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Steven Pinker: AI in the Age of Reason

Episode 2018-10-172018-10-17English

Guests: Steven Pinker

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Contents2 chapters§01Transcript · 00:00–19:45§02Transcript · 19:45–37:33

§01Transcript · 00:00–19:45

00:00You've studied the human mind, cognition, language, vision, evolution, psychology,

00:05from child to adult, from the level of individual to the level of our entire civilization.

00:11So I feel like I can start with a simple multiple choice question.

00:16What is the meaning of life? Is it A. to attain knowledge as Plato said,

00:22B. to attain power as Nietzsche said, C. to escape death as Ernest Becker said,

00:27D. to propagate our genes as Darwin and others have said,

00:33E. there is no meaning as the nihilists have said,

00:37F. knowing the meaning of life is beyond our cognitive capabilities as Stephen Pinker said,

00:42based on my interpretation 20 years ago, and G. none of the above.

00:48I'd say A. comes closest, but I would amend that to

00:51C. to attaining not only knowledge but fulfillment more generally, that is life, health, stimulation,

01:00access to the living cultural and social world.

01:06Now this is our meaning of life. It's not the meaning of life if you were to ask our genes.

01:12Their meaning is to propagate copies of themselves, but that is distinct from the

01:17meaning that the brain that they lead to sets for itself.

01:22So to you knowledge is a small subset or a large subset?

01:27It's a large subset, but it's not the entirety of human striving because we also want to

01:35interact with people. We want to experience beauty. We want to experience the richness

01:39of the natural world, but understanding what makes the universe tick is way up there.

01:47For some of us more than others, certainly for me that's one of the top five.

01:54So is that a fundamental aspect? Are you just describing your own preference or is this a

02:00fundamental aspect of human nature is to seek knowledge? In your latest book you talk about

02:05the power, the usefulness of rationality and reason and so on. Is that a fundamental

02:11nature of human beings or is it something we should just strive for?

02:17Both. We're capable of striving for it because it is one of the things that make us what we are,

02:23homo sapiens, wise men. We are unusual among animals in the degree to which we acquire

02:32knowledge and use it to survive. We make tools. We strike agreements via language. We extract

02:41poisons. We predict the behavior of animals. We try to get at the workings of plants.

02:47And when I say we, I don't just mean we in the modern West, but we as a species everywhere,

02:52which is how we've managed to occupy every niche on the planet, how we've managed to drive other

02:58animals to extinction. And the refinement of reason in pursuit of human wellbeing, of health,

03:06happiness, social richness, cultural richness is our main challenge in the present. That is

03:14using our intellect, using our knowledge to figure out how the world works, how we work

03:19in order to make discoveries and strike agreements that make us all better off in the long run.

03:25Right. And you do that almost undeniably and in a data driven way in your recent book,

03:31but I'd like to focus on the artificial intelligence aspect of things and not just

03:36artificial intelligence, but natural intelligence too. So 20 years ago in a book you've written on

03:41how the mind works, you conjecture again, am I right to interpret things? You can correct me

03:49if I'm wrong, but you conjecture that human thought in the brain may be a result of a

03:54massive network of highly interconnected neurons. So from this interconnectivity emerges thought

04:01compared to artificial neural networks, which we use for machine learning today,

04:06is there something fundamentally more complex, mysterious, even magical about the biological

04:12neural networks versus the ones we've been starting to use over the past 60 years and

04:19have become to success in the past 10? There is something a little bit mysterious

04:24about the human neural networks, which is that each one of us who is a neural network knows that

04:31we ourselves are conscious. Conscious not in the sense of registering our surroundings or even

04:36registering our internal state, but in having subjective first person, present tense experience.

04:42That is when I see red, it's not just different from green, but there's a redness to it that I

04:49feel. Whether an artificial system would experience that or not, I don't know and I don't think I can

04:54know. That's why it's mysterious. If we had a perfectly lifelike robot that was behaviorally

05:00indistinguishable from a human, would we attribute consciousness to it or ought we to attribute

05:06consciousness to it? And that's something that it's very hard to know. But putting that aside,

05:12putting aside that largely philosophical question, the question is, is there some difference between

05:19the human neural network and the ones that we're building in artificial intelligence will mean

05:23that we're on the current trajectory, not going to reach the point where we've got a lifelike

05:30robot indistinguishable from a human because the way their so called neural networks are organized

05:35are different from the way ours are organized. I think there's overlap, but I think there are

05:39some big differences that current neural networks, current so called deep learning systems are in

05:48reality not all that deep. That is, they are very good at extracting high order statistical

05:53regularities, but most of the systems don't have a semantic level, a level of actual understanding

06:00of who did what to whom, why, where, how things work, what causes what else. Do you think that

06:07kind of thing can emerge as it does? So artificial neural networks are much smaller, the number of

06:11connections and so on than the current human biological networks, but do you think sort of

06:18to go to consciousness or to go to this higher level semantic reasoning about things, do you

06:22think that can emerge with just a larger network with a more richly weirdly interconnected network?

06:29Separate it in consciousness because consciousness is even a matter of complexity.

06:33A really weird one.

06:34Yeah, you could sensibly ask the question of whether shrimp are conscious, for example,

06:38they're not terribly complex, but maybe they feel pain. So let's just put that part of it aside.

06:44But I think sheer size of a neural network is not enough to give it structure and knowledge,

06:52but if it's suitably engineered, then why not? That is, we're neural networks, natural selection

06:59did a kind of equivalent of engineering of our brains. So I don't think there's anything mysterious

07:04in the sense that no system made out of silicon could ever do what a human brain can do. I think

07:11it's possible in principle. Whether it'll ever happen depends not only on how clever we are

07:17in engineering these systems, but whether we even want to, whether that's even a sensible goal.

07:22That is, you can ask the question, is there any locomotion system that is as good as a human?

07:29Well, we kind of want to do better than a human ultimately in terms of legged locomotion.

07:35There's no reason that humans should be our benchmark. They're tools that might be better

07:39in some ways. It may be that we can't duplicate a natural system because at some point it's so much

07:49cheaper to use a natural system that we're not going to invest more brainpower and resources.

07:54So for example, we don't really have an exact substitute for wood. We still build houses out

08:00of wood. We still build furniture out of wood. We like the look. We like the feel. It has certain

08:05properties that synthetics don't. It's not that there's anything magical or mysterious about wood.

08:11It's just that the extra steps of duplicating everything about wood is something we just haven't

08:17bothered because we have wood. Likewise, say cotton. I'm wearing cotton clothing now. It feels

08:21much better than polyester. It's not that cotton has something magic in it. It's not that we couldn't

08:29ever synthesize something exactly like cotton, but at some point it's just not worth it. We've got

08:35cotton. Likewise, in the case of human intelligence, the goal of making an artificial system that is

08:42exactly like the human brain is a goal that we probably know is going to pursue to the bitter

08:47end, I suspect, because if you want tools that do things better than humans, you're not going to

08:53care whether it does something like humans. So for example, diagnosing cancer or predicting the

08:58weather, why set humans as your benchmark? But in general, I suspect you also believe

09:05that even if the human should not be a benchmark and we don't want to imitate humans in their

09:10system, there's a lot to be learned about how to create an artificial intelligence system by

09:15studying the human. Yeah, I think that's right. In the same way that to build flying machines,

09:22we want to understand the laws of aerodynamics, including birds, but not mimic the birds,

09:27but they're the same laws. You have a view on AI, artificial intelligence, and safety

09:35that, from my perspective, is refreshingly rational or perhaps more importantly, has elements

09:47of positivity to it, which I think can be inspiring and empowering as opposed to paralyzing.

09:53For many people, including AI researchers, the eventual existential threat of AI is obvious,

09:59not only possible, but obvious. And for many others, including AI researchers, the threat

10:05is not obvious. So Elon Musk is famously in the highly concerned about AI camp, saying things like

10:14AI is far more dangerous than nuclear weapons, and that AI will likely destroy human civilization.

10:21Human civilization. So in February, he said that if Elon was really serious about AI, the threat

10:29of AI, he would stop building self driving cars that he's doing very successfully as part of Tesla.

10:35Then he said, wow, if even Pinker doesn't understand the difference between narrow AI,

10:40like a car and general AI, when the latter literally has a million times more compute power

10:47and an open ended utility function, humanity is in deep trouble. So first, what did you mean by

10:54the statement about Elon Musk should stop building self driving cars if he's deeply concerned?

11:00Not the last time that Elon Musk has fired off an intemperate tweet.

11:04Well, we live in a world where Twitter has power.

11:07Yes. Yeah, I think there are two kinds of existential threat that have been discussed

11:16in connection with artificial intelligence, and I think that they're both incoherent.

11:20One of them is a vague fear of AI takeover, that just as we subjugated animals and less technologically

11:29advanced peoples, so if we build something that's more advanced than us, it will inevitably turn us

11:34into pets or slaves or domesticated animal equivalents. I think this confuses intelligence

11:42with a will to power, that it so happens that in the intelligence system we are most familiar with,

11:49namely homo sapiens, we are products of natural selection, which is a competitive process,

11:54and so bundled together with our problem solving capacity are a number of nasty traits like

12:00dominance and exploitation and maximization of power and glory and resources and influence.

12:08There's no reason to think that sheer problem solving capability will set that as one of its

12:13goals. Its goals will be whatever we set its goals as, and as long as someone isn't building a

12:18megalomaniacal artificial intelligence, then there's no reason to think that it would naturally

12:24evolve in that direction. Now, you might say, well, what if we gave it the goal of maximizing

12:28its own power source? That's a pretty stupid goal to give an autonomous system. You don't give it

12:34that goal. I mean, that's just self evidently idiotic. So if you look at the history of the

12:40world, there's been a lot of opportunities where engineers could instill in a system

12:45destructive power and they choose not to because that's the natural process of engineering.

12:49Well, except for weapons. I mean, if you're building a weapon, its goal is to destroy people,

12:53and so I think there are good reasons to not build certain kinds of weapons. I think building

12:58nuclear weapons was a massive mistake. You do. So maybe pause on that because that is one of

13:06the serious threats. Do you think that it was a mistake in a sense that it should have been

13:12stopped early on? Or do you think it's just an unfortunate event of invention that this was

13:19invented? Do you think it's possible to stop? I guess is the question. It's hard to rewind the

13:23clock because of course it was invented in the context of World War II and the fear that the

13:28Nazis might develop one first. Then once it was initiated for that reason, it was hard to turn

13:35off, especially since winning the war against the Japanese and the Nazis was such an overwhelming

13:42goal of every responsible person that there's just nothing that people wouldn't have done then

13:47to ensure victory. It's quite possible if World War II hadn't happened that nuclear weapons

13:52wouldn't have been invented. We can't know, but I don't think it was by any means a necessity,

13:57any more than some of the other weapon systems that were envisioned but never implemented,

14:02like planes that would disperse poison gas over cities like crop dusters or systems to try to

14:10create earthquakes and tsunamis in enemy countries, to weaponize the weather,

14:16weaponize solar flares, all kinds of crazy schemes that we thought the better of.

14:21I think analogies between nuclear weapons and artificial intelligence are fundamentally

14:25misguided because the whole point of nuclear weapons is to destroy things. The point of

14:30artificial intelligence is not to destroy things. So the analogy is misleading.

14:36So there's two artificial intelligence you mentioned. The first one I guess is highly

14:39intelligent or power hungry.

14:42Yeah, it's a system that we design ourselves where we give it the goals. Goals are external to

14:46the means to attain the goals. If we don't design an artificially intelligent system to

14:55maximize dominance, then it won't maximize dominance. It's just that we're so familiar

15:00with homo sapiens where these two traits come bundled together, particularly in men,

15:06that we are apt to confuse high intelligence with a will to power, but that's just an error.

15:15The other fear is that will be collateral damage that will give artificial intelligence a goal

15:21like make paper clips and it will pursue that goal so brilliantly that before we can stop it,

15:27it turns us into paper clips. We'll give it the goal of curing cancer and it will turn us into

15:32guinea pigs for lethal experiments or give it the goal of world peace and its conception of world

15:38peace is no people, therefore no fighting and so it will kill us all. Now I think these are utterly

15:43fanciful. In fact, I think they're actually self defeating. They first of all assume that we're

15:49going to be so brilliant that we can design an artificial intelligence that can cure cancer,

15:53but so stupid that we don't specify what we mean by curing cancer in enough detail that it won't

15:59kill us in the process and it assumes that the system will be so smart that it can cure cancer,

16:06but so idiotic that it can't figure out that what we mean by curing cancer is not killing everyone.

16:12I think that the collateral damage scenario, the value alignment problem is also based on

16:18a misconception. So one of the challenges, of course, we don't know how to build either system

16:23currently or are we even close to knowing? Of course, those things can change overnight,

16:27but at this time, theorizing about it is very challenging in either direction. So that's

16:33probably at the core of the problem is without that ability to reason about the real engineering

16:39things here at hand is your imagination runs away with things. Exactly. But let me sort of ask,

16:45what do you think was the motivation, the thought process of Elon Musk? I build autonomous vehicles,

16:52I study autonomous vehicles, I study Tesla autopilot. I think it is one of the greatest

16:57currently large scale application of artificial intelligence in the world. It has potentially a

17:04very positive impact on society. So how does a person who's creating this very good quote unquote

17:10narrow AI system also seem to be so concerned about this other general AI? What do you think

17:19is the motivation there? What do you think is the thing? Well, you probably have to ask him,

17:23but there, and he is notoriously flamboyant, impulsive to the, as we have just seen,

17:31to the detriment of his own goals of the health of the company. So I don't know what's going on

17:37in his mind. You probably have to ask him, but I don't think the, and I don't think the distinction

17:42between special purpose AI and so called general AI is relevant that in the same way that special

17:50purpose AI is not going to do anything conceivable in order to attain a goal. All engineering systems

17:57are designed to trade off across multiple goals. When we build cars in the first place,

18:02we didn't forget to install brakes because the goal of a car is to go fast. It occurred to people,

18:08yes, you want it to go fast, but not always. So you would build in brakes too. Likewise,

18:13if a car is going to be autonomous and program it to take the shortest route to the airport,

18:20it's not going to take the diagonal and mow down people and trees and fences because that's the

18:24shortest route. That's not what we mean by the shortest route when we program it. And that's just

18:29what an intelligence system is by definition. It takes into account multiple constraints.

18:36The same is true, in fact, even more true of so called general intelligence. That is,

18:41if it's genuinely intelligent, it's not going to pursue some goal singlemindedly, omitting every

18:48other consideration and collateral effect. That's not artificial and general intelligence. That's

18:54artificial stupidity. I agree with you, by the way, on the promise of autonomous vehicles for

19:01improving human welfare. I think it's spectacular. And I'm surprised at how little press coverage

19:06notes that in the United States alone, something like 40,000 people die every year on the highways,

19:11vastly more than are killed by terrorists. And we spent a trillion dollars on a war to combat

19:18deaths by terrorism, about half a dozen a year. Whereas year in, year out, 40,000 people are

19:24massacred on the highways, which could be brought down to very close to zero. So I'm with you on

19:29the humanitarian benefit. Let me just mention that as a person who's building these cars,

19:34it is a little bit offensive to me to say that engineers would be clueless enough not to engineer

19:39safety into systems. I often stay up at night thinking about those 40,000 people that are dying.

§02Transcript · 19:45–37:33

19:45And everything I tried to engineer is to save those people's lives. So every new invention that

19:50I'm super excited about, in all the deep learning literature and CVPR conferences and NIPS, everything

19:59I'm super excited about is all grounded in making it safe and help people. So I just don't see how

20:08that trajectory can all of a sudden slip into a situation where intelligence will be highly

20:13negative. You and I certainly agree on that. And I think that's only the beginning of the

20:17potential humanitarian benefits of artificial intelligence. There's been enormous attention to

20:24what are we going to do with the people whose jobs are made obsolete by artificial intelligence,

20:28but very little attention given to the fact that the jobs that are going to be made obsolete are

20:32horrible jobs. The fact that people aren't going to be picking crops and making beds and driving

20:38trucks and mining coal, these are soul deadening jobs. And we have a whole literature sympathizing

20:45with the people stuck in these menial, mind deadening, dangerous jobs. If we can eliminate

20:53them, this is a fantastic boon to humanity. Now granted, you solve one problem and there's another

20:58one, namely, how do we get these people a decent income? But if we're smart enough to invent machines

21:05that can make beds and put away dishes and handle hospital patients, I think we're smart enough to

21:12figure out how to redistribute income to apportion some of the vast economic savings to the human

21:19beings who will no longer be needed to make beds. Okay. Sam Harris says that it's obvious that

21:26eventually AI will be an existential risk. He's one of the people who says it's obvious.

21:31We don't know when the claim goes, but eventually it's obvious. And because we don't know when,

21:38we should worry about it now. This is a very interesting argument in my eyes. So how do we

21:45think about timescale? How do we think about existential threats when we don't really, we know

21:51so little about the threat, unlike nuclear weapons perhaps, about this particular threat, that it

21:58could happen tomorrow, right? So, but very likely it won't. Very likely it'd be a hundred years away.

22:04So how do we ignore it? How do we talk about it? Do we worry about it? How do we think about those?

22:12What is it?

22:13A threat that we can imagine. It's within the limits of our imagination,

22:18but not within our limits of understanding to accurately predict it.

22:24But what is the it that we're afraid of?

22:26Sorry. AI being the existential threat.

22:30AI. How? Like enslaving us or turning us into paperclips?

22:35I think the most compelling from the Sam Harris perspective would be the paperclip situation.

22:39Yeah. I mean, I just think it's totally fanciful. I mean, that is don't build a system.

22:43Don't give a, don't, first of all, the code of engineering is you don't implement a system with

22:50massive control before testing it. Now, perhaps the culture of engineering will radically change.

22:55Then I would worry, but I don't see any signs that engineers will suddenly do idiotic things,

23:00like put a electric power plant in control of a system that they haven't tested first.

23:07Or all of these scenarios, not only imagine almost a magically powered intelligence,

23:15including things like cure cancer, which is probably an incoherent goal because there's

23:20so many different kinds of cancer or bring about world peace. I mean, how do you even specify that

23:25as a goal? But the scenarios also imagine some degree of control of every molecule in the

23:31universe, which not only is itself unlikely, but we would not start to connect these systems to

23:39infrastructure without testing as we would any kind of engineering system.

23:45Now, maybe some engineers will be irresponsible and we need legal and regulatory and legal

23:53responsibility implemented so that engineers don't do things that are stupid by their own standards.

24:00But the, I've never seen enough of a plausible scenario of existential threat to devote large

24:08amounts of brain power to, to forestall it. So you believe in the sort of the power on

24:14mass of the engineering of reason, as you argue in your latest book of Reason and Science, to sort of

24:20be the very thing that guides the development of new technology so it's safe and also keeps us safe.

24:28You know, granted the same culture of safety that currently is part of the engineering mindset for

24:34airplanes, for example. So yeah, I don't think that that should be thrown out the window and

24:40that untested all powerful systems should be suddenly implemented, but there's no reason to

24:45think they are. And in fact, if you look at the progress of artificial intelligence, it's been,

24:50you know, it's been impressive, especially in the last 10 years or so, but the idea that suddenly

24:54there'll be a step function that all of a sudden before we know it, it will be all powerful,

25:00that there'll be some kind of recursive self improvement, some kind of fume is also fanciful.

25:06We, certainly by the technology that we, that we're now impresses us, such as deep learning,

25:13where you train something on hundreds of thousands or millions of examples,

25:18they're not hundreds of thousands of problems of which curing cancer is a typical example.

25:26And so the kind of techniques that have allowed AI to increase in the last five years are not the

25:31kind that are going to lead to this fantasy of exponential sudden self improvement. I think it's

25:40kind of a magical thinking. It's not based on our understanding of how AI actually works.

25:45Now give me a chance here. So you said fanciful, magical thinking. In his TED talk,

25:51Sam Harris says that thinking about AI killing all human civilization is somehow fun,

25:55intellectually. Now I have to say as a scientist engineer, I don't find it fun,

26:00but when I'm having beer with my non AI friends, there is indeed something fun and appealing about

26:08it. Like talking about an episode of Black Mirror, considering if a large meteor is headed towards

26:14Earth, we were just told a large meteor is headed towards Earth, something like this. And can you

26:20relate to this sense of fun? And do you understand the psychology of it?

26:24Yes. Good question. I personally don't find it fun. I find it kind of actually a waste of time

26:32because there are genuine threats that we ought to be thinking about like pandemics, like cyber

26:39security vulnerabilities, like the possibility of nuclear war and certainly climate change.

26:46You know, this is enough to fill many conversations. And I think Sam did put his

26:54finger on something, namely that there is a community, sometimes called the rationality

27:00community, that delights in using its brainpower to come up with scenarios that would not occur

27:07to mere mortals, to less cerebral people. So there is a kind of intellectual thrill in finding new

27:14things to worry about that no one has worried about yet. I actually think, though, that it's

27:19not only is it a kind of fun that doesn't give me particular pleasure, but I think there can be a

27:25pernicious side to it, namely that you overcome people with such dread, such fatalism, that there

27:32are so many ways to die, to annihilate our civilization, that we may as well enjoy life

27:39while we can. There's nothing we can do about it. If climate change doesn't do us in, then runaway

27:42robots will. So let's enjoy ourselves now. We've got to prioritize. We have to look at threats that

27:52are close to certainty, such as climate change, and distinguish those from ones that are merely

27:58imaginable but with infinitesimal probabilities. And we have to take into account people's worry

28:05budget. You can't worry about everything. And if you sow dread and fear and terror and fatalism,

28:12it can lead to a kind of numbness. Well, these problems are overwhelming, and the engineers are

28:17just going to kill us all. So let's either destroy the entire infrastructure of science, technology,

28:26or let's just enjoy life while we can. So there's a certain line of worry, which I'm worried about

28:32a lot of things in engineering. There's a certain line of worry when you cross, you're allowed to

28:36cross, that it becomes paralyzing fear as opposed to productive fear. And that's kind of what

28:44you're highlighting. Exactly right. And we've seen some, we know that human effort is not

28:50well calibrated against risk in that because a basic tenet of cognitive psychology is that

28:58perception of risk and hence perception of fear is driven by imaginability, not by data. And so we

29:05misallocate vast amounts of resources to avoiding terrorism, which kills on average about six

29:11Americans a year with one exception of 9 11. We invade countries, we invent entire new departments

29:18of government with massive, massive expenditure of resources and lives to defend ourselves against

29:25a trivial risk. Whereas guaranteed risks, one of them you mentioned traffic fatalities and even

29:34risks that are not here, but are plausible enough to worry about like pandemics, like nuclear war,

29:45receive far too little attention. In presidential debates, there's no discussion of how to minimize

29:51the risk of nuclear war. Lots of discussion of terrorism, for example. And so I think it's

29:58essential to calibrate our budget of fear, worry, concern, planning to the actual probability of

30:08harm. Yep. So let me ask this question. So speaking of imaginability, you said it's important to think

30:15about reason and one of my favorite people who likes to dip into the outskirts of reason through

30:23fascinating exploration of his imagination is Joe Rogan. Oh yes. So who has through reason used to

30:32believe a lot of conspiracies and through reason has stripped away a lot of his beliefs in that

30:37way. So it's fascinating actually to watch him through rationality kind of throw away the ideas

30:43of Bigfoot and 9 11. I'm not sure exactly. Kim Trails. I don't know what he believes in. Yes.

30:50Okay. But he no longer believed in. No, that's right. No, he's become a real force for good.

30:55Yep. So you were on the Joe Rogan podcast in February and had a fascinating conversation,

31:00but as far as I remember, didn't talk much about artificial intelligence. I will be on his podcast

31:05in a couple of weeks. Joe is very much concerned about existential threat of AI. I'm not sure if

31:11you're, this is why I was hoping that you would get into that topic. And in this way,

31:17he represents quite a lot of people who look at the topic of AI from 10,000 foot level.

31:22So as an exercise of communication, you said it's important to be rational and reason

31:29about these things. Let me ask, if you were to coach me as an AI researcher about how to speak

31:34to Joe and the general public about AI, what would you advise? Well, the short answer would be to

31:40read the sections that I wrote in enlightenment now about AI, but a longer reason would be I

31:45think to emphasize, and I think you're very well positioned as an engineer to remind people about

31:50the culture of engineering, that it really is safety oriented, that another discussion in

31:57enlightenment now, I plot rates of accidental death from various causes, plane crashes, car

32:04crashes, occupational accidents, even death by lightning strikes. And they all plummet because

32:12the culture of engineering is how do you squeeze out the lethal risks, death by fire, death by

32:18drowning, death by asphyxiation, all of them drastically declined because of advances in

32:24engineering that I got to say, I did not appreciate until I saw those graphs. And it is because

32:29exactly, people like you who stay up at night thinking, oh my God, is what I'm inventing likely

32:37to hurt people and to deploy ingenuity to prevent that from happening. Now, I'm not an engineer,

32:43although I spent 22 years at MIT, so I know something about the culture of engineering.

32:48My understanding is that this is the way you think if you're an engineer. And it's essential

32:53that that culture not be suddenly switched off when it comes to artificial intelligence. So,

32:59I mean, that could be a problem, but is there any reason to think it would be switched off?

33:02I don't think so. And one, there's not enough engineers speaking up for this

33:06way, for the excitement, for the positive view of human nature, what you're trying to create

33:13is positivity. Like everything we try to invent is trying to do good for the world.

33:18But let me ask you about the psychology of negativity. It seems just objectively,

33:23not considering the topic, it seems that being negative about the future makes you sound smarter

33:28than being positive about the future, irregardless of topic. Am I correct in this observation? And

33:34if so, why do you think that is? Yeah, I think there is that phenomenon that,

33:40as Tom Lehrer, the satirist said, always predict the worst and you'll be hailed as a prophet.

33:45It may be part of our overall negativity bias. We are as a species more attuned to the negative

33:52than the positive. We dread losses more than we enjoy gains. And that might open up a space for

34:02prophets to remind us of harms and risks and losses that we may have overlooked.

34:07So I think there is that asymmetry. So you've written some of my favorite books

34:16all over the place. So starting from Enlightenment Now to The Better Ages of Our Nature,

34:21Blank Slate, How the Mind Works, the one about language, Language Instinct. Bill Gates,

34:29big fan too, said of your most recent book that it's my new favorite book of all time.

34:37So for you as an author, what was a book early on in your life that had a profound impact on the

34:43way you saw the world? Certainly this book, Enlightenment Now, was influenced by David

34:49Deutsch's The Beginning of Infinity, a rather deep reflection on knowledge and the power of

34:55knowledge to improve the human condition. And with bits of wisdom such as that problems are

35:02inevitable but problems are solvable given the right knowledge and that solutions create new

35:07problems that have to be solved in their turn. That's I think a kind of wisdom about the human

35:11condition that influenced the writing of this book. There are some books that are excellent

35:16but obscure, some of which I have on a page on my website. I read a book called The History of Force,

35:22self published by a political scientist named James Payne on the historical decline of violence

35:27and that was one of the inspirations for The Better Angels of Our Nature.

35:33What about early on? If you look back when you were maybe a teenager?

35:38I loved a book called One, Two, Three, Infinity. When I was a young adult I read that book by

35:43George Gamow, the physicist, which had very accessible and humorous explanations of

35:48relativity, of number theory, of dimensionality, high multiple dimensional spaces in a way that I

35:59think is still delightful 70 years after it was published. I like the Time Life Science series.

36:06These are books that would arrive every month that my mother subscribed to, each one on a different

36:11topic. One would be on electricity, one would be on forests, one would be on evolution and then one

36:17was on the mind. I was just intrigued that there could be a science of mind and that book I would

36:24cite as an influence as well. Then later on... That's when you fell in love with the idea of

36:28studying the mind? Was that the thing that grabbed you? It was one of the things I would say. I read

36:35as a college student the book Reflections on Language by Noam Chomsky. I spent most of his

36:41career here at MIT. Richard Dawkins, two books, The Blind Watchmaker and The Selfish Gene,

36:47were enormously influential, mainly for the content but also for the writing style, the

36:55ability to explain abstract concepts in lively prose. Stephen Jay Gould's first collection,

37:02Ever Since Darwin, also an excellent example of lively writing. George Miller, a psychologist that

37:10most psychologists are familiar with, came up with the idea that human memory has a capacity of

37:16seven plus or minus two chunks. That's probably his biggest claim to fame. But he wrote a couple

37:20of books on language and communication that I read as an undergraduate. Again, beautifully written

37:25and intellectually deep. Wonderful. Stephen, thank you so much for taking the time today.

37:31My pleasure. Thanks a lot, Lex.

— A LITTLE MORE TO THINK ABOUT. —