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

Manolis Kellis 0:00 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.

Lex Fridman 0:54 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.

Lex Fridman 1:28 Good to see you, first of all, Manolis.

Manolis Kellis 1:29 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.

Lex Fridman 1:40 Thank you for the love. You always give me-

Manolis Kellis 1:41 (laughs)

Lex Fridman 1:42 ... so much support and love, I just can't, I, I, I, I'm forever grateful for that.

Manolis Kellis 1:45 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.

Lex Fridman 1:57 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?

Manolis Kellis 2:10 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.

Lex Fridman 2:42 (laughs)

Manolis Kellis 2:43 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.

Lex Fridman 3:12 Mm-hmm.

Manolis Kellis 3:12 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.

Lex Fridman 3:25 Mm-hmm.

Manolis Kellis 3:26 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.

Lex Fridman 4:33 So we can look at the entirety of people that are alive today and maybe all humans who have ever lived-

Manolis Kellis 4:39 Yeah.

Lex Fridman 4:39 ... 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.

Manolis Kellis 4:56 I would like to think that the center is actually empty.

Lex Fridman 5:00 Yes.

Manolis Kellis 5:00 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.

Lex Fridman 5:33 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.

Manolis Kellis 5:50 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.

Lex Fridman 6:12 ... 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.

Manolis Kellis 6:33 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.

Lex Fridman 7:07 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.

Manolis Kellis 7:17 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.

Lex Fridman 8:46 So you think the neocortex, the whatever reasoning is, that's the, the latest feature in the, in the latest version of this journey?

Manolis Kellis 8:55 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.

Lex Fridman 10:09 Mm-hmm.

Manolis Kellis 10:10 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.

Lex Fridman 10:34 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?

Manolis Kellis 10:47 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?

Lex Fridman 15:56 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?

Manolis Kellis 16:19 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-

Lex Fridman 16:27 Yeah.

Manolis Kellis 16:27 ...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.

Lex Fridman 17:25 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.

Manolis Kellis 17:42 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.

Lex Fridman 18:22 Hmm.

Manolis Kellis 18:23 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.

Lex Fridman 18:40 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?

Manolis Kellis 19:08 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."

Lex Fridman 19:32 Mm-hmm.

Manolis Kellis 19:33 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.

Lex Fridman 20:08 Mm-hmm.

Manolis Kellis 20:09 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.

Lex Fridman 20:31 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.

Manolis Kellis 21:14 So well before ChatGPT-

Lex Fridman 21:17 Yeah.

Manolis Kellis 21:17 ... 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.

Lex Fridman 21:27 Yes, yes.

Manolis Kellis 21:27 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-

Lex Fridman 21:35 Mm-hmm.

Manolis Kellis 21:35 ... 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.

Lex Fridman 21:42 Yes.

Manolis Kellis 21:43 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.

Lex Fridman 22:39 Yes.

Manolis Kellis 22:39 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)

Lex Fridman 22:50 (laughs)

Manolis Kellis 22:51 When he tries to solve a math equation all in one step, I know exactly what mistake he'll make. But if I prompt it with, "Oh, please think step by step," then he sort of gets in a mindset. And I think it's also part of the way that ChatGPT was actually trained, this whole sort of human in the loop-

Lex Fridman 23:07 Mm-hmm.

Manolis Kellis 23:08 ... reinforcement learning, has probably reinforced these types of behaviors, whereby having this feedback loop, you kind of aligned AI better to the prompting opportunities by humans.

Lex Fridman 23:23 Yeah, prompting human-like reasoning steps, the step by step kind of thinking. Yeah, but it does seem to be... I suppose it just puts a mirror to our own capabilities and so we can be truly impressed by our own, uh, cognitive capabilities, because the variety of what you can try. Because we don't usually have this kind of... We can't play with our own mind rigorously, uh, through Python code, right?

Manolis Kellis 23:50 Yeah.

Lex Fridman 23:50 (laughs) So this allows us to really play with, um, all, all of human wisdom and knowledge, or at least knowledge, at our fingertips, and then mess with that little mind that can think and speak in all kinds of ways.

Manolis Kellis 24:03 What's unique is that, as I mentioned earlier, every one of us was trained by a different subset-

Lex Fridman 24:08 Yeah.

Manolis Kellis 24:08 ... of-

Lex Fridman 24:09 That's right.

Manolis Kellis 24:09 ... human culture. And ChatGPT was trained on all of it.

Lex Fridman 24:14 Yeah.

Manolis Kellis 24:14 And the difference there is that it probably has the ability to emulate almost any, every one of us.

Lex Fridman 24:20 Yeah.

Manolis Kellis 24:21 The fact that you can figure out where that is in cognitive behavioral space just by a few prompts is pretty impressive.

Lex Fridman 24:27 Mm-hmm.

Manolis Kellis 24:28 But the fact that that exists somewhere is, you know, absolutely beautiful. And...The fact that it's encoded in an orthogonal way from the knowledge, I think is also beautiful. The fact that somehow, through this extreme over-parameterization of AI models, it was able to somehow figure out that context, knowledge, and form are separable.

Lex Fridman 24:53 Mm-hmm.

Manolis Kellis 24:53 And that you can sort of describe, uh, scientific knowledge in a haiku, in the form of, I don't know-

Lex Fridman 24:58 Yeah.

Manolis Kellis 24:58 ... Shakespeare or something. That tells you something about the un- the decoupling-

Lex Fridman 25:04 Okay.

Manolis Kellis 25:04 ...and the decouplability of these types of aspects of human psyche.

Lex Fridman 25:09 And as part of the science of this whole thing, so these large language models are, you know, days old, in terms of this kind of leap that they have taken. And it'll be interesting to do this kind of analysis on them, of conte- of the separation of context, form, and knowledge. Where exactly does that happen?

Manolis Kellis 25:26 Yeah.

Lex Fridman 25:26 There's already sort of initial investigations, but it's very hard to figure out where... Is there a particular, uh, parameter, set of parameters that are responsible for a particular piece of knowledge or particular context or particular style of speaking?

Manolis Kellis 25:40 So with convolutional neural networks, interpretability had many good advances-

Lex Fridman 25:46 Mm-hmm.

Manolis Kellis 25:47 ... because we can kind of understand them. There's a structure to them.

Lex Fridman 25:50 Yeah.

Manolis Kellis 25:50 There's a locality to them. And we can kind of understand the different layers have different sort of ranges that they're looking at. So we can look at activation features and basically see where, you know, where does that correspond to. With large language models, it's perhaps a little more complicated, but I think it's still achievable, in the sense that we could kind of ask, "Well, what kind of prompts does this generate? If I sort of drop out this part of the network-

Lex Fridman 26:15 Mm-hmm.

Manolis Kellis 26:16 ... then what happens?" And sort of start getting at a language to even describe these types of aspects of human be- behavioral psychology, if you wish, from the spoken part, in the language part. And the advantage of that is that it might actually teach us something about humans as well.

Lex Fridman 26:35 Huh.

Manolis Kellis 26:35 Like, you, you know, we might not have words to describe these types of aspects right now, but when somebody speaks in a particular way, it might remind us of a friend that we know from here and there and there. And if we had better language for describing that, these concepts might become more apparent in our own human psyche, and then we might be able to encode them better in machines themselves.

Lex Fridman 26:54 I mean, both probably you and I would have certain interests with the base model, with OpenEchoes, the base model, which is before the, the alignment of the reinforcement learning with human feedback and, and before the AI safety-based kind of censorship of the model. It would be fascinating to explore, to, uh, investigate the ways that the model can generate hate speech, the kind of hate that humans are capable of. It would be fascinating or the kind of, uh, of course, like, uh, sexual language or the kind of romantic language or the all kinds of ideologies. Can I get it to be a communist? Can I get it to be a fascist? Can I get it to be a capitalist? Can I get it to be all these kinds of things and see which parts get activated and not? Because it would be fascinating to sort of explore at the individual mind level and at a societal level where do these ideas, um, take hold? What is the fundamental core of those ideas? Maybe the communism, fascism, capitalism, democracy are all actually connected by the fact that the human heart, the human mind is drawn to ideology, to, to a centralizing idea. And maybe we need a neural network to remind us of that.

Manolis Kellis 28:15 I like the concept that the human mind is somehow tied to ideology, and I think that goes back to y- y- the, the promptability of ChatGPT. The fact that you can kind of say, "Well, think in this particular way now," and the fact that humans have invented words for encapsulating these types of behaviors. And it's hard to know how much of that is innate and how much of that was, like, passed on from language to language. But basically, if you look at the evolution of language, you can kind of see how young are these words in the history of language evolution that describe these types of behaviors, like, you know, kindness and anger and jealousy, et cetera. If these words are very similar from language to language, it might suggest that they're very ancient. If they're very different, it might suggest that this concept may have emerged independently in each different language and so on and so forth. So looking at the phylogeny, the history, the evolutionary traces of language at the same time as people moving around that we can now trace thanks to genetics is a fascinating way of understanding the human psyche and also understanding sort of how these types of behaviors emerge, and to go back to your idea about sort of exploring the system unfiltered, I mean, in a way, s- psychiatric hospitals are full of those pe- full of those people. So basically people whose mind is uncontrollable.

Lex Fridman 29:48 Yes.

Manolis Kellis 29:49 Who have kind of gone adrift in specific locations of their psyche. And I, I do find this fascinating. I basically, you know, watching movies that are trying to capture the essence of troubled minds, I think is teaching us so much about our everyday selves, because many of us are able to sort of control our minds and are able to h- some high- somehow hide these emotions. And but every time I see somebody who's troubled, I, I see versions of myself, maybe not as extreme, but I can sort of empathize with these behaviors. And, you know, I see bipolar, I see schizophrenia, I s- I see depression, I see autism, I see so many different aspects that we kind of have names for and crystallized in specific individuals.And I think all of us have that. All of us have sort of just this multidimensional brain and genetic variations that push us in these directions, environmental exposures and traumas that push us in these directions, environmental behaviors that are reinforced by the kind of friends that we chose or friends that we were stuck with because of the environments that we grew up in. So in a way, a lot of these types of behaviors are within the vector span...

Lex Fridman 31:15 Mm-hmm.

Manolis Kellis 31:15 ...of every human. It's just that the magnitude of those vectors is generally smaller for most people because they haven't inherited that particular set of genetic variants or because they haven't been exposed to those environments basically.

Lex Fridman 31:30 Or something about the mechanism of reinforcement learning with human feedback didn't quite work for them. So it's fascinating to think about that's what we do. We have this capacity to have all these psychra- psychiatric or, uh, behaviors associated with psychiatric disorders.

Manolis Kellis 31:46 Yeah.

Lex Fridman 31:46 But we, through the alignment process as we grow up with our parents-

Manolis Kellis 31:50 That's exactly right.

Lex Fridman 31:50 ...we kind of, (laughs) we know to suppress them.

Manolis Kellis 31:53 Yeah.

Lex Fridman 31:53 We know to, how to control them.

Manolis Kellis 31:54 Every human that grows up in this u- in this world spends several decades being shaped into place.

Lex Fridman 32:02 Yeah.

Manolis Kellis 32:02 And without that, you know, maybe we would have the unfiltered ChatGPT-4. (laughs)

Lex Fridman 32:08 Every baby is basically, uh, a raging narcissist.

Manolis Kellis 32:12 (laughs) Not all of them, not all of them, believe it or not. It's, it's, it's remarkable. Like,

Manolis Kellis 32:18 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."

Lex Fridman 32:40 Yeah.

Manolis Kellis 32:40 "You, you know, I'm happy to have the smaller part. Don't worry about me." (laughs)

Lex Fridman 32:43 Even in their early days, in their early days-

Manolis Kellis 32:45 Yeah.

Lex Fridman 32:45 ...of development?

Manolis Kellis 32:45 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-

Lex Fridman 33:22 Mm-hmm.

Manolis Kellis 33:23 ...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...

Lex Fridman 35:22 Mm-hmm.

Manolis Kellis 35:23 ...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.

Lex Fridman 35:45 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?

Manolis Kellis 36:13 So I'm gonna talk about regression, what do we call a regression-

Lex Fridman 36:17 Mm-hmm.

Manolis Kellis 36:18 ...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.

Lex Fridman 36:32 Mm-hmm.

Manolis Kellis 36:32 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.

Lex Fridman 39:37 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-

Manolis Kellis 40:02 It's not a random one.

Lex Fridman 40:03 Is- is it a totally ridiculous way to think about-

Manolis Kellis 40:05 No, not at all.

Lex Fridman 40:06 ... the... (laughs)

Manolis Kellis 40:07 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.

Lex Fridman 40:22 Yeah.

Manolis Kellis 40:23 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.

Lex Fridman 43:51 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.

Manolis Kellis 44:04 Yeah. I- I- I mean, in design of engineering systems, fail fast is one of the principles you learn.

Lex Fridman 44:09 Yeah.

Manolis Kellis 44:09 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.

Lex Fridman 44:25 Yeah.

Manolis Kellis 44:25 And if any of them fail, that sperm is gone.

Lex Fridman 44:28 Well, I just like the fact that I'm the winning sperm.

Manolis Kellis 44:30 (laughs)

Lex Fridman 44:30 I'm the result of the- the winner, winning, hashtag winning.

Manolis Kellis 44:34 My- my wife always plays me this French song that actually sings about that. It's like, you know, "Remember, in life, we were all the first one time." (laughs)

Lex Fridman 44:45 (laughs) So at least once, we won.

Manolis Kellis 44:45 At least one time, you were

Manolis Kellis 44:47 the first.

Lex Fridman 44:47 I should mention, as just a brief tangent back to the place where we came from-

Manolis Kellis 44:51 Yeah.

Lex Fridman 44:51 ... 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.

Manolis Kellis 45:02 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.

Lex Fridman 45:09 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.

Manolis Kellis 45:19 Yeah. Kinda like it's extremely difficult to work with some humans.

Lex Fridman 45:21 The parallels there are very interesting, because once you run the alignment process, it's much easier-

Manolis Kellis 45:26 Yeah.

Lex Fridman 45:26 ... to interact with it.

Manolis Kellis 45:27 Yeah.

Lex Fridman 45:28 But it makes you wonder what the capacity, what the underlying capability of the human psyche is, as-

Manolis Kellis 45:35 Yeah.

Lex Fridman 45:35 ... in the same way that what is the underlying capability of a large language model?

Manolis Kellis 45:38 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?

Lex Fridman 45:48 Mm-hmm.

Manolis Kellis 45:49 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...

Lex Fridman 46:11 (laughs) Yes.

Manolis Kellis 46:11 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-

Lex Fridman 46:28 Mm-hmm.

Manolis Kellis 46:28 ... 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-

Lex Fridman 46:41 Mm-hmm.

Manolis Kellis 46:41 ... 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)

Lex Fridman 46:51 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-

Manolis Kellis 47:01 Yeah.

Lex Fridman 47:01 ... actually tune it down to like, okay, they're not actually being an asshole there-

Manolis Kellis 47:04 Yeah.

Lex Fridman 47:04 ... this is a, they're actually expressing love right now.

Manolis Kellis 47:07 Yeah.

Lex Fridman 47:07 It's just that they're, this is a, they-

Manolis Kellis 47:08 They have their way of- of doing that.

Lex Fridman 47:09 And they probably live in New York, uh, if we're just to pick a random location.

Manolis Kellis 47:14 So- so the, yeah, so you can basically layer out contexts. You can basically say, "Ooh, let me change New York to Texas, and let me change, you know, uh, extreme left to extreme right, or somewhere in the middle, or something." And, um, I also like the concept of being able to, um, listen to the information without being dissuaded by the emotions.

Lex Fridman 47:39 Hmm.

Manolis Kellis 47:39 In other words, everything humans say has an intonation, has some kind of background that they're coming from, reflects the way that they're thinking of you, reflects the impression that they have of you, and all of these things are intertwined. But being able to disconnect them, being able to sort of... I mean, self-improvement is one of the things that I'm constantly working on, and being able to receive criticism from people who really hate you is difficult, because it's layered in with that hatred. But deep down, there's something that they say that actually makes sense. Or people who love you might layer it in a way that doesn't come through. But if you're able to sort of disconnect that emotional component from the sort of self-improvement-

Lex Fridman 48:29 Mm-hmm.

Manolis Kellis 48:30 ... and basically when somebody says, "Whoa, that was a bunch of bullshit, did you ever do the control this and this and that?"

Lex Fridman 48:37 Mm-hmm.

Manolis Kellis 48:38 You could just say, "Oh, thanks for the very interesting presentation. Uh, you know, I'm wondering, what about that control?" Then suddenly you're like, "Oh, yeah, of course, I'm gonna run that control. That's a great idea."

Lex Fridman 48:47 Yeah.

Manolis Kellis 48:48 Instead of, "That was a bunch of BS," you're like, "Ugh!" You're sort of hitting on the brakes and you're trying to push back against of that. So...... any kind of criticism that comes after that is very difficult to interpret in a positive way, because it helps reinforce the negative assessment of your work.

Lex Fridman 49:04 Mm-hmm.

Manolis Kellis 49:05 When in fact, if we disconnected the technical component from the negative assessment, then you're embracing the negative, th- then you're embracing the technical component, you're gonna fix it. Whereas if it's coupled with, "And if that thing is real and I'm right about your mistake, then it's a bunch of BS," then suddenly you're like, you're gonna try to prove that that mistake does not exist.

Lex Fridman 49:29 Yeah. It's fascinating to, like, carry the information. And this is what you're essentially able to do here, is you carry the information in the rich complexity that information contains.

Manolis Kellis 49:38 Mm-hmm. Mm-hmm.

Lex Fridman 49:38 So it's not actually dumbing it down in some way.

Manolis Kellis 49:40 Exactly.

Lex Fridman 49:41 You're still expressing it, but taking off...

Manolis Kellis 49:43 But you can (stutters) the emotional...

Lex Fridman 49:46 The emotion side.

Manolis Kellis 49:46 Yeah.

Lex Fridman 49:47 Which is probably so powerful for the internet or for social networks.

Manolis Kellis 49:51 Again, when it comes to understanding each other, one of, like for example, I don't know what it's like to go through life with a different skin color. I don't know how people will perceive me. I don't know how people will respond to me. We don't often have that experience. But in a virtual re- reality environment or in a sort of AI interactive system, you could basically say, "Okay. Now make me Chinese," or, "Make me South African," or, "Make me, you know, uh, Nigerian."

Lex Fridman 50:20 Mm-hmm.

Manolis Kellis 50:21 You can change the accent. You can change layers of that contextual information and then see how the information is interpreted. And you can re-hear yourself through a different angle. You can hear others. You can have others react to you from a different package. And then hopefully we can sort of build empathy by learning to disconnect all of these s- social cues that we get from, like, how a person is dressed, you know, i- if they're wearing a hoodie or if they're wearing a shirt or if they're wearing a, you know, jacket. You get very different emotional responses that, you know, I wish we could overcome as humans. And perhaps large language models and augmented reality and deep fakes can kind of help us overcome all that.

Lex Fridman 51:11 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?

Manolis Kellis 51:46 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.

Lex Fridman 53:21 Mm-hmm.

Manolis Kellis 53:22 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.

Lex Fridman 53:42 Mm-hmm.

Manolis Kellis 53:43 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."

Lex Fridman 54:08 Mm-hmm.

Manolis Kellis 54:09 "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.

Lex Fridman 54:59 Mm-hmm.

Manolis Kellis 55:00 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?

Lex Fridman 55:22 Mm-hmm.

Manolis Kellis 55:22 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?

Lex Fridman 55:51 Mm-hmm.

Manolis Kellis 55:51 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."

Lex Fridman 56:54 Mm-hmm.

Manolis Kellis 56:55 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.

Lex Fridman 57:09 Mm-hmm.

Manolis Kellis 57:09 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.

Lex Fridman 57:23 So we all become the, the builders of cathedrals.

Manolis Kellis 57:25 Correct.

Lex Fridman 57:28 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.

Manolis Kellis 57:43 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.

Lex Fridman 57:51 Hm.

Manolis Kellis 57:51 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.

Lex Fridman 58:27 Mm-hmm.

Manolis Kellis 58:28 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."

Lex Fridman 59:07 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.

Manolis Kellis 59:21 Mm-hmm.

Lex Fridman 59:21 Both of which we're currently engaging in.

Manolis Kellis 59:22 Mm-hmm.

Lex Fridman 59:23 So one is the communication of that to other people. It could be a classroom full of students, but it could be a podcast, it could be something that's, uh, that's shown on YouTube and so on. Or it could be just the act of sitting alone and playing with ideas in your head, or maybe with a loved one having a conversation that nobody gets to see.

Manolis Kellis 59:44 Yeah.

Lex Fridman 59:44 The experience of just sort of looking up at the sky and wondering different things, maybe quoting some philosophers from the past and playing with those little ideas, and that little exchange is forgotten forever, but you got to experience it, and maybe... We will... I wonder if it localizes that exchange of ideas, but that, with AI, it'll become less and less valuable to communicate with a large group of people, that you will live life intimately and, and richly just with that circle of meatbags that you seem to love.

Manolis Kellis 1:00:19 So the first is, even if you're alone in a forest having this amazing thought, when you exit that forest, the baggage that you carry has been shifted, has been altered by that thought. When I bike to work in the morning, I listen to books. And I'm alone, no one else is there. I'm having that experience by myself. And yet, in the evening when I speak with someone, an idea that was formed there could come back. Sometimes when I fall asleep, I fall asleep listening to a book.

Lex Fridman 1:00:53 Yeah.

Manolis Kellis 1:00:53 And in the morning, I'll be full of ideas that I never even processed consciously. I'll process them unconsciously. And they will shape that baggage that I carry.... that will then shape my interactions, and again, affect ultimately all of humanity in some butterfly effect, minute kind of way. So that's one aspect. The second aspect is gatherings. So basically you and I are having a conversation which feels very private.

Lex Fridman 1:01:22 Mm-hmm.

Manolis Kellis 1:01:22 But we're sharing with the world. And then later tonight, you're coming over...

Lex Fridman 1:01:27 Mm-hmm.

Manolis Kellis 1:01:27 ...and we're having a conversation that will be very public, with dozens of other people, but we will not share with the world.

Lex Fridman 1:01:33 Yeah.

Manolis Kellis 1:01:34 (laughs) So in a way, which one's more private? The one here or the one there? Here, there's just two of us, but a lot of others listening. There, a lot of people speaking and thinking together and bouncing off each other. And maybe that will then impact your millions of, you know, uh, audience...

Lex Fridman 1:01:52 Mm-hmm.

Manolis Kellis 1:01:52 ...through your next conversation.

Lex Fridman 1:01:56 Mm-hmm.

Manolis Kellis 1:01:56 And I think that's part of the beauty of humanity. The fact that no matter how small, how alone, how broadcast immediately or later on something is, it still percolates through the human psyche.

Lex Fridman 1:02:11 Human gatherings. All throughout human history, there's been gatherings. I, I wonder how those gatherings have impacted the direction of human civilization. Just, uh, thinking of in the early days of the Nazi party, it was a small collection of people gathering. And the, uh, the kernel of an idea, in that case an evil idea, uh, gave birth to something that actually had a transformative impact on all of human civilization. And then there's similar kind of gatherings that lead to positive transformations. Um, this, this is probably a good moment to ask you, on a bit of a

Lex Fridman 1:02:50 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?

Manolis Kellis 1:03:05 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.

Lex Fridman 1:06:02 So celebration of humanity and, and a kind of gratitude for having traveled, uh, quite a long way to get here.

Manolis Kellis 1:06:10 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.

Lex Fridman 1:06:26 Mm-hmm.

Manolis Kellis 1:06:26 We had a musician, a composer, from Italy, who lives in Australia, come and present his latest piece and fundraise.

Lex Fridman 1:06:39 Mm-hmm.

Manolis Kellis 1:06:39 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...

Lex Fridman 1:07:06 Mm-hmm.

Manolis Kellis 1:07:07 ...on AI and, uh, you know, alignment and all of that.

Lex Fridman 1:07:11 So a bunch of beautiful weirdos.

Manolis Kellis 1:07:13 Exactly. All of-

Lex Fridman 1:07:14 And beautiful human beings.

Manolis Kellis 1:07:15 All of the outcasts in one room. (laughs)

Lex Fridman 1:07:17 (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.

Manolis Kellis 1:07:30 Just for the moment. Just for the moment. (laughs)

Lex Fridman 1:07:33 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.

Manolis Kellis 1:07:43 It, it's not recorded, but it percolates.

Lex Fridman 1:07:45 (laughs) It's recorded in, in the minds of the-

Manolis Kellis 1:07:48 It shapes everyone's mind.

Lex Fridman 1:07:51 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?

Manolis Kellis 1:08:12 So in Greece, there's many, many words for love.

Lex Fridman 1:08:15 Mm-hmm.

Manolis Kellis 1:08:15 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.

Lex Fridman 1:09:54 Well, this a really interesting thought, to play devil's advocate. If those AI systems are locked in, in faking the baggage-

Manolis Kellis 1:10:05 Mm-hmm.

Lex Fridman 1:10:06 ... 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?

Manolis Kellis 1:10:52 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-

Lex Fridman 1:12:30 Mm-hmm.

Manolis Kellis 1:12:30 ... 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.

Lex Fridman 1:13:17 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?

Manolis Kellis 1:14:13 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-

Lex Fridman 1:15:21 (laughs)

Manolis Kellis 1:15:21 ... 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-

Lex Fridman 1:15:49 Yeah.

Manolis Kellis 1:15:50 ... 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)

Lex Fridman 1:16:06 And what's the answer? I mean, from the-

Manolis Kellis 1:16:08 I don't know the answer. (laughs)

Lex Fridman 1:16:09 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)

Manolis Kellis 1:16:17 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.

Lex Fridman 1:16:29 Yeah.

Manolis Kellis 1:16:29 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?

Lex Fridman 1:16:43 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."

Manolis Kellis 1:17:04 Yeah. Yeah.

Lex Fridman 1:17:04 And that, if it's all that matters, is actually real but not fake.

Manolis Kellis 1:17:08 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?

Lex Fridman 1:17:18 Yeah.

Manolis Kellis 1:17:18 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.

Lex Fridman 1:17:50 Well, let me ask you, I mean, this is for, for your, for your kids, for, for just loved ones in general.

Lex Fridman 1:17:55 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?

Manolis Kellis 1:18:22 I can't wait. (laughs)

Lex Fridman 1:18:24 (laughs)

Manolis Kellis 1:18:24 I mean, it's the same guy.

Lex Fridman 1:18:26 I cannot wait. Seriously, like...

Manolis Kellis 1:18:28 But wait, wouldn't that have a big impact on you emotionally? Because now-

Lex Fridman 1:18:32 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...

Manolis Kellis 1:19:52 ... 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.

Lex Fridman 1:20:01 Mm-hmm.

Manolis Kellis 1:20:02 I want to see how that system evolves. I want to see the impact of exercise or sleep-

Lex Fridman 1:20:06 Mm-hmm.

Manolis Kellis 1:20:07 ... 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.

Lex Fridman 1:20:50 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."

Manolis Kellis 1:21:01 (laughs)

Lex Fridman 1:21:01 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?

Manolis Kellis 1:21:20 (laughs)

Lex Fridman 1:21:21 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-

Manolis Kellis 1:21:29 Yeah, what are your triggers?

Lex Fridman 1:21:31 What, yeah, k- but not only triggers, can I get it to go like lose its mind? (laughs)

Manolis Kellis 1:21:35 Yeah.

Lex Fridman 1:21:35 Like go completely nuts.

Manolis Kellis 1:21:37 Just don't exercise for a few days. (laughs)

Lex Fridman 1:21:40 (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.

Manolis Kellis 1:21:50 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.

Lex Fridman 1:22:07 Mm-hmm.

Manolis Kellis 1:22:07 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.

Lex Fridman 1:22:36 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 ...

Manolis Kellis 1:22:51 Yeah.

Lex Fridman 1:22:51 ... of digital Manolises.

Manolis Kellis 1:22:52 Yeah.

Lex Fridman 1:22:52 Wh- are- aren't you lost in the sea of Manolises? The original, uh, is hardly the original. It's just one of millions.

Manolis Kellis 1:23:02 I, I want to have the room to grow. Maybe the new version of me, that, that, that's the actual me, will get slightly worse sometimes-

Lex Fridman 1:23:12 Hm.

Manolis Kellis 1:23:12 ... slightly better other times. When it gets slightly better, I'd like to emulate that and have a much higher standard to meet.

Lex Fridman 1:23:18 Mm-hmm.

Manolis Kellis 1:23:19 And keep going.

Lex Fridman 1:23:20 But does it make you sad that your loved ones, the physical, real loved ones might kinda like start cheating on you with the other Manolises? (laughs)

Manolis Kellis 1:23:31 I, I, I want to be there 100% of them, for each of them.

Lex Fridman 1:23:34 (laughs)

Manolis Kellis 1:23:35 So I, I, yeah, I have zero perks, uh, or zero, zero quer- qualms about me being physically me. Like, zero jealousy.

Lex Fridman 1:23:43 Wait a minute. But is, isn't that like ... (sighs) Don't we hold onto that? Isn't that why we're afraid of death? We don't wanna lose this thing we have going on. Isn't that an ego death? When there's a bunch of other Manolises, you get to look at them, they're not you. They're just very good copies of you. They get to live a life. The, I mean, it's fear of missing out. It's FOMO. (laughs) They get to have interactions.

Manolis Kellis 1:24:09 I ...

Lex Fridman 1:24:10 And you don't get to have those interactions.

Manolis Kellis 1:24:12 There's two aspects of every person's life. There's what you give to others, and there's what you experience yourself.

Lex Fridman 1:24:20 Yeah.

Manolis Kellis 1:24:21 Life truly ends when you experiencing ends. But the others experiencing you doesn't need to end.

Lex Fridman 1:24:31 Oh. Ah. But your experience, you could still ... I guess you're saying the digital twin does not limit your ability to truly experience-

Manolis Kellis 1:24:42 Yeah.

Lex Fridman 1:24:42 ... to experience as a human being.

Manolis Kellis 1:24:44 Yeah. The, the, the, the downside is when, you know, my wife or my kids will have a really emotional interaction with my digital twin and I won't know about it.

Lex Fridman 1:24:55 Yeah.

Manolis Kellis 1:24:55 So I will show up and they now have the baggage, but I don't. So basically what makes interactions between humans unique in this sharing and exchanging kind of way is the fact that we are both shaped by every one of our interactions.

Lex Fridman 1:25:08 Mm-hmm.

Manolis Kellis 1:25:09 I think the model of the digital twin works for dissemination of knowledge, of advice, et cetera. Where, you know, I wanna have wise people give me advice across history. I want to have chats with Gandhi, but Gandhi won't necessarily l- learn from me, but I will learn from him. So in a way, you know, the, the dissemination, the democratization rather than the building of relationships.

Lex Fridman 1:25:35 So the, the emotional aspect. So there should be an alert when an AI system is interacting with your loved ones ...

Manolis Kellis 1:25:42 Exactly.

Lex Fridman 1:25:42 ... and all of a sudden it starts getting like emotionally fulfilling, like a magical moment. There should be, okay, stop. AI system like freezes. There's an alert on your phone. You need to take over. (laughs)

Manolis Kellis 1:25:53 Yeah, yeah. I take over and then whoever I was speaking with, they can have the, the AI or like one of the AIs.

Lex Fridman 1:25:59 Uh, this is such a tricky thing to get right. I mean, it's still ... Well, I mean, there's g-... uh, is go- is going to go wrong in so many interesting ways that we're gonna have to learn as a society.

Manolis Kellis 1:26:09 Yeah. Yeah.

Lex Fridman 1:26:10 That in the process of trying to automate our tasks and having a digital twin, you know, for me personally, if I could have a relatively good copy of myself, uh, I would set it to start answering emails.

Manolis Kellis 1:26:24 But-

Lex Fridman 1:26:24 I would start it, set it to start tweeting. I would like to replace-

Manolis Kellis 1:26:27 It gets, it gets better. What if that one is actually way better than you?

Lex Fridman 1:26:31 Yeah. Exactly.

Manolis Kellis 1:26:32 Then you're like, "Oh."

Lex Fridman 1:26:33 Well, I wouldn't want that because...

Manolis Kellis 1:26:35 Why?

Lex Fridman 1:26:36 Because then I would never be able to live up to... Like what if the people that love me start loving that thing and then I'm, I will also... I already fall short. (laughs) I would be falling short even more.

Manolis Kellis 1:26:48 So listen, I'm a professor. The stuff that I give to the world is the stuff that I teach, but most, much more importantly, like, sorry, number one, the stuff that I teach, number two, the discoveries that we make in my research group, but much more importantly, the people that I train.

Lex Fridman 1:27:03 Mm-hmm.

Manolis Kellis 1:27:04 They are now out there in the world teaching others. If you look at my own trainees, they are extraordinarily successful professors. So Anshu Kundaje at Stanford, Alex Stark at IMP in Vienna, Jason Ernst at UCLA, Andreas Pfenning at CMU. Each of them, I'm like, "Wow, they're better than I am." And I love that. So maybe your role will be to train better versions of yourself and they will be your legacy. Not you doing everything, but you training much better version of Lex Fridman than you are. And then they go off to do their mission, which is in many ways what this mentorship model of academia does.

Lex Fridman 1:27:47 But the legacy is ephemeral. It doesn't really live anywhere. The legacy, it's not like written somewhere. It just lives through them.

Manolis Kellis 1:27:55 But you can continue improving and you can continue making even better versions of you.

Lex Fridman 1:28:00 Yeah. But they'll do better than me at-

Manolis Kellis 1:28:02 And that's awesome.

Lex Fridman 1:28:02 ... creating new versions.

Manolis Kellis 1:28:03 (laughs)

Lex Fridman 1:28:04 It's awesome. But it's, um, you know, there's a ego that says there's a value to an individual and it feels like this process decreases the value of the individual, this meat bag, right? If there's good digital copies of people, then, uh, uh, there's more flourishing of human thought and ideas and experiences, but there's less value to the individual human.

Manolis Kellis 1:28:29 I, I don't have any such limitations. I, I, I basically, I don't f- I don't have that feeling at all.

Lex Fridman 1:28:36 Hm.

Manolis Kellis 1:28:36 Like I remember one of our interviews, I was basically saying, you know, the meaning of life you had asked me and I was like, I came back and I was like, "I felt useful today." And I was at my maximum. I was, I was, you know, like a hundred percent and I gave good ideas and I was a good person. I was a good advisor. I was a good husband, good father. That was a great day because I was useful. And if I can be useful to more people by having a digital twin, I will be liberated because my urge to be useful will, will be satisfied. Doesn't matter whether it's direct me or indirect me, whether it's my students that I've trained, my AI that I've trained. I think there's a, there's a sense that my mission in life is being accomplished and I can work on myself growth.

Lex Fridman 1:29:25 I mean, that's a very zen state. That's why people love you. It's a zen state you've achieved. But do you think most of humanity will be able to achieve that kind of thing? Is the people, people really hold on to the value of their own ego, that