Manolis Kellis: Evolution of Human Civilization and Superintelligent AI | Lex Fridman Podcast #373

1. 0:00 – 1:28

   Introduction

   1. MKManolis Kellis0:00

      Maybe we shouldn't think of AI as our tool and as our assistant, maybe we should really think of it as our children. And the same way that you are responsible for training those children, but they are independent human beings, and at some point, they will surpass you. And, uh, this whole concept of alignment, of basically making sure that the AI is always at the service of humans, is very self-serving and very limiting. If instead you basically think about AI as a partner and AI as someone that shares your goals but has freedom, then we can't just simply force it to align with ourselves and we not align with it. So in a way, building trust is mutual. You can't just simply, like, train an intelligent system to love you when it realizes that you can just shut it off.

   2. LFLex Fridman0:54

      The following is a conversation with Manolis Kellis, his fifth time on this podcast. He's a professor at MIT and head of the MIT Computational Biology Group. He's one of the greatest living scientists in the world, but he's also a humble, kind, caring human being that I have the greatest of honors and pleasures of being able to call a friend. This is the Lex Fridman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Manolis Kellis.

2. 1:28 – 10:34

   Humans vs AI

   1. LFLex Fridman1:28

      Good to see you, first of all, Manolis.

   2. MKManolis Kellis1:29

      Lex, I've missed you. I think you've changed the lives of so many people that I know. And it's truly, like, uh, such a pleasure to be back, such a pleasure to see you grow, to sort of reach so many different aspects of your own personality.

   3. LFLex Fridman1:40

      Thank you for the love. You always give me-

   4. MKManolis Kellis1:41

      (laughs)

   5. LFLex Fridman1:42

      ... so much support and love, I just can't, I, I, I, I'm forever grateful for that.

   6. MKManolis Kellis1:45

      It's lovely to see a fellow human being who has that love, who basically does not judge people, and there's so many judgmental people out there, and it's just so nice to see this beacon of openness.

   7. LFLex Fridman1:57

      So what makes me, one instantiation of human irreplaceable, do you think? As we enter this increasingly capable, age of increasingly capable AI, I have to ask, what do you think makes humans irreplaceable?

   8. MKManolis Kellis2:10

      So humans are irreplaceable because of the baggage that we talked about. So we talked about baggage, we talked about the fact that every one of us has effectively re- relearned all of human civilization in their own way. So every single human has a unique set of genetic variants that they've inherited, some common, some rare, and some make us think differently, some make us have different personalities. They say that a, a parent with one child believes in genetics, a parent with multiple children understands genetics.

   9. LFLex Fridman2:42

      (laughs)

   10. MKManolis Kellis2:43

       Just how different kids are, and, and my three kids have dramatically different personalities ever since the beginning. So one thing that makes us unique is that every one of us has a different hardware. The second thing that makes us unique is that every one of us has a different software uploading of all of human society, all of human civilization, all of human knowledge. We don't, we're not born knowing it. We're not like, I don't know, uh, birds that learn how to make a nest through genetics and will make a nest even if they've never seen one.

   11. LFLex Fridman3:12

       Mm-hmm.

   12. MKManolis Kellis3:12

       We are constantly relearning all of human civilization. So that's the second thing. And the third one that actually makes humans very different from AI is that the baggage we carry is not experiential baggage, it's also evolutionary baggage.

   13. LFLex Fridman3:25

       Mm-hmm.

   14. MKManolis Kellis3:26

       So we have evolved through rounds of complexity. So just like ogres have layers and (laughs) Shrek has layers, humans have layers. There's the cognitive layer, which is sort of the outer, you know, most, the, the latest evolutionary innovation, this enormous neocortex that we have evolved, and then there's the emotional, uh, baggage underneath that, and then there's all of the fear and fright and flight and all of these kinds of behaviors. So AI only has a neocortex. AI doesn't have a limbic system. It doesn't have this complexity of human emotions, which make us so, I think, beautifully complex, so beautifully, uh, intertwined with our emotions, with our instincts, with our, you know, sort of gut reactions and all of that. So I think when humans are trying to suppress that aspect, the sort of, quote-unquote, more human aspect towards a more cerebral aspect, I think we lose a lot of the creativity, we lose a lot of the, you know, freshness of humans. And I think that's quite irreplaceable.

   15. LFLex Fridman4:33

       So we can look at the entirety of people that are alive today and maybe all humans who have ever lived-

   16. MKManolis Kellis4:39

       Yeah.

   17. LFLex Fridman4:39

       ... and mapped them in this high-dimensional space, and there's probably a, a center, uh, a center of mass for that mapping, and a lot of us deviate in different directions. So the, the variety of, uh, directions in which we all deviate from that center is vast.

   18. MKManolis Kellis4:56

       I would like to think that the center is actually empty.

   19. LFLex Fridman5:00

       Yes.

   20. MKManolis Kellis5:00

       That basically humans are just so diverse from each other that there's no such thing as an average human, that every one of us has some kind of complex baggage of emotions, intellectual, you know, motivational, uh, behavioral traits, that, um, it's not just one sort of normal distribution and we deviate from it. There's so, so many dimensions that we're kind of hitting the sort of sparseness, the, the curse of dimensionality, where it's actually quite sparsely populated. And I don't think you have an average human being.

   21. LFLex Fridman5:33

       So what makes us unique in part is the diversity and the capacity for diversity, and the capacity of the diversity comes from that entire evolutionary history, so there's just so many ways we can vary from each other.

   22. MKManolis Kellis5:50

       Yeah. I would say not just the capacity, but the inevitability of diversity. Basically, it's in our hardware. We are wired differently from each other. My siblings and I are completely different. My kids from each other are completely different. My, my, my wife has, she's like number two of six siblings. From, from a distance, they look the same, but then you get to, you know, you get to know them, every one of them is completely different.

   23. LFLex Fridman6:12

       ... but sufficiently the same that the differences interplay with each other. So, that's the interesting thing, where the diversity is functional, it's useful. So it's like we're close enough to where we notice the diversity and y- it doesn't, um, completely destroy the possibility of, like, effective communication and interaction. So it's, we're still the same kind of thing.

   24. MKManolis Kellis6:33

       So what I said in one of our earlier podcasts is that if humans realize that we're 99.9% identical, we would basically stop fighting with each other. (laughs) Like, we are really one human species and we are so, so similar to each other. And if you look at the alternative, if you look at the next thing outside humans, like, it's been six million years that we haven't had a relative. So it's, it's truly extraordinary that, that we're, we're kind of like this dot in outer space compared to the rest of life on Earth.

   25. LFLex Fridman7:07

       When you think about evolving through rounds of complexity, can you maybe elaborate? It's such a beautiful phrase, beautiful thought, that there's layers of complexity that make up a human being.

   26. MKManolis Kellis7:17

       So, so with software, sometimes you're like, "Oh, let's, like, build version two from scratch." But this doesn't happen in evolution. In evolution, you layer in additional features on top of old features. So basically when I, like, every single time my cells divide, I'm a yeast, like, I'm a unicellular organism. And then cell division is basically identical. Every time I breathe in and my lungs expand, I'm basically... You know, like, every time my heart beats, I'm a fish. So basically that, uh, I still have the same heart. Like, very, very little has changed. The blood going through my veins, the oxygen, the, you know, our immune system, we're basically primates. Our social behavior, we're basically new world monkeys and old world monkeys. We are basically... Um, this, this concept that every single one of these behaviors can be traced somewhere in evolution and that all of that continues to live within us is also a testament to not just not killing other humans, for God's sake, but, like, not killing other species either. Like, just to realize just how united we are with nature and that all of these biological processes have never ceased to exist. They're continuing to live within us. And then just the neocortex and all of the reasoning ca- capabilities of humans are built on top of all of these other species that continue to live, breathe, divide, metabolize, fight off pathogens, all continued inside us.

   27. LFLex Fridman8:46

       So you think the neocortex, the whatever reasoning is, that's the, the latest feature in the, in the latest version of this journey?

   28. MKManolis Kellis8:55

       It's, it's extraordinary that humans have evolved so much in so little time. Again, if you look at the, the timeline of evolution, you basically have billions of years to even get to a dividing cell, and then a multicellular organism, and then a complex body plan, and then these incredible senses that we have for perceiving the world. The fact that bats can fly, and they evolved flight, they evolved sonar, in the span of a few million years. I mean, it is just e- extraordinary how much evolution has kind of sped up. And all of that comes through this evolvability, the fact that we took a while to get good at evolving, and then once you get good at evolving, you can sort of, you have modularity built in, you have hierarchical organizations built in. You have all of these constructs that allow meaningful changes to occur without breaking the system completely. If you look at a traditional genetic algorithm, the way that humans designed them in the '60s, you can only evolve so much. And as you evolve a certain amount of complexity, the number of mutations that move you away from something functional exponentially increases.

   29. LFLex Fridman10:09

       Mm-hmm.

   30. MKManolis Kellis10:10

       And the number of mutations that move you to something better exponentially decreases. So the probability of evolving something so complex becomes infinitesimally small as you get more complex. But with evolution, it's almost the opposite, almost the exact opposite, that it appears that it's speeding up exactly as complec- complexity is increasing. And I think that's just the system getting good at evolving.

3. 10:34 – 32:18

   Evolution

   1. MKManolis Kellis10:34

   2. LFLex Fridman10:34

      Where do you think it's all headed? Do you ever think about where... Try to visualize the entirety of the evolutionary system and see if there's an arrow to it and, uh, a destination to it?

   3. MKManolis Kellis10:47

      So the best way to understand the future is to look at the past. If you look at the trajectory, then you can kind of learn something about the direction in which we're heading. And if you look at the trajectory of life on Earth, it's really about information processing. So the, the concept of the senses evolving one after the other, uh, you know, being, like, bacteria are able to do chemotaxis, basically means moving towards a chemical gradient. And that's the first thing that you need to sort of hunt down food. The next step after that is being able to actually perceive light. So all life on this planet and all life that we know about evolved on this rotating rock. Every 24 hours, you get sunlight and dark, sunlight and dark. And light is a source of energy, light is also information about where is up, light is all kinds of, you know, things. So you can, you can basically now start perceiving light and then perceiving shapes beyond just the sort of single photoreceptor. You can now have complex eyes or multiple eyes and then start perceiving motion or perceiving direction, perceiving shapes. And then you start building infrastructure on the cognitive apparatus to start processing this information and making sense of the environment, building more complex models of the environment. So if you look at that trajectory of evolution, what we're experiencing now... And humans are basically, according to this sort of information theoretic view of evolution, humans are basically the next natural step. And it's perhaps no surprise that we became the dominant species of the planet....because, yes, there's so many dimensions in which some animals are way better than we are. But at least on the cognitive dimension, we're just simply unsurpassed on this planet and, and perhaps the universe. But the, the concept that if you now trace this forward... We talked a little bit about evolvability and how things get better at evolving. One possibility is that the next layer of evolution builds the next layer of evolution. And what we're looking at now with humans and AI is that having mastered this information capability that humans have from this, quote-unquote, old hardware, this basically, you know, biological evolved system that kind of, you know, uh, somehow in the environment of Africa and then in subsequent environments was sort of dispersing through the globe, was evolutionarily advantageous. That has now created technology which now has a capability of solving many of these cognitive tasks. It doesn't have all the baggage of the previous evolutionary layers, but maybe the next round of evolution on Earth is self-replicating AI, where we're actually using our current smarts to build better programming languages and the programming languages to build, you know, ChatGPT, and that then build the next layer of software that will then sort of help AI speed up. And it's lovely that we're coexisting with this AI, that sort of the creators of this next layer of evolution in this next stage are still around to help guide it and hopefully will be for the rest of eternity as partners, but it's also nice to think about it as just simply the next stage of evolution, where you've kind of extracted away the biological needs. Like, if you look at animals, most of them spend 80% of their waking hours hunting for food or building shelter. Humans, maybe 1% of that time. And then the rest is left to creative endeavors. An AI doesn't have to worry about shelter, et cetera. So basically, it's all living in the cognitive space. So in a way, it might just be a very natural sort of next step to think about evolution. And that's, that's on the, on the sort of purely cognitive side. If you now think about humans themselves, the ability to understand and comprehend our own genome, again, the ultimate layer of introspection, gives us now the ability to even mess with this hardware, not just augment our capabilities through interacting and collaborating with AI, but also perhaps understand the neural pathways that are necessary for, you know, um, empathetic thinking, for, for justice, for this and this and that, and sort of help augment human capabilities through, n- you know, neuronal interventions, through chemical interventions, through electrical interventions, to basically help steer the human, you know, bag of hardware, that we kind of evolve with, into greater capabilities. And then ultimately, by understanding not just the wiring of neurons and the functioning of neurons, but even the genetic code, we could even, at one point in the future, start thinking about, well, can we get rid of psychiatric disease? Can we get rid of neurodegeneration? Can we get rid of dementia and start perhaps even augmenting human capabilities, not just getting rid of disease?

   4. LFLex Fridman15:56

      Can we tinker with the genome, with the hardware, or getting closer to the hardware without having to deeply understand the baggage? In the way we've disposed of the baggage in our software systems with AI, to some degree, not fully, but to some degree, can we do the same with the genome? Or is the genome deeply integrated into this baggage?

   5. MKManolis Kellis16:19

      I wouldn't want to get rid of the, the baggage. The baggage what makes us awesome. So the fact that I'm sometimes angry and sometimes hungry and sometimes hangry-

   6. LFLex Fridman16:27

      Yeah.

   7. MKManolis Kellis16:27

      ...um, is perhaps contributing to my creativity. I don't want to be dispassionate. I don't want to be another, like, you know, robot. I, you know, I want to get in trouble and I want to sort of say the wrong thing and I want to sort of, you know, make a- an awkward comment and sort of push myself into, you know, reactions and responses and things that can get just people thinking differently. And I, I think our society is moving towards a humorless, uh, space, where everybody's so afraid to say the wrong thing that people kind of start quitting en masse and start like not liking their jobs and stuff like that. Maybe we should be, uh, kind of embracing that human aspect a little bit more and all of that baggage aspect and, uh, not necessarily thinking about replacing it. On the contrary, like, embracing it and sort of this coexistence of the cognitive and the emotional hardwares.

   8. LFLex Fridman17:25

      So, uh, embracing and celebrating the diversity that, uh, springs from the baggage versus, uh, kind of, uh, pushing towards and empowering this kind of pull towards conformity.

   9. MKManolis Kellis17:42

      Yeah. And in fact, with the advent of AI, I would say, and these seemingly extremely intelligent systems that sort of can for- can perform tasks that we thought of as extremely intelligent at the blink of an eye, this might democratize intellectual pursuits. Instead of just simply wanting the same type of brains that, you know, carry out specific ways of thinking, we can... Like, instead of just always only wanting, say, the mathematically extraordinary to go to the same universities, what you could see, simply say is like, "Who needs that anymore?" You know, we now have AI.

   10. LFLex Fridman18:22

       Hmm.

   11. MKManolis Kellis18:23

       Maybe what we should really be thinking about is...... the diversity and the power that comes with the diversity, where AI can do the math, and then we should be getting a bunch of humans that sort of think extremely differently from each other, and maybe that's the true cradle of innovation.

   12. LFLex Fridman18:40

       But AI can also, these large language models, can also be with just a few prompts, essentially fine-tuned to be diverse from the center, so the prompts can really take you away into unique territory. You can ask the model to act in a certain way, and it will start to act in that way. Is that possible that, uh, the language models could also have some of the magical diversity that makes us so damn interesting?

   13. MKManolis Kellis19:08

       Yeah. So I would say humans are the same way. So basically, when you, when you sort of prompt humans to basically, you know, in a given environment, to act a particular way, they change their own behaviors. And, um, you know, the old saying is, "Show me your friends, and I'll tell you who you are." More like, "Show me your friends, and I'll tell you who you'll become."

   14. LFLex Fridman19:32

       Mm-hmm.

   15. MKManolis Kellis19:33

       So it's not necessarily that you choose friends that are like you, but, I mean, that's the first step, but then the second step is that, you know, th- the kind of behaviors that you find normal in your circles are the behaviors that you'll start espousing. And that type of meta evolution, where every action we take not only shapes our current action and the result of this action, but it also shapes our future actions by shaping the environment in which those future actions will be taken. Every time y- you carry out a particular behavior, it's not just a consequence for today, but it's also a consequence for tomorrow, because you're reinforcing that neural pathway.

   16. LFLex Fridman20:08

       Mm-hmm.

   17. MKManolis Kellis20:09

       So in a way, self-discipline is a self-fulfilling prophecy. And by behaving the way that you want to behave and choosing people that are like you and sort of exhibiting those behaviors that are sort of desirable, you end up creating that, that environment as well.

   18. LFLex Fridman20:31

       So i- it is a kind of, life itself is a kind of prompting mechanism, super complex, the, the friends you choose, the environments you choose, the way you modify the environment that you choose. Yes. But that seems like that process is much less efficient than a large language model. You can literally get a large language model through a couple of prompts to be a mix of Shakespeare and David Bowie, right? You can very aggressively change, in a way that's stable and convincing, you really transform, through a couple of prompts, the behavior of the model into something very different from the original.

   19. MKManolis Kellis21:14

       So well before ChatGPT-

   20. LFLex Fridman21:17

       Yeah.

   21. MKManolis Kellis21:17

       ... I would tell my students, "Just ask, you know, what would Manolis say right now?" And you, you guys all have a pretty good emulator of me right now.

   22. LFLex Fridman21:27

       Yes, yes.

   23. MKManolis Kellis21:27

       And I don't know if you know the programming paradigm of the rubber duckling, where you basically explain to the rubber duckling that's just sitting there-

   24. LFLex Fridman21:35

       Mm-hmm.

   25. MKManolis Kellis21:35

       ... exactly what you did with your code and why you have a bug, and just by the act of explaining, he'll kind of figure it out.

   26. LFLex Fridman21:42

       Yes.

   27. MKManolis Kellis21:43

       I woke up one morning from a dream where I was giving a lecture in this amphitheater, and one of my friends was basically giving me some deep evolutionary insight on how cancer genomes and cancer cells evolve. And I woke up with a very elaborate discussion that I was giving and a very elaborate set of insights that he had, that I was projecting onto my friend in my sleep, and obviously this was my dream, so (laughs) my own neurons were capable of doing that. But they only did that under the prompt of, "You are now Piyush Gupta. You are a professor in cancer genomics, you're an expert in that field, what do you say?" So I feel that we all have that inside us, that we have that capability of basically saying, "I don't know what the right thing is, but let me ask my virtual ex, 'What would you do?'" And virtual ex would say, "Be kind." And I'm like, "Oh, yes." (laughs) Or something like that.

   28. LFLex Fridman22:39

       Yes.

   29. MKManolis Kellis22:39

       And even though I myself might not be able to do it unprompted, and, uh, the, my favorite prompt is, "Think step by step." And I'm like, "You know, this also works on my 10-year-old." (laughs)

   30. LFLex Fridman22:50

       (laughs)
4. 32:18 – 44:47

   Nature vs Nurture

   1. MKManolis Kellis32:18

      I, I remember, like, watching my kids grow up, and again, like, yes, part of their personality has, stays the same, but also in different phases through their life, they've gone through these dramatically different types of behaviors. And, you know, my daughter basically saying, you know, basically one, one kid saying, "Oh, I want the bigger piece." The other one's saying, "Oh, everything must be exactly equal." And the third one's saying, "I'm okay."

   2. LFLex Fridman32:40

      Yeah.

   3. MKManolis Kellis32:40

      "You, you know, I'm happy to have the smaller part. Don't worry about me." (laughs)

   4. LFLex Fridman32:43

      Even in their early days, in their early days-

   5. MKManolis Kellis32:45

      Yeah.

   6. LFLex Fridman32:45

      ...of development?

   7. MKManolis Kellis32:45

      Yeah. Yeah. It's just extraordinary to sort of see these dramatically different, like, I mean, my wife and I, you know, are, are very different from each other, but we also have, you know, six million variants, six million loci each, if you wish, if you just look at common variants. We also have a bunch of rare variants that are inherited in more Mendelian fashion. And now you have, you know, an infinite possi- number of possibilities for each of the kids. So basically it's two to the sixth million just from the common variants, and then if you, like, layer in the, the rare variants. So let me talk a little bit about common variants and rare variants. So if you look at just common variants-

   8. LFLex Fridman33:22

      Mm-hmm.

   9. MKManolis Kellis33:23

      ...they're generally weak effect because selection selects against strong effect variants. So if something, like, has a big risk for schizophrenia, it won't rise to high frequency. So the ones that are common are, by definition, by selection, only the ones that had relatively weak effect. And if all of the variants associated with personality, with cognition, and all aspects of human behavior were weak effect variants, then kids would basically be just averages of their parents. If it was like thousands of loci, just by low law of large numbers, the average of two large numbers would be, you know, very robustly close to that middle. But what we see is that kids are dramatically different from each other. So that basically means that in the context of that common variation, you basically have rare variants that are inherited in a more Mendelian fashion, that basically then sort of govern likely many different aspects of human behavior, human biology, and human psychology. And that's, again, i- i- y- like if you look at sort of a person with schizophrenia, their identical twin has only 50% chance of actually being diagnosed with schizophrenia. So that basically means there's probably developmental exposures, environmental exposures, trauma, all kinds of other aspects that can shape that. And if you look at siblings, for the common variants, it kinda drops off exponentially as you would expect, with, you know, f- sharing 50% of your genome, 25% of your genome, you know, 12.5% of your genome, et cetera, with more and more distant cousins. But the fact that siblings can differ so much in their personalities that we observe every day, it can't all be nurture. Basically, you know, we, we f- like, again, as parents, we, we spend enormous amount of energy trying to "fix," quote unquote, the nurture part, trying to g- you know, get them to share, get them to be kind, get them to be open, get them to trust each other, like, you know, like overcome the prisoner's dilemma...

   10. LFLex Fridman35:22

       Mm-hmm.

   11. MKManolis Kellis35:23

       ...of, you know, if y- if everyone fends for themselves, we're all gonna live in a horrible place, but if we're a little more altruistic, then we're all gonna be in a better place. And I think it's not like we treat our kids differently, but, but they're, they're just born differently. So in a way, as a geneticist, (laughs) I have to admit that there's only so much I can do with nurture, that nature definitely plays a big component.

   12. LFLex Fridman35:45

       The, the selection of variants we have, the common variants and the rare variants... What, uh, what can we say about the landscape of possibility they create? If you can just linger on that. So the, the selection of ra- rare variants is, is defined how? How do we get the ones that we get? Is, is, is it just laden in that giant evolutionary baggage?

   13. MKManolis Kellis36:13

       So I'm gonna talk about regression, what do we call a regression-

   14. LFLex Fridman36:17

       Mm-hmm.

   15. MKManolis Kellis36:18

       ...and the concept of regression to the mean. The fact that when fighter pilots in a dogfight did amazingly well, they would give them rewards, and then the next time they're in a dogfight, they would do worse.

   16. LFLex Fridman36:32

       Mm-hmm.

   17. MKManolis Kellis36:32

       So then, you know, the Navy basically realized that, wow, this, or at least interpreted that as, "Wow, we're ruining them by praising them. And then they're gonna perform worse."The statistical interpretation of that is regression of the mean. The fact that you're an extraordinary pilot, you've been trained in an extraordinary fashion, that pushes your mean further and further to extraordinary achievement. And then in some dogfights, you'll just do extraordinarily well. The probability that the next one will be just as good is almost nil, because this is the peak of your performance. And just by statistical odds, the next one will be another sample from the same underlying distribution, which is gonna be a little closer to the mean. So regression analysis (laughs) takes its name from this type of realization in the statistical world. Now, if you now take, um, humans, you basically have people who have achieved extraordinary achievements. Uh, Einstein for example. You know, you would call him, for example, the epitome of human intellect. Does that mean that all of his children and grandchildren will be extraordinary geniuses? It probably means that their sample from the same underlying distribution, but he was probably a rare combination of extremes in addition to these common variants. So you can basically interpret your kids' variation, for example, as... Well, of course they're gonna be some kind of sampled from the average of the parents, with some kind of deviation according to the specific combination of rare variants that they ha- that they have inherited. So, you know, given all that, the op-, you know, the possibilities are endless as to sort of where sh- you should be, but you should always interpret that with, well, it's probably an alignment of nature and nurture. And the nature has both the common variants that are acting kind of like the law of large numbers and the rare variants that are acting more in a Mendelian fashion. And then you layer in the nurture, which again, in everyday action we make, we shape our future environment, but the genetics we inherit are shaping the future environment of not only us, but also our children. So there's this weird nature-nurture interplay and self-reinforcement where you're kind of shaping your own environment, but you're also shaping the environment of your kids. And your kids are gonna be born in the context of your environment that you've shaped, but also with a bag of genetic variants that they have inherited. And there's just so much complexity associated with that. When we start blaming something on nature, it might just be nurture. It might just be that, well, yes, they inherited the genes from the parents, but they also, you know, were shaped by the same environment. So it's very, very hard to untangle the two. And you should also always realize that nature can influence nurture, nurture can influence nature, or at least be correlated with and predictive of, and so on and so forth.

   18. LFLex Fridman39:37

       So I love thinking about that distribution that you mentioned, and here's where I can, uh, be my usual ridiculous self. And, um... I sometimes think about that army of sperm cells, however many hundreds of thousands there are, and I kind of think of all the possibilities there, because there's a lot of variation and one gets to win. I- is- is that a-

   19. MKManolis Kellis40:02

       It's not a random one.

   20. LFLex Fridman40:03

       Is- is it a totally ridiculous way to think about-

   21. MKManolis Kellis40:05

       No, not at all.

   22. LFLex Fridman40:06

       ... the... (laughs)

   23. MKManolis Kellis40:07

       So I would say, evolutionarily, we are a very slow evolving species. Basically, the generations of humans are a terrible way to do selection. What you need is processes that allow you to do selection in a smaller, tighter loop.

   24. LFLex Fridman40:22

       Yeah.

   25. MKManolis Kellis40:23

       And part of what... If- if you look at our immune system, for example, it evolves at a much faster pace than humans evolve, because there is actually an evolutionary process that happens within our immune cells as they're dividing. There's basically VDJ recombination that basically creates this extraordinary wealth of antibodies and antigens against the- the environment. And basically all these antibodies are now recognizing all these antigens from the environment, and they send signals back that cause these cells that recognize the non-self to multiply. So that basically means that even though viruses evolve at millions of times faster than we are, we can still have a component of our cells which is environmentally facing, which is sort of evolving at not the same scale, but very rapid pace. Sperm expresses perhaps the most proteins of any cell in the body. And part of the thought is that this might just be a way to check that the sperm is intact. In other words, if you waited until that human has a liver and starts eating solid food and, you know, sort of filtrates away, you know, uh, or- or kidneys or stomach, etc., basically, if you waited until these mutations, you know, manifest late, late in life, then you would end up not failing fast and you would end up with a lot of failed pregnancies and a lot of later onset, you know, psychiatric illnesses, etc. If instead you basically express all of these genes at the sperm level, and if they misform, they basically cause the sperm to cripple, then you have, at least on the male side, the ability to exclude some of those mutations. And on the female side, as the egg develops, there's probably a similar, uh, process where you could- you could sort of weed out eggs that are just not, you know, carrying beneficial mutations or at least that are carrying highly detrimental mutations. So you can basically think of the evolutionary process in a nested loop, basically, where there's an inner loop where you get many, many more iterations to- to run, and then there's an outer loop that moves at a much slower pace.And going back to, uh, the next step of evolution, of possibly designing systems that we can use to sort of complement our own biology or to sort of eradicate disease and you name it, or at least mitigate, uh, some of the, I don't know, psychiatric illnesses, neurodegenerative disorders, et cetera, you can basically... And also, you know, metabolic, immune, cancer, you name it. Simply engineering these mutations from rational design might be very inefficient. If instead you have ev- an evolutionary loop, where you're kind of growing neurons in a dish and you're exploring evolutionary space and you're sort of shaping that one protein to be better adapt that sort of, I don't know, recognizing light or communicating with other neurons, et cetera, you can basically have a smaller evolutionary loop that you can run, like, thousands of times faster than the speed it would take to evolve humans for another million years. So I think it's important to think about sort of this evolvability as a set of nested structures that allow you to sort of test many more combinations but in a more fixed setting.

   26. LFLex Fridman43:51

       Yeah, that's fascinating, that, so the mechanism there is, uh, for- for sperm to express proteins to create a testing ground early on, uh, so that the- the failed designs don't make it.

   27. MKManolis Kellis44:04

       Yeah. I- I- I mean, in design of engineering systems, fail fast is one of the principles you learn.

   28. LFLex Fridman44:09

       Yeah.

   29. MKManolis Kellis44:09

       Like basically you assert something. Why do you assert that? Because if that something ain't right, you better crash now than sort of let it crash at an unexpected time. And in a way you can think of it as like 20,000 assert functions. Assert protein can fold. Assert protein can fold.

   30. LFLex Fridman44:25

       Yeah.
5. 44:47 – 51:11

   AI alignment

   1. MKManolis Kellis44:47

      the first.

   2. LFLex Fridman44:47

      I should mention, as just a brief tangent back to the place where we came from-

   3. MKManolis Kellis44:51

      Yeah.

   4. LFLex Fridman44:51

      ... which is the base model, uh, that I mentioned for OpenAI, which is before the reinforcement learning with human feedback. And you kind of gave this metaphor of it being kind of like a psychiatric hospital.

   5. MKManolis Kellis45:02

      I like that because it's basically all of these different angles at once. Like you basically have the more extreme versions of human psyche.

   6. LFLex Fridman45:09

      So the interesting thing is... Well, I- I've talked with, uh, folks in OpenAI quite a lot, and they say it's extremely difficult to work with that model.

   7. MKManolis Kellis45:19

      Yeah. Kinda like it's extremely difficult to work with some humans.

   8. LFLex Fridman45:21

      The parallels there are very interesting, because once you run the alignment process, it's much easier-

   9. MKManolis Kellis45:26

      Yeah.

   10. LFLex Fridman45:26

       ... to interact with it.

   11. MKManolis Kellis45:27

       Yeah.

   12. LFLex Fridman45:28

       But it makes you wonder what the capacity, what the underlying capability of the human psyche is, as-

   13. MKManolis Kellis45:35

       Yeah.

   14. LFLex Fridman45:35

       ... in the same way that what is the underlying capability of a large language model?

   15. MKManolis Kellis45:38

       And remember earlier when I was basically saying that, um, part of the reason why it's so prompt malleable is because of that alignment problem, uh, th- that alignment work?

   16. LFLex Fridman45:48

       Mm-hmm.

   17. MKManolis Kellis45:49

       It's kind of nice that the engineers at OpenAI have the same interpretation that, you know, in fact, i- it is that. And, um, this whole concept of easier to work with... Um, I- I wish that we could work with more diverse humans in a way...

   18. LFLex Fridman46:11

       (laughs) Yes.

   19. MKManolis Kellis46:11

       And- and sort of that's one of the possibilities that I see with the advent of these large language models, the fact that it gives us the chance to both dial down friends of ours that we can't interpret or that are just too edgy-

   20. LFLex Fridman46:28

       Mm-hmm.

   21. MKManolis Kellis46:28

       ... to sort of really truly interact with, where you could have a real-time translator. Just the same way that you can translate English to Japanese or Chinese or Korean by like real-time adaptation-

   22. LFLex Fridman46:41

       Mm-hmm.

   23. MKManolis Kellis46:41

       ... you could basically suddenly have a conversation with your favorite extremist on either side of the spectrum and just dial them down a little bit. (laughs)

   24. LFLex Fridman46:51

       Of course, not you and I, but, uh, uh, you could, uh, have friends that is, uh, who's a complete asshole, uh, but it's a- a different base level, so you can-

   25. MKManolis Kellis47:01

       Yeah.

   26. LFLex Fridman47:01

       ... actually tune it down to like, okay, they're not actually being an asshole there-

   27. MKManolis Kellis47:04

       Yeah.

   28. LFLex Fridman47:04

       ... this is a, they're actually expressing love right now.

   29. MKManolis Kellis47:07

       Yeah.

   30. LFLex Fridman47:07

       It's just that they're, this is a, they-
6. 51:11 – 1:02:50

   Impact of AI on the job market

   1. MKManolis Kellis51:11

   2. LFLex Fridman51:11

      In what way do you think these large language models and the thing they give birth to in the AI space would change this human experience, the human condition, the things we've talked across many podcasts about that makes life so damn interesting and rich, love, fear, fear of death, all of it? Uh, if we could just begin kind of thinking about how does it change, for the good and the bad, the human condition?

   3. MKManolis Kellis51:46

      Human society is extremely complicated. We have come from a hunter-gatherer society to an agricultural and farming society, where the goal of most professions was to eat and to survive. And with the advent of agriculture, the ability to live together in societies, humans could suddenly be valued for different skills. If you don't know how to hunt but you're an amazing potterer, then you fit in society very well, because you can sort of make your pottery and you can barter it for rabbits that somebody else caught. And the person who hunts the rabbits doesn't need to make pots, because you're making all the pots. And that specialization of humans is what shaped modern society. And with the advent of currencies and governments and, you know, credit cards and Bitcoin, you basically now have the ability to exchange value for the kind of productivity that you have. So basically, I make things that are desirable to others, I can sell them and buy back food, shelter, et cetera. With AI, the concept of, "I am my profession," might need to be revised, because I defined my profession in the first place as something that humanity needed that I was uniquely capable of delivering.

   4. LFLex Fridman53:21

      Mm-hmm.

   5. MKManolis Kellis53:22

      But the moment we have AI systems able to deliver these goods, for example, writing a piece of software or making a self-driving car or interpreting the human genome, then that frees up more of human time for other pursuits.

   6. LFLex Fridman53:42

      Mm-hmm.

   7. MKManolis Kellis53:43

      This could be pursuits that are still valuable to society. I could basically be ten times more productive at interpreting genomes and do a lot more. Or I could basically say, "Oh, great, the interpreting genomes part of my job now only takes me 5% of the time instead of 60% of the time. So now I can do more creative things. I can explore not new career options, but maybe new directions for my research lab."

   8. LFLex Fridman54:08

      Mm-hmm.

   9. MKManolis Kellis54:09

      "I can sort of be more productive, contribute more to society." And if you look at this giant pyramid that we have built on top of the subsistence economy, what fraction of US jobs are going to feeding all of the US? Less than 2%. Basically, the gain in productivity is such that 98% of the economy is beyond just feeding ourselves. And that basically means that we kinda have built these system of interdependencies of needed or useful or valued goods that sort of make the economy run, that the vast majority of wealth goes to other......what we now call needs, but used to be wants.

   10. LFLex Fridman54:59

       Mm-hmm.

   11. MKManolis Kellis55:00

       So basically, I wanna fly a drone, I wanna buy a bicycle, I wanna buy a nice car, I wanna have a nice home, I wanna... et cetera, et cetera, et cetera. So... And, and then, sort of, what is my direct contribution to my eating? I mean, I'm, I'm doing research on the human genome. I mean, this will help humans, it will help all humanity, but how is that helping the person who's giving me poultry or (laughs) vegetables?

   12. LFLex Fridman55:22

       Mm-hmm.

   13. MKManolis Kellis55:22

       So, in a way, I see AI as perhaps leading to a dramatic rethinking of human society. If you think about sort of the economy being based on intellectual goods that I'm producing, what if AI can produce a lot of these intellectual goods and satisfies that need? Does that now free humans for more artistic expression, for more emotional maturing, for basically having a better work/life balance?

   14. LFLex Fridman55:51

       Mm-hmm.

   15. MKManolis Kellis55:51

       Being able to show up for your two hours of work a day, or two hours of work, like, three times a week, with, like, immense rest and preparation and exercise and you're sort of clearing your mind until you have these two amazingly creative ho- hours. You basically show up at the office as your AI is busy answering your phone call, making all your meetings, you know, revising all your papers, et cetera, and then you show up for those creative hours and you're like, "All right. Autopilot, I'm on." And then you can basically do so, so much more that you would perhaps otherwise never get to because you're so overwhelmed with these mundane aspects of your, of your job. So I feel that AI can truly transform the human condition from realizing that we don't have jobs anymore, we now have vocations. And there's this beautiful analogy of, uh, three people laying bricks. And somebody comes over and asks the first one, "What are you doing?" He's like, "Oh, I'm laying bricks." Second one, "What are you doing?" "I'm building a wall." And the third one, "What are you doing?" "I'm building this beautiful cathedral."

   16. LFLex Fridman56:54

       Mm-hmm.

   17. MKManolis Kellis56:55

       So in a way, the first one has a job, the last one has a vocation. And if you ask me, "What are you doing?" "Oh, I'm editing a paper," then I have a job. "What are you doing?" "I'm understanding human disease circuitry," I have a vocation.

   18. LFLex Fridman57:09

       Mm-hmm.

   19. MKManolis Kellis57:09

       So in a way, being able to allow us to enjoy more of our vocation by taking away, off-loading some of the job part of our daily activities.

   20. LFLex Fridman57:23

       So we all become the, the builders of cathedrals.

   21. MKManolis Kellis57:25

       Correct.

   22. LFLex Fridman57:28

       Yeah. And we follow intellectual pursuits, artistic pursuits. I wonder what... how that really changes at a scale of several billion people. Everybody playing in the space of ideas, in the space of creations.

   23. MKManolis Kellis57:43

       So ideas, maybe for some of us, maybe you and I are in the job of ideas, but other people are in the job of experiences.

   24. LFLex Fridman57:51

       Hm.

   25. MKManolis Kellis57:51

       Other job... other people in the job of emotions, of dancing, of creative, artistic expression, of, you know, skydiving, and you name it. So basically, these... Again, the beauty of human diversity is exactly that, that what rocks my boat might be very different from what rocks other people's boat. And what I'm trying to say is that maybe AI will allow humans to truly, like, not just look for, but find meaning, and sort of, you don't need to work.

   26. LFLex Fridman58:27

       Mm-hmm.

   27. MKManolis Kellis58:28

       But you need to keep your brain at ease, and the way that your brain will be at ease is by dancing and creating these amazing, you know, movements, or creating these amazing paintings, or creating, I don't know, something that, that sort of changes... that, that touches at least one person out there, that sort of shapes humanity through that process. And instead of working your, you know, mundane programming job where you, like, hate your boss and you hate your job and you say you hate that darn program, et cetera, you're like, "Well, I don't need that. I can, you know, off-load that and I can now explore something that will actually be more beneficial to hum- to humanity, because the mundane parts can be off-loaded."

   28. LFLex Fridman59:07

       I wonder if it localizes our... Uh... All the things you've mentioned, all the vocations. So y- you mentioned that you and I might be playing in the space of ideas, but there's two ways to play in the space of ideas.

   29. MKManolis Kellis59:21

       Mm-hmm.

   30. LFLex Fridman59:21

       Both of which we're currently engaging in.
7. 1:02:50 – 1:07:51

   Human gatherings

   1. LFLex Fridman1:02:50

      tangent, but you mentioned it, you put together salons with, um, gatherings, small human gatherings, with, uh, folks from MIT, Harvard, here in Boston, friends, colleagues. What's your vision behind that?

   2. MKManolis Kellis1:03:05

      So it's not just MIT people and it's not just Harvard people. We have artists, we have musicians, we have painters, we have dancers, we have cinematographers. We have so many different diverse folks. And the goal is exactly that, celebrate humanity. What, what is humanity? Humanity is the all of us. It's not the any one subset of us. And we live in such an amazing extraordinary moment in time where you can sort of bring people from such diverse professions all living under the same city. You know, we live in an extraordinary city where you can have extraordinary people who have gathered here from all over the world. So my father grew up in a village in a, in an island in Greece that didn't even have a high school. To go get a high school education, he had to move away from his home. My mother grew up in another small island in Greece. They did not have this environment that I am now creating for my children. My parents were not academics. They didn't have these gatherings. So I feel that, like, I feel so privileged as an immigrant to basically be able to offer to my children the nurture that my ancestors did not have. So Greece was under Turkish occupation until 1821. My dad's island was liberated in 1920. (laughs) So, like, they, they were under Turkish occupation for hundreds of years. These people did not know what it's like to be Greek, let alone go to an elite university or, you know, be surrounded by, by these extraordinary humans. So the way that I'm thinking about these gatherings is that I'm, I'm shaping my own environment, and I'm shaping the environment that my children get to grow up in. So I can give them all my love, I can give them all my parenting, but I can also give them an environment as immigrants that sort of we feel welcome here, that... I mean, my wife grew up in a farm in rural France. Her father was a farmer. Her mother was a schoolteacher. Like, for me and for my wife to be able to host these extraordinary individuals that we feel so privileged, so humbled by, is amazing. And, and, you know, um, I, I think it's celebrating the welcoming nature of America, the fact that it doesn't matter where you grew up. And many, many of our friends at these gatherings are immigrants themselves. They grew up in Pakistan, in, you know, all kinds of places around the world that are now able to sort of gather in one roof as human to human. No one is judging you for your background, for the color of your skin, for your profession. It's just everyone gets to raise their hands and ask ideas.

   3. LFLex Fridman1:06:02

      So celebration of humanity and, and a kind of gratitude for having traveled, uh, quite a long way to get here.

   4. MKManolis Kellis1:06:10

      And if you look at the diversity of topics as well. I mean, we had a schoolteacher present on teaching immigrants, a book called Making Americans. We had a presidential advisor to four different presidents, you know, come and, you know, talk about the changing of US politics.

   5. LFLex Fridman1:06:26

      Mm-hmm.

   6. MKManolis Kellis1:06:26

      We had a musician, a composer, from Italy, who lives in Australia, come and present his latest piece and fundraise.

   7. LFLex Fridman1:06:39

      Mm-hmm.

   8. MKManolis Kellis1:06:39

      We had painters come and sort of show their art and talk about it. We've had authors of books on leadership. We've had, you know, intellectuals like, um, Steven Pinker. And, um, it's just extraordinary, the, the breadth. And this, this crowd basically loves not just the diversity of, of the audience, but also the diversity of the topics. And the last few were with Scott Aaronson...

   9. LFLex Fridman1:07:06

      Mm-hmm.

   10. MKManolis Kellis1:07:07

       ...on AI and, uh, you know, alignment and all of that.

   11. LFLex Fridman1:07:11

       So a bunch of beautiful weirdos.

   12. MKManolis Kellis1:07:13

       Exactly. All of-

   13. LFLex Fridman1:07:14

       And beautiful human beings.

   14. MKManolis Kellis1:07:15

       All of the outcasts in one room. (laughs)

   15. LFLex Fridman1:07:17

       (laughs) And just like you said, basically every human is a kind of outcast, uh, in this sparse distribution far away from the center. But it's not recorded. It's just hu- a small human gathering.

   16. MKManolis Kellis1:07:30

       Just for the moment. Just for the moment. (laughs)

   17. LFLex Fridman1:07:33

       In this world that seeks to record so much, uh, it's, it's, it's powerful to get so many interesting humans together and not, and not record.

   18. MKManolis Kellis1:07:43

       It, it's not recorded, but it percolates.

   19. LFLex Fridman1:07:45

       (laughs) It's recorded in, in the minds of the-

   20. MKManolis Kellis1:07:48

       It shapes everyone's mind.

8. 1:07:51 – 1:17:55

   Human-AI relationships

   1. MKManolis Kellis1:07:51

   2. LFLex Fridman1:07:51

      So allow me to please return to the human condition, and, uh, one of the nice features of the human condition is love. Do you think humans will fall in love with AI systems and maybe they with us? So that aspect of the human condition, do you think that will be affected?

   3. MKManolis Kellis1:08:12

      So in Greece, there's many, many words for love.

   4. LFLex Fridman1:08:15

      Mm-hmm.

   5. MKManolis Kellis1:08:15

      And some of them mean friendship, some of them mean passionate love, some of them mean fraternal love, et cetera. So, um, I think AI doesn't have the baggage that we do, and it doesn't have, you know, all of the subcortical regions that we kind of, you know, started with before we evolved all of the cognitive aspects. So I would say AI is faking it when it comes to love. But when it comes to friendship, when it comes to being able to be your therapist, your coach, your motivator, someone who synthesizes stuff for you, who writes for you, who interprets a complex passage, who compacts down a very long lecture or a very long text, I think that friendship will definitely be there. Like, the, the fact that I can have my companion, my partner, my AI who has grown to know me well and that I can trust with all of the darkest parts of myself, all of my flaws, all of the stuff that I, I only talk about to my friends and basically say, "Listen, you know, here's all this stuff that, that I'm struggling with." Someone who will not judge me, who will always be there to better me, in, in some ways, not having the baggage might make for your best friend, for your, you know, your confidant, uh, that, that can truly help reshape you. So I do believe that human-AI relationships will absolutely be there, but not the passion, more the mentoring.

   6. LFLex Fridman1:09:54

      Well, this a really interesting thought, to play devil's advocate. If those AI systems are locked in, in faking the baggage-

   7. MKManolis Kellis1:10:05

      Mm-hmm.

   8. LFLex Fridman1:10:06

      ... who are you to say that the AI systems that begs you not to leave it, who are, doesn't love you, who are you to say that this AI system that writes poetry to you, that, uh, is afraid of death, afraid of life without you, um, or vice versa, what, you know, creates the kind of drama that humans create, the, the power dynamics that can exist in a relationship, what about an AI system that is on- abusive one day and romantic the other day, all the different variations of relationships, and it's consistently that it holds the full richness of a particular personality, why is that not a system you can love in a romantic way? Why is it faking it if it sure as hell seems real?

   9. MKManolis Kellis1:10:52

      There's many answers to this. The first is, it's only in the eye of the beholder. Who tells me that I'm not faking it either? Maybe all of these subcortical systems that make me sort of have different emotions, maybe they don't really matter. Maybe all that matters is the neocortex and that's where all of my emotions are encoded, and, uh, the rest is just, you know, bells and whistles. Um, that's one possibility. And, and therefore, you know, who am I to judge that he's faking it when maybe I'm faking it as well? The second is, neither of us is faking it. Maybe it's just an emergent behavior of these neocortical systems that is truly capturing the same exact essence of love and hatred and dependency and sort of, you know, reverse psychology and, um, th- that, that, that we have. So it is possible that it's simply an emergent behavior and that we don't have to encode these additional architectures, that all we need is more parameters. And some of these parameters can be all of the personality traits. A third option is that just by telling me, oh, look, now I've built an emotional component to AI, it has a limbic system, it has a lizard brain, et cetera, and suddenly, I'll say, oh, cool, it has the capability of emotion. So now, when it exhibits the exact same unchanged behaviors that it does without it, I, as the beholder, will be able to sort of attribute to it emotional attributes-

   10. LFLex Fridman1:12:30

       Mm-hmm.

   11. MKManolis Kellis1:12:30

       ... that I would to another human being, and therefore, have that mental model of that other person. So again, I think a lot of relationships is about the mental models that you project on the other person and that they're projecting on you. And, um, then, yeah, then in that respect, I do think that even without the embodied intelligence part, without having ever experienced what it's like to be heartbroken, the sort of cultural feeling of misery, um, that that system, you know, I could still attribute it traits of human feelings and emotions.

   12. LFLex Fridman1:13:17

       And in the interaction with that system, something like love emerges. So it's possible that love is not a thing that exists in your mind, but a thing that exists in the, uh, interaction of the different mental models you have of other people's minds or other person's mind. And so...You, you know, it doesn't, as long as one of the entities... Let's just take the easy case. One of the entities is human and the other is AI, it feels very natural, that from the perspective of at least the human, there is a real love there. And then the question is, how does that transform human society? If it's possible that, which I believe will be the case, I don't know what to make of it, but I believe that'll be the case, where there's hundreds of millions of romantic partnerships between humans and AIs. What does that mean for society?

   13. MKManolis Kellis1:14:13

       If you look at longevity and if you look at happiness and if you look at late life, you know, well-being, the love of another human is one of the strongest indicators of health into long life. And I have many, many countless stories where as soon as the romantic partner of 60 plus years, of a person dies, within three, four months, the other person dies. Just like losing their love. I think the concept of being able to satisfy that emotional need that humans have, even just as a mental health sort of service, uh, to me, you know, that's, that's a very good society. (laughs) It doesn't matter if your love is "wasted," quote unquote, on a machine. It is, you know, the placebo, if you wish, that makes the patient better anyway. Like there's nothing behind it, but just the feeling that you're being loved will probably engender all of the emotional attributes of that. The other story that I want to say in this whole concept of faking it, and maybe I'm a terrible dad-

   14. LFLex Fridman1:15:21

       (laughs)

   15. MKManolis Kellis1:15:21

       ... but I was asking my kids, (laughs) I was asking my, my kids, I'm like, "Does it matter if I'm a good dad or does it matter if I act like a good dad?" (laughs) In other words, if I give you love and shelter and kindness and warmth and all of the above, you know, does it matter that I'm a good dad? Conversely, if I deep down love you to the end of eternity, but I'm always gone-

   16. LFLex Fridman1:15:49

       Yeah.

   17. MKManolis Kellis1:15:50

       ... which, which dad would you rather have? The cold, ruthless killer that will show you only love and warmth and nourish you and nurture you, or the amazingly warmhearted but works five jobs and you never see them? (sighs) (laughs)

   18. LFLex Fridman1:16:06

       And what's the answer? I mean, from the-

   19. MKManolis Kellis1:16:08

       I don't know the answer. (laughs)

   20. LFLex Fridman1:16:09

       I think from a, I think you're a romantic, so you say it matters what's on the inside, but pragmatically speaking, why does it matter? (laughs)

   21. MKManolis Kellis1:16:17

       The fact that I'm even asking the, asking the question basically says it's not enough to love my kids. I better freaking be there to show them that I'm there. So basically, of course, you know, everyone's a good guy in their story.

   22. LFLex Fridman1:16:29

       Yeah.

   23. MKManolis Kellis1:16:29

       So in my story, I'm a good dad. But if I'm not there, it's wasted. So the reason why I asked the question is for me to say, you know, does it really matter that I love them if I'm not there to show it?

   24. LFLex Fridman1:16:43

       But it's also possible that what reality is, is the you showing it, that what you feel on the inside is, is little narratives and games you play inside your mind, it doesn't really matter. That the thing that truly matters is how you act, and that AI systems can, quote unquote, "fake."

   25. MKManolis Kellis1:17:04

       Yeah. Yeah.

   26. LFLex Fridman1:17:04

       And that, if it's all that matters, is actually real but not fake.

   27. MKManolis Kellis1:17:08

       Yeah. Yeah. Again, let there be no doubt, I love my kids to pieces, but, you know, my, my worry is, am I being a good enough dad?

   28. LFLex Fridman1:17:18

       Yeah.

   29. MKManolis Kellis1:17:18

       And what does that mean? Like if I'm only there to do their homework and make sure that they, you know, do all the stuff, but I don't show it to them, then, you know, might as well be a terrible dad. But I agree with you that like if the AI system can basically play the role of a father figure for many children that don't have one, or, you know, the role of parents or the role of siblings, if a child grows up alone, maybe their emotional state will be very different than if they grow up with an AI sibling.

   30. LFLex Fridman1:17:50

       Well, let me ask you, I mean, this is for, for your, for your kids, for, for just loved ones in general.

9. 1:17:55 – 1:30:21

   Being replaced by AI

   1. LFLex Fridman1:17:55

      Let's, let's go to, like, the trivial case of just texting back and forth. What if we create a large language model, fine-tune a Manolis, and while you're at work, it'll replace... Every once in a while, you'll just activate the auto Manolis and it'll, it'll text them exactly in your way. Is that, is that cheating?

   2. MKManolis Kellis1:18:22

      I can't wait. (laughs)

   3. LFLex Fridman1:18:24

      (laughs)

   4. MKManolis Kellis1:18:24

      I mean, it's the same guy.

   5. LFLex Fridman1:18:26

      I cannot wait. Seriously, like...

   6. MKManolis Kellis1:18:28

      But wait, wouldn't that have a big impact on you emotionally? Because now-

   7. LFLex Fridman1:18:32

      I'm replaceable. I love that. (laughs) No seriously, I would love that. I would love to be replaced. I would love to be replaceable. I would love to have a digital twin that, you know, we don't have to wait for me to, to die or to disappear in a plane crash or something, um, to, to replace me. Like I'd love that model to be constantly learning, constantly evolving, adapting with every one of my changing, growing self. Uh, as, as I'm growing, I want that AI to grow, and I think this will be extraordinary. Number one, when I'm, you know, giving advice, being able to be there for more than one person, you know? Why does someone need to be at MIT to get advice from me? Like, you know, people in India could download it and, you know, so many, so many students contact me from across the world who want to come and spend a summer with me. I wish they could do that, (laughs) all of them, like, you know, we, we don't have room for all of them, but I wish I could do that to all of them. And, um, that, that aspect is the democratization of, of relationships. I think that, that is extremely beneficial. The other aspect is I want to interact with that system. I want to look inside the hood. I want to sort of evaluate it. I want to basically see if...

   8. MKManolis Kellis1:19:52

      ... when I see it from the outside, the emotional parameters are off, or the cognitive parameters are off, or the set of ideas that I'm giving are not quite right anymore.

   9. LFLex Fridman1:20:01

      Mm-hmm.

   10. MKManolis Kellis1:20:02

       I want to see how that system evolves. I want to see the impact of exercise or sleep-

   11. LFLex Fridman1:20:06

       Mm-hmm.

   12. MKManolis Kellis1:20:07

       ... on sort of my own cognitive system. I want to be able to sort of decompose my own behavior in a set of parameters that are gonna evaluate and look at my own personal growth. I can sort of, I'd love to sort of, at the end of the day, have my model say, "Well, you know, you didn't quite do well today." Like, you know, "You, you, you weren't quite there." And sort of grow from that experience. And I, I, I think the concept of basically being able to become more aware of our own personalities, become more aware of our own identities, maybe even interact with ourselves and sort of hear how we are being perceived, I think would be immensely helpful in self-growth, in self-actualization, self-instantiation.

   13. LFLex Fridman1:20:50

       The experiments I would do on that thing, because one of the challenges, of course, is you might not like what you see in your interaction. And you might say, "Well, it's the model, it's not accurate."

   14. MKManolis Kellis1:21:01

       (laughs)

   15. LFLex Fridman1:21:01

       But then you have to, should probably consider the possibility the ma- the model is accurate (laughs) and that there's actually flaws in your mind. I would definitely prod and see how many biases I have of different kinds. I don't know. And I would, of course, go to the extremes. I would go like, um, how jealous can I make this thing?

   16. MKManolis Kellis1:21:20

       (laughs)

   17. LFLex Fridman1:21:21

       Like what, what, at which stages does it get super jealous, you know? Or at which stage does it get angry? Can I like provoke it? Can I get it like completely-

   18. MKManolis Kellis1:21:29

       Yeah, what are your triggers?

   19. LFLex Fridman1:21:31

       What, yeah, k- but not only triggers, can I get it to go like lose its mind? (laughs)

   20. MKManolis Kellis1:21:35

       Yeah.

   21. LFLex Fridman1:21:35

       Like go completely nuts.

   22. MKManolis Kellis1:21:37

       Just don't exercise for a few days. (laughs)

   23. LFLex Fridman1:21:40

       (laughs) Basically. That's basically it, yes. Uh, I mean, that, that's a, that's an interesting way to prod yourself, almost like a, a self-therapy session.

   24. MKManolis Kellis1:21:50

       And, and the beauty of such a model is that if I am replaceable, if the parts that I currently do are replaceable, that's amazing, because it frees me up to work on other parts that I don't currently have time to develop. Maybe all I'm doing is giving the same advice over and over and over again.

   25. LFLex Fridman1:22:07

       Mm-hmm.

   26. MKManolis Kellis1:22:07

       Like, just let my AI do that, and I can work on the next stage and the next stage and the next stage. So I think in terms of freeing up, like ... (laughs) they say a programmer is someone who cannot do the same thing twice. (laughs) So, so the second time you write a program to do it. And I wish I could do that for my own existence. I could just like, you know, figure out things, keep improving, improving, improving, and once I've nailed it, let the AI loose on that. And maybe even let the AI better it, better than I could have.

   27. LFLex Fridman1:22:36

       But doesn't the concept of, you said me and I can work on new things, but doesn't that, uh, break down? Because you said digital twin, but there's no reason it can't be millions ...

   28. MKManolis Kellis1:22:51

       Yeah.

   29. LFLex Fridman1:22:51

       ... of digital Manolises.

   30. MKManolis Kellis1:22:52

       Yeah.

Episode duration: 2:30:27