47.120 --> 29:51.760
	receive far too little attention. In presidential debates, there's no discussion of

	29:51.760 --> 29:56.720
	how to minimize the risk of nuclear war, lots of discussion of terrorism, for example.

	29:57.840 --> 30:05.520
	And so we, I think it's essential to calibrate our budget of fear, worry, concerned planning

	30:05.520 --> 30:12.640
	to the actual probability of harm. Yep. So let me ask this in this question.

	30:13.520 --> 30:18.960
	So speaking of imaginability, you said it's important to think about reason. And one of my

	30:18.960 --> 30:26.560
	favorite people who likes to dip into the outskirts of reason through fascinating exploration of his

	30:26.560 --> 30:34.880
	imagination is Joe Rogan. Oh, yes. So who has, through reason, used to believe a lot of conspiracies

	30:34.880 --> 30:40.000
	and through reason has stripped away a lot of his beliefs in that way. So it's fascinating actually

	30:40.000 --> 30:47.920
	to watch him through rationality, kind of throw away the ideas of Bigfoot and 911. I'm not sure

	30:47.920 --> 30:52.320
	exactly. Kim Trails. I don't know what he believes in. Yes, okay. But he no longer believed in,

	30:52.320 --> 30:57.920
	that's right. No, he's become a real force for good. So you were on the Joe Rogan podcast in

	30:57.920 --> 31:02.880
	February and had a fascinating conversation, but as far as I remember, didn't talk much about

	31:02.880 --> 31:09.280
	artificial intelligence. I will be on his podcast in a couple of weeks. Joe is very much concerned

	31:09.280 --> 31:14.640
	about existential threat of AI. I'm not sure if you're, this is why I was hoping that you'll get

	31:14.640 --> 31:20.480
	into that topic. And in this way, he represents quite a lot of people who look at the topic of AI

	31:20.480 --> 31:27.840
	from 10,000 foot level. So as an exercise of communication, you said it's important to be

	31:27.840 --> 31:33.280
	rational and reason about these things. Let me ask, if you were to coach me as an AI researcher

	31:33.280 --> 31:38.320
	about how to speak to Joe and the general public about AI, what would you advise?

	31:38.320 --> 31:42.400
	Well, the short answer would be to read the sections that I wrote in Enlightenment.

	31:44.080 --> 31:48.880
	But longer reason would be, I think to emphasize, and I think you're very well positioned as an

	31:48.880 --> 31:54.800
	engineer to remind people about the culture of engineering, that it really is safety oriented,

	31:54.800 --> 32:02.160
	that another discussion in Enlightenment now, I plot rates of accidental death from various

	32:02.160 --> 32:09.280
	causes, plane crashes, car crashes, occupational accidents, even death by lightning strikes,

	32:09.280 --> 32:16.560
	and they all plummet. Because the culture of engineering is how do you squeeze out the lethal

	32:16.560 --> 32:23.360
	risks, death by fire, death by drowning, death by asphyxiation, all of them drastically declined

	32:23.360 --> 32:28.160
	because of advances in engineering, that I got to say, I did not appreciate until I saw those

	32:28.160 --> 32:34.000
	graphs. And it is because exactly people like you who stay up at night thinking, oh my God,

	32:36.000 --> 32:42.560
	what I'm inventing likely to hurt people and to deploy ingenuity to prevent that from happening.

	32:42.560 --> 32:47.360
	Now, I'm not an engineer, although I spent 22 years at MIT, so I know something about the culture

	32:47.360 --> 32:51.360
	of engineering. My understanding is that this is the way you think if you're an engineer.

	32:51.360 --> 32:58.160
	And it's essential that that culture not be suddenly switched off when it comes to artificial

	32:58.160 --> 33:02.080
	intelligence. So I mean, that could be a problem, but is there any reason to think it would be

	33:02.080 --> 33:07.360
	switched off? I don't think so. And one, there's not enough engineers speaking up for this way,

	33:07.360 --> 33:13.680
	for the excitement, for the positive view of human nature, what you're trying to create is

	33:13.680 --> 33:18.240
	the positivity, like everything we try to invent is trying to do good for the world.

	33:18.240 --> 33:23.600
	But let me ask you about the psychology of negativity. It seems just objectively,

	33:23.600 --> 33:27.680
	not considering the topic, it seems that being negative about the future, it makes you sound

	33:27.680 --> 33:32.720
	smarter than being positive about the future, in regard to this topic. Am I correct in this

	33:32.720 --> 33:39.120
	observation? And if so, why do you think that is? Yeah, I think there is that phenomenon,

	33:39.120 --> 33:43.920
	that as Tom Lehrer, the satirist said, always predict the worst and you'll be hailed as a

	33:43.920 --> 33:51.840
	prophet. It may be part of our overall negativity bias. We are as a species more attuned to the

	33:51.840 --> 33:59.200
	negative than the positive. We dread losses more than we enjoy gains. And that might open up a

	33:59.200 --> 34:06.560
	space for prophets to remind us of harms and risks and losses that we may have overlooked.

	34:06.560 --> 34:15.040
	So I think there is that asymmetry. So you've written some of my favorite books

	34:16.080 --> 34:21.680
	all over the place. So starting from Enlightenment now, to the better ranges of our nature,

	34:21.680 --> 34:28.560
	blank slate, how the mind works, the one about language, language instinct. Bill Gates,

	34:28.560 --> 34:37.840
	big fan too, said of your most recent book that it's my new favorite book of all time. So for

	34:37.840 --> 34:44.000
	you as an author, what was the book early on in your life that had a profound impact on the way

	34:44.000 --> 34:50.560
	you saw the world? Certainly this book Enlightenment now is influenced by David Deutch's The Beginning

	34:50.560 --> 34:57.520
	of Infinity. We have a rather deep reflection on knowledge and the power of knowledge to improve

	34:57.520 --> 35:02.960
	the human condition. They end with bits of wisdom such as that problems are inevitable,

	35:02.960 --> 35:07.760
	but problems are solvable given the right knowledge and that solutions create new problems

	35:07.760 --> 35:12.480
	that have to be solved in their turn. That's I think a kind of wisdom about the human condition

	35:12.480 --> 35:16.960
	that influenced the writing of this book. There's some books that are excellent but obscure,

	35:16.960 --> 35:22.080
	some of which I have on my page on my website. I read a book called The History of Force,

	35:22.080 --> 35:27.920
	self published by a political scientist named James Payne on the historical decline of violence and

	35:27.920 --> 35:35.120
	that was one of the inspirations for the better angels of our nature. What about early on if

	35:35.120 --> 35:40.640
	you look back when you were maybe a teenager? I loved a book called One, Two, Three, Infinity.

	35:40.640 --> 35:45.920
	When I was a young adult, I read that book by George Gamov, the physicist, which had very

	35:45.920 --> 35:55.120
	accessible and humorous explanations of relativity, of number theory, of dimensionality, high

	35:56.080 --> 36:02.240
	multiple dimensional spaces in a way that I think is still delightful 70 years after it was published.

	36:03.120 --> 36:09.280
	I like the Time Life Science series. These are books that arrive every month that my mother

	36:09.280 --> 36:15.600
	subscribed to. Each one on a different topic. One would be on electricity, one would be on

	36:15.600 --> 36:21.440
	forests, one would be on evolution, and then one was on the mind. I was just intrigued that there

	36:21.440 --> 36:27.040
	could be a science of mind. That book, I would cite as an influence as well. Then later on.

	36:27.040 --> 36:30.960
	That's when you fell in love with the idea of studying the mind. Was that the thing that grabbed

	36:30.960 --> 36:38.560
	you? It was one of the things, I would say. I read as a college student the book Reflections on

	36:38.560 --> 36:44.800
	Language by Noam Chomsky. He spent most of his career here at MIT. Richard Dawkins,

	36:44.800 --> 36:48.800
	two books, The Blind Watchmaker and the Selfish Gene were enormously influential,

	36:49.520 --> 36:56.640
	partly mainly for the content, but also for the writing style, the ability to explain

	36:56.640 --> 37:03.760
	abstract concepts in lively prose. Stephen Jay Gould's first collection ever since Darwin, also

	37:05.040 --> 37:11.120
	excellent example of lively writing. George Miller, the psychologist that most psychologists

	37:11.120 --> 37:17.440
	are familiar with, came up with the idea that human memory has a capacity of seven plus or minus

	37:17.440 --> 37:21.920
	two chunks. That's probably his biggest claim to fame. He wrote a couple of books on language

	37:21.920 --> 37:27.520
	and communication that I'd read as an undergraduate. Again, beautifully written and intellectually deep.

	37:28.400 --> 37:31.840
	Wonderful. Stephen, thank you so much for taking the time today.

	37:31.840 --> 37:42.960
	My pleasure. Thanks a lot, Lex.