Donald Hoffman: Reality is an Illusion - How Evolution Hid the Truth | Lex Fridman Podcast #293

1. 0:00 – 1:12

   Introduction

   1. DHDonald Hoffman0:00

      Whatever reality is, it's not what you see. W- what you see is, is just an adaptive fiction.

   2. LFLex Fridman0:12

      The following is a conversation with Donald Hoffman, Professor of Cognitive Sciences at UC Irvine, focusing his research on evolutionary psychology, visual perception, and consciousness. He's the author of over 120 scientific papers on these topics, and his most recent book titled The Case Against Reality: Why Evolution Hid the Truth from Our Eyes. I think some of the most interesting ideas in this world, like those of Donald Hoffman's, attempt to shake the foundation of our understanding of reality, and thus, they take a long time to internalize deeply, so proceed with caution. Questioning the fabric of reality can lead you to either madness or the truth. And the funny thing is, you won't know which is which. This is the Lex Fridman Podcast. To support it, please check out our sponsors in the description, and now, dear friends, here's Donald Hoffman.

2. 1:12 – 12:40

   Case against reality

   1. LFLex Fridman1:12

      In your book, The Case Against Reality: Why Evolution Hid the Truth from Our Eyes, you make the bold claim that the world we see with our eyes is not real. It's not even an abstraction of objective reality, it is completely detached from, uh, objective reality. Can you explain this idea?

   2. DHDonald Hoffman1:30

      Right, so this is a theorem from evolution by natural selection. So, the technical question that I and my team asked was, "What is the probability that natural selection would shape sensory systems to see true properties of objective reality?" And to our surprise, we found that the answer is precisely zero, except for one, one kind of structure that we can go into if you want to. But for, for any generic structure that you might think the world might have, a total order, a topology, metric, the probability is precisely zero that natural selection would shape any sensory system of any organism to see any aspect of objective reality. So, in that sense, uh, what we're seeing is what we need to see to stay alive long enough to reproduce. So, in other words, we're seeing what we need to guide adaptive behavior, full stop.

   3. LFLex Fridman2:23

      So, the evolutionary process, the process that took us from the origin of life on Earth-

   4. DHDonald Hoffman2:30

      (clears throat)

   5. LFLex Fridman2:30

      ... to the humans that we are today, that process does not maximize for truth, it maximizes for fitness, as you say, "Fitness beats truth." And fitness does not have to be connected to truth, is the claim. And that's where you have a- an approach towards zero of probability that we have evolved, human cognition, human consciousness, whatever it is, the magic that makes our mind work, evolved not for its ability to see the truth of reality, but its ability to survive in the environment.

   6. DHDonald Hoffman3:09

      That's exactly right. So, most of us intuitively think that surely the way that evolution will make our senses more fit is to make them tell us more truths, or at least the truths we need to know-

   7. LFLex Fridman3:22

      Yeah.

   8. DHDonald Hoffman3:22

      ... about objective reality, the truths we need in our niche. That's the standard view, and it was the view I took. I mean, that's, that's sort of what we're taught or just even assume. It's just sort of like the intelligent assumption that we would all make. But we don't have to just wave our hands. Uh, evolution by natural selection is a mathematically precise theory. Uh, John Maynard Smith, uh, in the '70s, uh, created evolutionary game theory, and we have evolutionary graph theory and even genetic algorithms that we can use to study this. And so we don't have to wave our hands, it's- it's a matter of theorem and proof and/or simulation before you get to theorems and proofs. And, uh, a couple graduate students of mine, Justin Maurach and Brian Marion, um, did some wonderful simulations that tipped me off that there was something going on here, and then I went to a mathematician, Chetan Prakash and Maneesh Singh and, uh, some other friends of mine, uh, Chris Fields and... But Chetan was the real mathematician in- behind all this and he's proved several theorems that, uh, uniformly indicate that, um, with one exception, which has to do with probability measures, um, there's no, uh, the probability is zero. Uh, the- the reason there's an exception for probability measures, so-called sigma algebras or, or, um, s- s- sigmatitive classes, is that for any scientific theory, uh, there is the assumption th- that needs to be made that the whatever structure the s- whatever probabilistic structure the world may have is not unrelated to the probabilistic structure n- of our perceptions. If they were completely unrelated, then no science would be possible. So in, so this is technically the- the map from reality to our senses has to be a so-called measurable map, has to preserve sigma algebras. But that means it could be infinite to one, and it could collapse all sorts of, of event information. But other than that there's, there's no requirement in standard evolutionary theory for, uh, fitness payoff functions, for example, to preserve any specific structures of objective reality. So, you can ask the technical question, this is one of the avenues we took. Um, if you look at all the fitness payoffs from, um, whatever world structure you might want to i- imagine, so a world with say a- a total order on it. So it's got end states and they're totally ordered. And then you can have, uh, a set of maps from that world into a set of payoffs, say from zero to 1,000 or whatever you want your payoffs to be, and you can just literally count all the payoff functions, and just do the combinatorics and count them. Then you can ask a precise question, how many of those payoff functions preserve the total order? If that's what you're lo- ... Or how many preserve the topology?... and you just count them and divide. So, so the number that are homomorphisms versus the total number, and then take the limit as the number of states in the world and the number of payoff values goes very large. And when you do that, you get zero every time.

   9. LFLex Fridman6:21

      O- okay. You've (laughs) ... There's a million things to ask here. But first of all, just in case, uh, people are not familiar with your work, let's sort of linger on the big bold statement here-

   10. DHDonald Hoffman6:35

       Sure. Mm-hmm.

   11. LFLex Fridman6:36

       ... which is, the thing we see with our eyes is not some kind of limited window into reality, it is completely detached from reality, likely completely detached from reality. You're saying 100% likely. (sighs) Okay. So none of this is real in the way we think is real, in the way we have this intuition there's, um, like this table is some kind of abstraction, but underneath it all, there's atoms, and there's an entire century of physics that describes the functioning of those atoms and the quarks that make them up. There's, uh, m- many Nobel Prizes-

   12. DHDonald Hoffman7:17

       (laughs)

   13. LFLex Fridman7:17

       ... about particles and fields and all that kinda stuff that, uh, slowly builds up to something that's perceivable to us, both with our eyes, with our different senses as this table. Then there's also ideas of chemistry that over layers of abstraction, from DNA to embryos, the cells that make the human body.

   14. DHDonald Hoffman7:42

       Right.

   15. LFLex Fridman7:43

       So all of that is not real.

   16. DHDonald Hoffman7:46

       It's a real experience, and it's a real adaptive set of perceptions. So it's an adaptive set of perceptions, full stop. The- we want to think that the perceptions-

   17. LFLex Fridman7:57

       So the perceptions are real.

   18. DHDonald Hoffman7:58

       So, so their perceptions are real as perceptions, right? They, they are... We, we are having our perceptions, but we've assumed that there's, uh, a, a pretty tight relationship between our perceptions and reality. If I look up and see the moon, then there is something that, uh, exists in space and time that, uh, matches, um, what I perceive. And all I'm saying is that if you take evolution by natural selection seriously, then that is precluded, that our perceptions are there, they're there to guide adaptive behavior, full stop. They're not there to show you the truth. In fact, the way I think about it is they're there to hide the truth because the truth is too complicated. It's just like if you're trying to, you know, use your laptop to write an email, right? What you're doing is toggling voltages in the computer, but good luck trying to do it that way. That's... We... The reason why we have a user interface is because we don't want to know that "truth." The diodes and resistors and all that, that terrible hardware. If you had to know all that truth, it would... you know, your friends wouldn't hear from you . So you... so what evolution gave us was perceptions that guide adaptive behavior, and part of that process, it turns out, means hiding the truth and giving you, um, uh, eye candy.

   19. LFLex Fridman9:16

       So what's the difference between hiding the truth and forming abstractions, uh, layers upon layers of abstractions over these, over low level voltages and transistors and, uh, chips and, uh, programming languages from Assembly to Python that then leads you to be able to have an interface like Chrome where you open up another set of JavaScript and HTML, uh, programming languages that lead you to have a graphical user interface on which you can then send your friends an email? Is that completely detached from the zeros and ones that are firing away inside the computer?

   20. DHDonald Hoffman10:01

       It's not, though, of course, when I talk about the user interface on your desktop, um, there's this whole sophisticated backstory to it, right? That, that the hardware and the software that's allowing that to happen. Evolution doesn't tell us the backstory, right? So the theory of evolution is not going to be adequate to tell you what is that backstory. It's gonna say that whatever reality is, and that's the interesting thing, it says whatever reality is, you don't see it. You see a user interface, but it doesn't tell you what that user interface is, how it's built, right? Now, we can, we can try to look at certain aspects of the interface, but already we're gonna look at that and go real... okay, before I would look at neurons and I was assuming that I was seeing something that was, uh, at least partially true, and now I'm realizing it, it could be like looking at the pixels on my desktop, uh, or icons on my desktop, and good luck, you know, going from that to the data structures and then the voltages and the... I mean, good luck. It, it... there's just n- no way. So what's interesting about this is that our scientific theories are precise enough and rigorous enough to tell us certain limits, but... and even limits of the theories themselves, but they're not going to tell us what the next move is. And that's where scientific creativity comes in. So the, the stuff that I'm saying here, for example, um, is not alien to physicists. The physicists are saying precisely the same thing that space time is doomed. We've assumed that space time is fundamental. We've assumed that for, for several centuries, and it's been very useful. So all the things that you are mentioning, the particles and all the work that's been done, that's all been done in space time. But now physicists are saying space time is doomed. There's no such thing as space time fundamentally in the laws of physics, and that comes actually out of gravity together with quantum field theory. It just comes right out of it. It's, it's, it's a theorem of, of, of those two theories put together, but it doesn't tell you what's behind it. So the physicists are... know that their, their best theories, Einstein's gravity and quantum field theory put together, is...... entail that spacetime cannot be fundamental and therefore, particles in spacetime cannot be fundamental. They're just irreducible representations of the symmetries of spacetime. That's what they are. So we have, so spacetime, so we put the two together. We put together what the physicists are discovering, and we can talk about how they do that, and then we, uh, the new discoveries from evolution by natural selection. Both of these discoveries are really in the last 20 years, and what both are saying

3. 12:40 – 37:04

   Spacetime

   1. DHDonald Hoffman12:40

      is, um, spacetime has had a good ride.

   2. LFLex Fridman12:43

      (chuckles)

   3. DHDonald Hoffman12:43

      It's been very useful. Reductionism has been useful, but it's over and it's time for us to go beyond.

   4. LFLex Fridman12:48

      When you say spacetime is doomed, is it the space? Is the, is the, is it the time? Is it the very hard-coded specification of four dimensions? Um, or are, are you specifically referring to the kind of, um, perceptual domain that humans operate in, which is spacetime? You think like there's a 3D, um, like our world is three-dimensional and time progresses forward, therefore three dimensions plus one, 4D. What, uh, what, what exactly do you mean by spacetime? What, when, (laughs) what, what do you mean by spacetime is doomed?

   5. DHDonald Hoffman13:24

      Great. Great. So this is, by the way, not my quote, this is from, for example, Nima Arkani-Hamed at the Institute for Advanced Study at Princeton, Ed Witten also there, David Gross, Nobel Prize winner. So this is not just something that cognitive scientists, this is what the physicists are saying.

   6. LFLex Fridman13:40

      Yeah. The physicists, they're spacetime, uh, skeptics.

   7. DHDonald Hoffman13:45

      Well, yeah, they're saying-

   8. LFLex Fridman13:46

      (laughs)

   9. DHDonald Hoffman13:46

      ... that, and I can say exactly why they think it's doomed, but what they're saying is that, you know, 'cause your question was, what, what aspect of spacetime, what are we talking about here? It's both space and time, their union into spacetime, a- as in Einstein's theory, that's doomed.

   10. LFLex Fridman14:00

       Mm-hmm.

   11. DHDonald Hoffman14:01

       And they're, they're basically saying that, uh, even quantum theory, uh, this is with Nima Arkani-Hamed especially. So Hilbert spaces will not be fundamental either. So that, that where the notion of Hilbert space, which is really critical to quantum field theory, quantum information theory, uh, that's not going to figure in the fundamental new laws of physics. So what they're looking for is some new mathematical structures beyond spacetime, beyond, you know, Einstein's four-dimensional spacetime or super symmetric version, you know, geometric algebra signature, two comma four kind of. Uh, there are different ways that you can represent it, but they're finding new structures. And, and, by the way, they're succeeding now. They're finding, they found something called the amplituhedron, this is Nima and his colleagues, the, the cosmological polytope. These are... So the- there are these like polytopes, these polyhedra in, in multi-dimensions, generalizations of simplices that are coding for, for example, the scattering amplitudes of, of processes in the Large Hadron Collider and other, other colliders. So they're finding that if they let go of spacetime completely, they're finding new ways of computing these scattering amplitudes that turn literally billions of terms into one term. When you do it in space and time, because it's the wrong framework, it's- it's- it's just a user interface from, that's now from the evolutionary point of view, it's just user interface, it's not a deep insight into the nature of reality. So it's missing deep symmetry is something called a dual conformal symmetry, which turns out to be true of the scattering data, but you can't see it in spacetime, and is making the compli- the computations way too complicated because you're trying to compute all the loops and Feynman diagrams and all the Feynman integrals. So see, the Feynman approach to the scattering amplitudes is trying to enforce two critical properties of spacetime, locality and unitarity. And so by, when you enforce those, you get all these loops and multiple, you know, different levels of loops. And for each of those, you have to add new terms to your computation. But when you do it outside of spacetime, you don't have the notion of unitarity, you don't have the notion of locality, you have something deeper and it's capturing some symmetries that are actually true of the data. And, but then when you look at the geometry of the facets of these polytopes, then certain of them will code for unitarity and, uh, locality. So it actually comes out of the structure of these deep polytopes. So what we're finding is there's this whole new world now beyond spacetime that is making explicit symmetries that are true of the data that cannot be seen in spacetime and that is turning the computations from billions of terms to one or two or a handful of terms. So we're getting insights into symmetries and we're... And all of a sudden the math is becoming simple because we're not doing something silly. We're not adding up all these loops in spacetime. We're doing something far deeper. But they don't know what this world is about. Also, you know, they're in an interesting position where we know that spacetime is doomed. And I, I, I should probably tell you why it's doomed, uh, what they're saying about why it's doomed, but, but they need a flashlight to look beyond spacetime. What is, what flashlight are we gonna use to look into the dark beyond spacetime? Because Einstein's theory and quantum theory can't tell us what's beyond them. All they can do is tell us that when you put us together, spacetime is doomed at 10 to the minus 33 centimeters, 10 to the minus 43 seconds, beyond that, spacetime doesn't even make sense. It just has no operational definition. So, but it doesn't tell you what's beyond. And so they're, they're just looking for deep structures, like guessing. It's really fun. So these really brilliant guys, generic, we have brilliant men and women who are doing this work-

   12. LFLex Fridman17:48

       Mm-hmm.

   13. DHDonald Hoffman17:48

       ... uh, physicists, are making guesses about these structures, informed guesses, because they're trying to ask, "Well, okay, what deeper structure could give us the stuff that we're seeing in spacetime, but without certain commitments that we have to make in spacetime, like locality So they make these brilliant guesses. And of course, most of the time you're gonna be wrong. But once you get one or two, that start to pay off. And then you get some lucky breaks. So they got a lucky break back in 1986. Um, a couple of mathematicians named Park and Taylor.... took the scattering amplitude for two gluons coming in at high energy and four gluons going out at low energy. So, that kind of scattering thing. So, so like, apparently for people w- who are into this, that's sort of something that happens so often you need to be able to find it and get rid of those, 'cause you already know about that and you need to... So, you needed to compute them. It was billions of terms. And they couldn't do it, even for the supercomputers, couldn't do that for the many billions or millions of times per second they needed to do it. So, they, they begged, you know, the experimentals begged the theorist, "Please, can you... I mean, you gotta..." And so Park and Taylor took the billions of terms, hundreds of pages, and miracli- miraculously turned it into nine, and then a little bit later, they guessed one term expression that turned out to be equivalent. So, billions of terms reduced to one term, the so-called famous Park-Taylor formula, 1986. And that was like, okay, where did that come from? What... This is a pointer into a deep realm beyond space and time, but, but no one... I mean, what can you do with it? And they thought maybe it was a one-off, but then other formulas started coming up and then eventually, Nima Arkani-Hamed and his team found this thing called the amplituhedron which really sort of captures the whole, a, a big part of the whole ball of wax. Um, I- I'm sure they would say, "No, there's plenty more to do." So, so I won't say they did it all, by any means. They're looking at the cosmological polytope as well. So, what's remarkable to me is that two pillars of modern science, quantum field theory with gravity on the one hand, and evolution by natural selection on the other, just in the last 20 years have very clearly said spacetime has had a good run, reductionism has been a fantastic methodology, so we had a great ontology of spacetime, a great methodology of reductionism. Now it's time for a new trick.

   14. LFLex Fridman20:09

       (laughs)

   15. DHDonald Hoffman20:10

       But now you need to go deeper. And, and show... But by the way, this isn't, doesn't mean we throw away everything we've done. N- not by a long shot. Every new idea that we come up with beyond spacetime must project precisely into spacetime and it better give us back everything that we know and love in spacetime or generalizations. Or it's not gonna be taken seriously, and it shouldn't be. So, so we have a strong constraint on whatever we're going to do beyond spacetime. It needs to project into spacetime. And whatever this deeper theory is, it may not itself have evolution by natural selection. This may not be part of this deeper realm. But when we take the, whatever that thing is beyond spacetime and project it into spacetime, it has to look like evolution by natural selection, or it's wrong. So, so that's, so that's a strong constraint on, on this work.

   16. LFLex Fridman20:57

       So, even the evolution by natural selection and, um, quantum field theory, uh, could be interfaces into something that n- that doesn't look anything like... Like you mentioned evol- I mean, it's interesting to think that evolution might be a very crappy interface into something much deeper.

   17. DHDonald Hoffman21:18

       That's right. They're both telling us that the framework that you've had can only go so far. And it has to stop. And there's something beyond. And that framework, th- the very framework that is, is spacetime itself. Now, of course, evolution by natural selection is not telling us, uh, about like Einstein's relativistic spacetime. So, that was another question you asked a little bit earlier. It's telling us more about our perceptual space and time, which, um, we have used as the basis for creating first a Newtonian space versus time as a mathemat- mathematical extension of our perceptions. And then Einstein then took that and extended it even further. So, the relationship between what evolution is telling us and what the physicists are telling us is that in some sense, the Newton and Einstein spacetime are formulated as sort of rigorous extensions of our perceptual space, um, making it mathematically rigorous and f- and laying out the symmetries that, that, that they find there. So, that's sort of the relationship between them. So, it's the perceptual spacetime that evolution is telling us is just a, a user interface, effectively, and then the physicists are finding that even the mathematical extension of that into the Einsteinian formulation has to be as well, um, not the final story. There's something deeper.

   18. LFLex Fridman22:38

       So, let me ask you about reductionism and interfaces. As we march forward from Newtonian physics, uh, to quantum mechanics, these are all, in your view, interfaces. Um, are we getting closer to objective reality? How do we know... If these interfaces in the process of science, the reason we like those interfaces is because they're predictive of some aspects, strongly predictive about some aspects of our reality. Is that completely deviating from our understanding of that reality? Or is it helping us get closer and closer and closer?

   19. DHDonald Hoffman23:22

       Well, of course, one critical constraint on all of our theories is that they are empirically tested and pass the experiments that we have for them. So, so no one's arguing against experiments being important and wanting to test all of our, our current theories and, uh, any new theories on that. So, that's, that's, that's all there. But we have good reason to believe that science will never get a theory of everything. In a sense-

   20. LFLex Fridman23:52

       Everything, everything.

   21. DHDonald Hoffman23:53

       Everything, everything. Right. A final theory of everything, right. I think that my, my own take is, for what it's worth, is that Godel's incompleteness theorem sort of points us in that direction. That e- even with mathematics, uh, any finite axiomatization that's sophisticated enough to be able to do arithmetic, it's easy to show that there'll be, um, statements that are true that can't be proven, can't be deduced from within that framework. And if you add the new statements to your axioms, then there'll be always new statements that are true but can't be proven with the new axiom system. And s-... the best scientific theories, um, in physics for example, and also now evolution, are mathematical. So our theories are gonna be- a- a- they're gonna have their own assumptions, and, um, they'll be mathematically precise, and there'll be theories perhaps of everything except those assumptions 'cause the assumptions are, we say, "Please grant me these assumptions. If you grant me these assumptions, then I can explain this other stuff." But, so you have the assumptions that, um, are like miracles as far as the theory is concerned. They're not explained. They're the starting points for explanation. And then you have the mathematical structure of the theory itself which will have the girdle limits. And so, my- my take is that, um, reality, whatever it is, is always going to transcend any conceptual theory that we can come up with.

   22. LFLex Fridman25:22

       There's- there's always gonna be mystery at the edges. Uh, (laughs) -

   23. DHDonald Hoffman25:27

       Right.

   24. LFLex Fridman25:27

       ... uh, contradictions and all that kind of stuff. Okay. (sighs)

   25. DHDonald Hoffman25:31

       And truths.

   26. LFLex Fridman25:32

       So there's a- this idea that was brought up in the- in the financial space of, uh, settlement of transactions. It's o- often talked about in cryptocurrency especially. So you could do, you know, money, cash, is not connected to anything. Uh, it used to be connected to gold, to physical reality, but then you can use money to exchange, uh, to exchange value, trans- transact. Uh, so when- when it was in the gold standard, eh, the money would represent some stable, uh, component of reality. Isn't it more effective to avoid things like hyperinflation if we generalize that idea? Isn't it better to connect your, uh, whatever we humans are doing in the social interaction space with each other, isn't it better, uh, from an evolutionary perspective to connect it to some degree to reality so that the- the- the transactions are settled with something that's universal as opposed to us constantly operating in something that's a complete illusion? Isn't it easy to hyperinflate that? (laughs) Like, where n- where you really-

   27. DHDonald Hoffman26:43

       (laughs)

   28. LFLex Fridman26:43

       ... deviate very, very far away from, um, from the underlying reality? Or do you not, never get in trouble for this? Can you just completely drift far, far away from the underlying reality and never get in trouble?

   29. DHDonald Hoffman27:01

       That's a great question. S- y- on the financial side, there's two levels at least th- that we could take your question. One- one is strictly like evolutionary psychology of financial systems. Um, and that's- that's pretty interesting. Um, and there, the decentralized idea, the De- DeFi kind of idea-

   30. LFLex Fridman27:17

       Mm-hmm.
4. 37:04 – 57:30

   Reductionism

   1. DHDonald Hoffman37:04

      over. Reductionism is in fact dead, as is space-time.

   2. LFLex Fridman37:08

      What exactly is reductionism? What is the process of reductionism that is different than, uh, some of the physicists that you mentioned there trying to think, trying to let go of the assumption of space-time, looking beyond? Isn't that still trying to come up with a simple model that explains this whole thing? Isn't it still reducing?

   3. DHDonald Hoffman37:29

      It's a wonderful question because it really helps to clarify two different notions, which is scientific explanation on the one hand and a particular kind of scientific explanation on the other, which is the reductionist. So the reductionist explanation is saying, "I will start with, with things that are smaller in space-time and, and therefore more fundamental, and, where the laws are more fundamental."

   4. LFLex Fridman37:50

      Mm-hmm.

   5. DHDonald Hoffman37:51

      So we go, uh, to just smaller and smaller scales. Whereas w- in science more generally, we just say, like when Einstein did the special theory of relativity, he's saying, "Let me have a couple postulates. I will assume that the speed of light is universal for, for all, um, observers, uh, in uniform motion, um, and that the laws of physics, so for, for, for, you know, uniform motion are, are those." That's not a reductionist. That, those are saying, "Grant me these assumptions. I can build this entire concept of space-time out of it." It's not a reductionist thing. You're not going to smaller and smaller scales of space. You're, you're coming up with these deep, deep principles. Same thing with his theory of gravity, right? It's, it's the falling elevator ide- idea, right? So this is not a reductionist kind of thing. It's, it's, it's, it's, it's something different. So s-

   6. LFLex Fridman38:40

      So simplification is a bigger thing than just reductionism?

   7. DHDonald Hoffman38:44

      That, yeah, r- reductionism has been a particularly useful kind of scientific explanation, for example, in thermodynamics, right, where the notion that we have of heat, some ma- macroscopic thing like temperature and heat. It turns out that, you know, Boltzmann and others discovered, well, hey, you know, if we go to smaller and smaller scales, we find these things called molecules or atoms. And if we think of them as bouncing around and having some kind of, um, energy, then, um, what we call heat is, is a, is really can be reduced to, to that. And, and so that's a particularly useful kind of e- um, reduction, is a useful kind of scientific explanation that works within a range of scales within space-time. But we know now precisely where that has to stop, at 10 to the minus 33 centimeters and 10 to the minus 43 seconds. And I would be impressed if it was 10 to the minus 33 trillion centimeters. I'm not terribly impressed at 10 to the minus 33 centimeters.

   8. LFLex Fridman39:41

      (laughs) I don't even know how to comprehend either of those numbers, frankly. Uh, do... Just a small aside-

   9. DHDonald Hoffman39:49

      (laughs)

   10. LFLex Fridman39:49

       ... 'cause I am a computer science person, I also find cellular automata beautiful.

   11. DHDonald Hoffman39:53

       Yes.

   12. LFLex Fridman39:54

       And, uh, so you have somebody like, uh, Stephen Wolfram, who recently has been very excitedly exploring, um, a proposal for a data structure that could be, uh, um, the numbers that would make you a little bit happier in terms of scale, 'cause they're very, very, very, very tiny. Um, so do you like this space of exploration, of really thinking, letting go of space-time, letting go of everything, and trying to think what kind of data structures could be underneath this whole mess?

   13. DHDonald Hoffman40:23

       That's right. So if they're thinking about these as outside of space-time, then that's th- that's what we have to do. That's what our best theories are telling us. You now have to think outside of space-time. Now, of course, I should back up and say we know that Einstein surpassed Newton, right? But that doesn't mean that there's not good work to do on Newton. There's all sorts of Newtonian physics that takes us to the moon and so forth, and there's lots of good problems that we want to d- solve with Newtonian physics. The same thing will be true of space-time. We'll, we'll still... It's not like we're gonna stop using space-time. We'll continue to do all sorts of good work there. But for, for those scientists who are really looking to go deeper, to actually find the next... You know, just like what Einstein did to Newton, what, what are we gonna do to Einstein? How do we get beyond Einstein and quantum theory to something deeper? Then we have to actually let go. And, and if we're gonna do, like, this a- a- automata kind of approach, it's, it's critical that it's not automata in space-time. It's automata prior to space-time from which we're going to show how space-time emerges. If you're doing automata within space-time, well, that might be a fun model, but it's not the radical new step that we need.

   14. LFLex Fridman41:33

       Yeah, so the space-time emerges from that whatever system. And y- uh, like you're saying, it's, it's a dynamical system. Do we even have an understanding of what dynamical means when we go beyond the, the... When, when you start to think about dynamics, that could mean a lot of things. Even causality could mean a lot of things if, if we, if we realize that everything's an interface. (laughs) Uh, like what...

   15. DHDonald Hoffman41:59

       Right.

   16. LFLex Fridman41:59

       How much do we really know is an interesting question, 'cause you, you brought up neurons. I gotta ask you an another, yet another tangent. There's a paper, I remember a while ago, looking at... called, uh, Could a Neuroscientist Understand a Microprocessor? And I just enjoyed that thought experiment-

   17. DHDonald Hoffman42:14

       Mm-hmm.

   18. LFLex Fridman42:14

       ... that they provided, which is they basically... It's a couple of, uh, neuroscientists, Eric Jonas and Konrad Kording, uh, who use the tools of neuroscience to analyze a microprocessor, so a computer, computer chip.

   19. DHDonald Hoffman42:30

       Yeah, if we lesion it here, what happens, and so forth. And if you go and-

   20. LFLex Fridman42:33

       Yeah.

   21. DHDonald Hoffman42:33

       ... lesion in, uh, you know, computer, it's very, very clear that lesion experiments on computers are not gonna give you a lot of insight into-

   22. LFLex Fridman42:39

       Yeah.

   23. DHDonald Hoffman42:39

       ... how it works.

   24. LFLex Fridman42:40

       And also the measurement devices and the kind of, sort of... Just using the basic approaches of neuroscience, collecting the data, uh, trying to intuit about the underlying function of it. And that helps you understand that...... our scientific exploration of concepts, um, depending on the field, uh, are, are, maybe in the very, very early stages. I wouldn't say in, leads us astray. Uh, perhaps it does sometimes. But it's not a, uh, it's not anywhere close to some fundamental mechanism that actually makes a thing work. I don't know if you can sort of comment on that-

   25. DHDonald Hoffman43:18

       Sure.

   26. LFLex Fridman43:18

       ... in terms of using neuroscience to understand the human mind and neurons. Are we really far away, potentially, from, uh, understanding in the way we understand the transistors enough to be able to build a computer? So one, one, uh, one thing about understanding is you can understand for fun. The other one is to, to understand so you could build things.

   27. DHDonald Hoffman43:45

       Right.

   28. LFLex Fridman43:45

       And, and that's when you really have to understand, (laughs) uh-

   29. DHDonald Hoffman43:49

       Exactly. In fact, what got me into the field that I'm at MIT was, um, work by David Marr on this very topic. So David Marr was a professor at MIT, but he'd done his PhD in neuroscience, studying just the architectures of the brain. But he realized that hi- his, his work, it was on the cerebellum. Um, he, he realized that his work, as, as, as rigorous as it was, left him unsatisfied because he didn't know what the cerebellum was for.

   30. LFLex Fridman44:18

       (laughs) Yeah.
5. 57:30 – 1:25:53

   Evolutionary game theory

   1. LFLex Fridman57:30

      c- because you mentioned evolutionary game theory, and that's really where you... the perspective from which you come, uh, uh, to form the case against reality.

   2. DHDonald Hoffman57:40

      Right.

   3. LFLex Fridman57:40

      Uh, at which point in our evolutionary history did we start to deviate the most from reality? Is it, uh, is it way before life even originated on Earth? Is it, um, in the early development from bacteria and so on? Or is it when some inklings of what we think of as intelligence or maybe even, uh, complex consciousness, uh, started to emerge? So where did this deviation... Um, just like with the interfaces on, in a computer, you know, you start with transistors and then you have, uh, assembly, and then you have, uh, C, C++, then you have Python, then you have GUIs, all that k-... you have layers upon layers. When did we start to deviate?

   4. DHDonald Hoffman58:33

      Well, David Marr, again my advisor at MIT, in his book Vision, suggested that the more primitive sensory systems were less realistic, less veridical. But that by the time you got to something as complicated as the humans, we were actually tr- estimating the true shapes and distances to objects and so forth. So, so his point of view, and I think it was probably... a- is not an un- uncommon view among my colleagues, that, that, yeah, the sensory systems of lower creatures may just not be complicated enough to give them much, much truth. Um, but as you get t- you know, to 86 billion neurons, you can now compute the truth, or at least the parts of the truth that we need. When w- when I look at evolutionary game theory, um, one of my graduate students, Justin Mauch, did some simulations using genetic algorithms. So there he was just exploring... Um, we started off with random organisms, random sen-

   5. LFLex Fridman59:33

      Wow.

   6. DHDonald Hoffman59:33

      ... sensory genetics and random actions, and first generation was unbelievably... there were... it was a foraging situation, they were foraging for resources, and most of them s- set, you know, stayed in one place, didn't do anything important, and, and... but we could then just look at how the genes evolved, and, and what we found was... what, what, what, what he found was that, uh, basically you never even saw the, the, the truth organisms even come on the stage. They, they, they, they... if they came, th- they were gone in one generation. They just, they just weren't... so they, they, they came and gone, th- they came and went, uh, even just in one generation. They, they just are not good enough. The ones that were just tracking... their senses just were tracking the fitness payoffs, were, were far more, um, fit than, than, um, the truth seekers. So from a... so an answer at, at one level... now I'm gonna give an answer at a deeper level, but just with evolutionary game theory, because my attitude as a scientist is, um, I don't believe any of our theories. I take them very, very seriously, I study them, I look at their implications, but none of them are the gospel. They're just the latest ideas that we have. And, you know... so the reason I study evolutionary game theory is because that's the best tool we have right now in this area. There's, there's, there is n- nothing else that competes. And so as a scientist it's my responsibility to take the best tools and see what they mean. And the same thing the physicists are doing. They're, they're taking the best tools and looking at what, what they entail. But I don't... I, I think that science now has enough experience to realize that we should not...... believe our theories, i- in the sense that we've now arrived. I- in 1890, it was a lot of physicists thought we'd arrived. They were discouraging, um, bright young students from going into physics because it was all done. And that's precisely the wrong attitude.

   7. LFLex Fridman1:01:31

      Yeah.

   8. DHDonald Hoffman1:01:31

      Forever.

   9. LFLex Fridman1:01:32

      (laughs)

   10. DHDonald Hoffman1:01:32

       It's the wrong attitude forever. It, we, the attitude we should have is, I, a- a century from now they'll be looking at us and laughing at what we didn't know, and we just have to assume that that's going to be the case. A c- just, just know that everything that we think is so brilliant right now, our final theory of everything, a century from now they'll look at us like we look at the physicists of 1890 and go, "How could they have been so dumb?"

   11. LFLex Fridman1:01:55

       Yeah.

   12. DHDonald Hoffman1:01:56

       So, so I don't wanna make that mistake. So, so I'm not doctrinaire about any of our current scientific theories. I am doctrinaire about this. We should use the best tools we have right now.

   13. LFLex Fridman1:02:08

       Mm-hmm.

   14. DHDonald Hoffman1:02:09

       That's what we've got.

   15. LFLex Fridman1:02:09

       And with, with humility. Well, l- so let me ask you about game theory. There's, um... I, I love game theory and, uh, evolution game theory, um, but I'm always suspicious of it, um, like economics. Um, when you construct models, it's too easy to construct things, uh, that oversimplify just, um, because we, our human brains enjoy the over- the simplification of constructing a few variables that somehow represent organisms or represent people and running a simulation that then allows you to build up intuition, and then it feels really good because you get, can get some really deep and surprising intuitions. But how do you know, uh, your models aren't... The assumptions underlying your models aren't some fundamentally flawed, and because of that, your conclusions are fundamentally flawed? So, I guess-

   16. DHDonald Hoffman1:03:04

       Yes.

   17. LFLex Fridman1:03:04

       ... my question is, what are the limits in your use of game theory, evolutionary game theory, your experience with it, what are the limits of game theory?

   18. DHDonald Hoffman1:03:12

       So I've gotten some pushback from professional colleagues and friends who have tried to rerun simulations and tried to... I mean, the, the idea that we don't see the truth is not comfortable, and so many of my colleagues are very interested in trying to show that we're wrong.

   19. LFLex Fridman1:03:26

       Mm-hmm.

   20. DHDonald Hoffman1:03:26

       And so the idea would be to say that somehow we did something, as you're suggesting, maybe something special that wasn't completely general. Um, we've got some little special part of the whole search space in evolutionary game theory in which this happens to be true, but more generally organisms would evolve to see the truth. So the, the best pushback we've gotten is from a team at Yale, and, uh, they suggested that, um, if you use thousands of payoff functions... So we, in, uh, our simulations we just use a couple-

   21. LFLex Fridman1:03:56

       Mm-hmm.

   22. DHDonald Hoffman1:03:57

       ... one or two, 'cause it was through our first simulations, right? So that would be a limit. We had one or two payoff functions. We showed th- the result in those, at least for the genetic algorithms. And they said if you have 20,000 of them, then we can find these conditions in which, um, truth see- seeing organisms would be the ones that, that evolved and, and survived. And so we looked at, at their simulations and, and it, it certainly is the case that you can find special cases in which truth can evolve. So when I say its probability is zero, it doesn't mean it can't happen.

   23. LFLex Fridman1:04:30

       Mm-hmm.

   24. DHDonald Hoffman1:04:30

       It, it can happen. In fact, it could happen infinitely often. It's just probability is zero. So if probability zero things can happen infinitely often.

   25. LFLex Fridman1:04:37

       Wha- when you say probability zero, you mean probability close to zero?

   26. DHDonald Hoffman1:04:42

       To be very, very precise, so for example, if I have a unit square, uh, on the plane, um, and I use a measure in which the, um, well, on... a probability measure in which the area of a region is this probability.

   27. LFLex Fridman1:04:56

       Mm-hmm.

   28. DHDonald Hoffman1:04:58

       Then if I draw a curve in that unit square, it has me- measured precisely zero. L- precisely, not approximately, precisely zero. And yet it has infinitely many points. So there is an object that, for that probability measure, has probability of zero, and yet there is infinitely, infinitely many points on it. So that's what I, what I mean by, when I say that the things that are probability zero can happen infinitely often in principle.

   29. LFLex Fridman1:05:21

       Yeah, but infinity as far as I... and I look outside often. I walk around, and I look at people. I have never seen infinity in real life.

   30. DHDonald Hoffman1:05:32

       That's an interesting i- issue.
6. 1:25:53 – 2:21:13

   Consciousness

   1. LFLex Fridman1:25:53

      the big topic of consciousness.

   2. DHDonald Hoffman1:25:55

      Okay.

   3. LFLex Fridman1:25:57

      This, this very beautiful, powerful things that perhaps is the thing that makes us human. What is it? What's the role of consciousness in, um, let's say even just the thing we've been talking about, which is the formation of this interface? Um, any kind of ways you want to kind of start-

   4. DHDonald Hoffman1:26:15

      Sure.

   5. LFLex Fridman1:26:16

      ... uh, trocking, talking about it?

   6. DHDonald Hoffman1:26:18

      Well, let me s- say first what most of my colleagues say. 99% are, again, assuming that space-time is fundamental, particles in space-time, matter is fundamental. And most are reductionist. And so the standard approach to consciousness is to figure out what complicated systems of matter with the right functional properties could possibly lead to the emergence of consciousness. That's the general idea, right? So maybe you have to have neurons. Maybe only if you have neurons, but that might not be enough. They have to, certain kinds of complexity in their, their organization and their dynamics, certain kind of network abilities, for example. So there's, there are those who say, for example, that, um, consciousness arises from orchestrated collapse of quantum states of microtubules and, and neurons. Certain-

Episode duration: 3:16:15