Dr. Michael Levin on Lex Fridman: How Cells Can Be Persuaded

1. 0:00 – 0:44

   Introduction

   1. LFLex Fridman0:00

      The following is a conversation with Michael Levin, his second time on the podcast. He is one of the most fascinating and brilliant biologists and scientists I've ever had the pleasure of speaking with. He and his labs at Tufts University study and build biological systems that help us understand the nature of intelligence, agency, memory, consciousness, and life in all of its forms here on Earth, and beyond. This is the Lex Fridman Podcast. To support it, please check out our sponsors in the description, where you can also find links to contact me, ask questions, give feedback, and so on. And now, dear friends, here's Michael Levin.

2. 0:44 – 9:17

   Biological intelligence

   1. LFLex Fridman0:45

      You write that the central question at the heart of your work from, uh, biological systems to computational ones is, how do embodied minds arise in the physical world, and what determines the capabilities and properties of those minds? Can you unpack that question for us and maybe, uh, begin to answer it?

   2. MLMichael Levin1:04

      Well, the fundamental tension is in both the first-person, the second-person, and third-person descriptions of mind. So, so in third-person, we want to understand, how do we recognize them, and how do we know looking out into the world what degree of agency there is and how best to relate to the different systems that we find, and, uh, are our intuitions any good when we look at something and it looks really stupid and mechanical versus, uh, it really looks like there's something, uh, cognitive going on there? How do we get good at recognizing them? Then there's the second-person, which is the control, and that's both for engineering but also for regenerative medicine, when you want to tell the system to do something, right? What kind of tools are you going to use? And this is a major part of my framework is that all of these kinds of things are operational claims. Are you going to use the tools of hardware rewiring, of control theory and cybernetics, of behavior science, of psychoanalysis and love and friendship? Like, what are the interaction protocols that you bring, right? And then in first-person, it's this notion of having an inner perspective and being a system that has valence and cares about the outcome of things, makes decisions and has memories and tells a story about itself and the outside world, and how can all of that exist and still be consistent with the laws of physics and chemistry and various other things that, uh, that we see around us? So that, that I find to be maybe the most interesting and the most important, uh, mystery for all of us to, uh, well, on the science and also on the personal level. So that's, that's what I'm interested in.

   3. LFLex Fridman2:30

      So your work is focused on starting at the physics, going all the way to friendship and love and psychoanalysis.

   4. MLMichael Levin2:37

      Yeah, although, although actually I would turn that upside down. I, I think that pyramid is backwards, and I think it's behavior science at the bottom. I think it's behavior science all the way. I think in certain ways even math is the behavior of a certain kind of being that lives in a latent space, and physics is what we call systems that at least look to be amenable to a very, uh, simple, low-agency kinda model and so on. But, uh, but that's what I'm interested in, is understanding that and developing applications, because it's very important to me that, uh, what we do is transition deep ideas and philosophy into actual practical applications that not only make it clear whether we're making any progress or not, but also allow us to relieve suffering and make life better for all sentient beings and, and enable to, uh, you know, enable us and others to reach their full potential. So these are, these are very practical things, I think.

   5. LFLex Fridman3:28

      Behavioral science is suppose- is more subjective and mathematics and physics is more objective? Would that be the, the clear difference?

   6. MLMichael Levin3:35

      The idea basically is that where something is on that spectrum, and I've called it the spectrum of persuadability, you could call it the spectrum of intelligence or agency or something like that. I like the notion of the spectrum of persuadability because it's an engineering approach. It means that these are not things you can decide or have feelings about from a, from a philosophical armchair. You have to make a hypothesis about which tools, which interaction protocols you're gonna bring to a given system, and then we all get to find out how that worked out for you, right? So, so you could be wrong in many ways, in both directions. You can guess too high or too low or wrong in various ways, and then we can all find out how that's working out. And so I do think that the behavior of certain objects is well-described by specific formal, uh, formal rules, and we call those things the s- the te- the subject of mathematics, and then there are some other things whose behavior really requires the kinds of, uh, tools that we use in, in behavioral cognitive, uh, neuroscience, and those are other kinds of minds that, uh, that we think we study in biology or in psychology or other sciences.

   7. LFLex Fridman4:39

      Why, why are you using the term persuadability? Who are you persuading and of what?

   8. MLMichael Levin4:43

      Well-

   9. LFLex Fridman4:44

      In this context.

   10. MLMichael Levin4:45

       (laughs) Yeah, the beginning of my work is very much in regenerative medicine, in, uh, in bioengineering, things like that. So for those kinds of systems the re- the question is always how do you get the system to do what you want it to do? So there are cells, there are molecular networks, there are materials, there are organs and tissues and synthetic beings and biobots and whatever, and so the idea is if I want your cells to regrow a limb, for example, if you're injured and I want your cells to regrow a limb, I have many options. Some of those options are, I'm going to micromanage all of the molecular, uh, events that have to happen, right? And there's an incredible number of those. Or maybe I just have to micromanage the cells and the stem cell, uh, kinds of, uh, signaling factors. Or maybe actually I can give the cells very high level, uh, prompt that says, "You really should build a limb," and convince them to do it, right? And so where, um, w- what, what i- which of those is possible? I mean, clearly people have a lot of intuitions about that. If you ask standard people in regenerative medicine and molecular biology, they're going to say, "Well, that convincing thing is crazy. What we really should be doing is talking to the cells, or better yet, the molecular networks." And in fact all the excitement of the biological sciences today are at, at, you know, single molecule approaches and big data and, and, and genomics and all of that. The assumption is that, uh, going down is where the action's going to be, going down in scale, and-And I think that's, I think that's wrong. But the, but the thing that we can say for sure is that you can't guess that, you- you have to do experiments and you have to see because you don't know where any given system is on that spectrum of persuadability. And it turns out that every time we look and we take tools from behavioral science, so learning different kinds of training, different kinds of models that are used in, uh, active inference and surprise minimization and, uh, perceptual multi-stability and visual illusions and all- all these kinds of interesting things, you know, stress perception and- and memory, um, uh, a- active memory reconstruction, all these interesting things. When we apply them outside the brain to other kinds of living systems, we find novel discoveries and novel capabilities, actually being able to get the material to do new things that nobody had ever found before. And- and precisely because I think that, uh, people didn't, uh, didn't look at it from- from those perspectives, they- they assumed that it was a low level kind of thing. So when I say persuadability, I mean different types of approaches, right? And we all, and we all know if you wanna, if you wanna persuade your wind-up clock to do something, y- you're not gonna argue with it or make it feel guilty or anything. You're gonna have to get in there with a wrench and you're gonna have to, you know, tune it up and do whatever. If you want to do that same thing to a cell or a thermostat or an animal or a human, you're going to be using other sets of tools that we've given other names to. And so that's... Now- now, of course, that spectrum, the important thing is that as you get to the right of that spectrum was the agency of the system goes up. It is no longer just about persuading it to do things. It's a bidirectional relationship, what Richard Watson would call a mutual vulnerable knowing. So the idea is that on the right side of that spectrum, when systems reach the higher levels of agency, the idea is that you are willing to let that system persuade you of things as well. You know, in molecular biology, you do things, hopefully the system does what you wanna do, but you haven't changed. You're still, you're still exactly the way you- you came in. But on the right side of that spectrum, if you're having interactions with even cells, but certainly, you know, uh, dogs, other- other- other animals, maybe- maybe other- other creatures soon, you're not the same at the end of that interaction as you were going in. It's a mutual bidirectional relationship. So it's not just you persuading something else, it's not you pushing things. It's a- it's a mutual bidirectional set of, uh, set of persuasions, whether those are purely intellectual or of other kinds.

   11. LFLex Fridman8:20

       So in order to be effective at persuading an intelligent being, you yourself have to be persuadable. So the closer in intelligence you are to the thing you're trying to persuade, the more persuadable you have to become, hence the mutual vulnerable knowing. What a term.

   12. MLMichael Levin8:37

       Yeah, yeah. Richard, uh... Yeah, you should- you should talk to Richard as well. He's- he's an amazing guy and he's got some very interesting ideas about the intersection of cognition and, um, evolution. But, you know, I think- I think what you bring up is- is very important because, um, there has to be a kind of impedance match between what you're looking for and the tools that you're using. I think the reason physics always sees mechanism and not minds is that physics uses low agency tools. You've got volt meters and- and rulers and things like this. And- and if you use those tools as your interface, all you're ever going to see is mechanisms and- and those kinds of things. If you want to see minds, you have to use a mind, right? You have to have... There has to be some degree of resonance between your interface and the thing you're hoping

3. 9:17 – 14:30

   Living vs non-living organisms

   1. MLMichael Levin9:17

      to find.

   2. LFLex Fridman9:18

      You said this about physics before. Can you just linger on that and, like, expand on it what you mean why physics is not enough to understand life, to understand mind, to understand intelligence? You make a lot of controversial statements with your work. That's one of them. 'Cause there are a lot of physicists that believe they can understand life, the emergence of life, the origin of life, the origin of intelligence using the tools of physics.

   3. MLMichael Levin9:41

      Yeah.

   4. LFLex Fridman9:41

      In fact, all the other tools are a distraction to those folks. If you want to understand fundamentally anything, you have to start with physics to them. And you're saying, "No, physics is not enough."

   5. MLMichael Levin9:52

      Here's- here's the issue. E- everything here hangs on what it means to understand, okay? And for- for me, because u- understand doesn't just mean, uh, have some sort of a pleasing model that seems to capture some important aspect of what's going on, it also means that you have to be generative and creative in terms of, uh, capabilities. And so for me, that means if I tell you, uh, this is what I think about cognition in cells and tissues, it means, for example, that, uh, I think we're going to be able to take those ideas and use them to produce new regenerative medicine that actually helps people in various ways, right? So it's just an example. So if you think as a physicist you're going to have a complete understanding of what's going on from that, uh, uh, perspective of- of fields and particles and- and, you know, who knows what- what else is at the bottom there, does that mean then that when somebody is missing a finger or has a psychological problem or- or- or- or, uh, you know, has these other high level issues, that you have something for them, that you're gonna be able to do something? Because my claim is that you're not going to. And even- even if- even if you- you have some theory of physics that is completely compatible with everything that's going on, that is... It's not enough. That's not specific enough to enable you to solve the problems you need to solve. In the end, when you need to solve those problems, the- the person you're going to go- go to is not a physicist. It's going to be either a biologist or a psychiatrist or who knows, but- but- but it's not gonna be a physicist. And- and the simple example is this. You know, let's say, let's say someone, uh, comes in here and tells you a beautiful mathematical proof, okay? It's just really, you know, deep and beautiful, and there's a physicist nearby and he says, "Well, I know exactly what happened. I- there were some air particles that moved from- from- from that guy's mouth to your ear. I see what goes on. It moved your, uh, the cilia, um, in your ear and the e- and the, uh, electrical signals went up to your brain." I mean, we have a complete accounting of what happened, done and done. But if you wanna understand what's the more important aspect of that interaction, it's not gonna be found in the physics department, it's gonna be found in the math department. So that's my only claim is that physics is an amazing lens with which to view the world, but you're capturing certain things. And- and if you wanna stretch to, um, sort of encompass these other things, it- it's just... We- we just don't call that physics anymore, right? That's... We- we call that something else.

   6. LFLex Fridman12:03

      Okay, but you're kind of speaking about the...... uh, super complex organisms. Can we go to the simplest possible thing where you first take a step over the line, the Cartesian cut as you've called it, from the non-mind to mind, from the non-living to live? It is the simplest possible thing. Isn't that in the realm of physics to understand? How do we understand that first step where you're like, that thing is no mind, probably non-living, and here's a living thing that has a mind. That line. I think that's a really interesting line. Maybe you can speak to the line as well, and can physics help us understand it?

   7. MLMichael Levin12:43

      Yeah, let's talk about... Well, fir- first of all, of- of course it can. I mean, it can help, meaning that I'm not saying physics is not helpful. Of course it's helpful. It's- it's a very important lens on one slice of what's going on in any of these systems. But I think the most important thing I can say about, um, that question is I- I don't believe in any such line. I don't believe any of that exists. I think, uh, I think there is a, um, a c- I think it's a continuum. I think we as humans like to, uh, demarcate areas on that continuum and give them names because it makes life easier, and then we have a lot of battles over, uh, you know, so-called category errors when people, they transgress those, uh, those categories. I think most of those categories at this point, they- they may have done some- some good service at the beginning of when the scientific method was getting started and so on. I think at this point, uh, they mostly hold back science. Many, many categories that we can talk about are at this point very harmful to progress, because what those categories do is they prevent you from hoarding tools. If you think that, uh, living things are fundamentally different from non-living things, or if you think that cognitive things are these like advanced brainy things that are very different from other kinds of systems, what you're not going to do is take the tools that are appropriate to these, uh, to- to these kind of, uh, cognitive systems, right? So the- so the tools that have been developed in- in behavioral science and so on. You're never going to try them in other contexts because- because you've already decided that there's a categorical difference, that it would be a categorical error to apply them. And- and people say this to me all the time is that, "You're making a category error," as- as if these categories were given to us, you know, by, from- from- from on high, and we have to, we have to obey them forevermore. The categories should change with the science. So, um, yeah, I don't believe in any such line, and I think, I think ph- a- a physics story is very often a useful part of the story. But for most interesting things, it's not the entire story.

4. 14:30 – 18:15

   Origin of life

   1. MLMichael Levin14:30

   2. LFLex Fridman14:30

      Okay. So if there's no line, is it still useful to talk about things like the origin of life? That's the- the, one of the big open mysteries before us as a human civilization, as, uh, scientifically minded curious homo sapiens, how did this whole thing start? Are you saying there is no start? Is there a point where you could say that invention right there was the start of it all on Earth?

   3. MLMichael Levin15:01

      My suggestion is that much better than trying to, it in- in- in my experience, much better than trying to define any kind of a line, okay? Because- because inevitably I've never, I've never found, and people try to, you know, we play this game all the time when I make my continuum claim. Then people try to come, "Okay, well, what about this? You know, what about this?" And I- I haven't found one yet that really shoots that down that- that you can't zoom in and say, "Yeah, okay, but right before then, this happened, and if we really look close, like here's a bunch of steps in between," right? Pretty much everything ends up being a continuum, but here's what I think is much more interesting than trying to make that line. I think what's- what's really, uh, more useful is trying to understand the transformation process. What is it that happened to scale up? And I'll give you a really dumb example. And we al- and we always get into this 'cause people, people often really, really don't like this continuum view. The word adult, right?

   4. LFLex Fridman15:50

      Mm-hmm.

   5. MLMichael Levin15:51

      E- everybody is going to say, "Look, I know what a baby is, I know what an adult is. You're crazy to say that there's no difference." I'm not saying there's no difference. What I'm saying is the word adult is really helpful in court because- because- because you just need to move things along. And so we've decided that, uh, if you're 18, you're an adult. However, what it hides is, is, and what- what it completely conceals is the fact that, f- first of all, nothing happens on your 18th birthday, right? That's- that's special. Second, if you actually look at the data, the car rental companies actually have a much better estimate because they actually look at the accident statistics and they'll say it's about 25 is- is- is really what you're looking for, right? So there's is a little better, it's less arbitrary. But in either case, what it's hiding is the fact that we do not have a good story of what happened from the time that you were an egg to the time that you're the supposed adult, and what is the scaling of re- personal responsibility, decision-making, judgment. Like, these are deep fundamental conte- uh, you know, questions. Nobody wants to get into that every time somebody, uh, you know, has a traffic ticket. And so, okay, so- so we've just decided that there's this adult idea. How... And- and- and of course it does come up in court because then somebody has a brain tumor or somebody's eaten too many Twinkies or- or something has happened and you say, "Look, that wasn't me. Whoever did that, I was on drugs." "Well, why'd you take the drugs?" "Well, that was, you know, that was yesterday. I mean, today this is..." Right? So- so we get into these very deep questions that are completely glossed over by this idea of an adult. So- so I think once you start scratching the surface, most of these categories are like that. They're convenient and they're good. It- it's... You know, I get into this with neurons all the time. I- I'll- I'll ask people, "What's- what's a neuron? Like, what's really a neuron?" And yes, if you're, if you're in, uh, Neurobiology 101, of- of course you just say, "Look, these are what neurons look like. Let's just study the neuroanatomy and we're done." But if you really wanna understand what's going on, well, neurons develop from other types of cells, and that was a slow and gradual process, and most of the cells in your body do the things that neurons do. So what really is a neuron, right? So- so once you start scratching this, this- this happens, and I have some things that I think are coming out of our lab, and others that are I think very interesting about the origin of life. But I don't think it's about finding that one boom like this is. Yeah, there will be, there- there are innovations, right? There are, there are innovations that- that, um, allow you to, uh, scale in a, in an amazing way, for s- for sure. And- and there are lots of people that study those, right? Uh, so- so things, the thermodynamic kind of metabolic things and- and- and all kinds of architectures and so on. But I don't think it's about finding a line. I think it's about finding a scaling process.

5. 18:15 – 51:19

   The search for alien life (on Earth)

   1. LFLex Fridman18:16

      ... the scaling process. But then there is more rapid scaling and there's slower scaling, so innovation, invention, I think is useful to understand so you can predict how likely it is on other planets, for example. Or, uh, to be able to describe the likelihood of these kinds of phenomena happening in certain kinds of environments. Again, specifically in answering how many alien civilizations there are.

   2. MLMichael Levin18:44

      Yeah. Yeah.

   3. LFLex Fridman18:44

      You... That's why it's useful. But i-it is also useful on a scientific level to have categories, not just 'cause it makes us feel good and fuzzy inside, but because it makes conversation possible and productive, I think. If everything is a spectrum, it's, i-it becomes, um, difficult to make concrete statements, I think. Like we even use the terms of biology and physics. Those are categories. Technically, it's all the same thing, really. Fundamentally, it's all the same. There's no difference between biology and physics. But it's a useful category. If you go to the physics department and the biology department, those people are different in, in, uh, some kind of categorical way. So somehow, I don't know what the chicken or the egg is with the categories. Maybe the categories create themselves because of the way we think about them and use them in language, but it does seem useful.

   4. MLMichael Levin19:35

      Let me make the opposite argument. They're absolutely useful. They're useful specifically when you wanna gloss over certain things.

   5. LFLex Fridman19:41

      Mm-hmm.

   6. MLMichael Levin19:41

      E- ex- The categories are exactly useful when there's a whole bunch of stuff, and this is, this is what's important about science is, like, the art of being able to say something without first having to say everything, right?

   7. LFLex Fridman19:50

      Yes.

   8. MLMichael Levin19:50

      Which would make it impossible. So, so categories are great when you, when you wanna say, "Look, I, I, I know, there's a bunch of stuff hidden here. I'm gonna ignore all that and we're just gonna, like, let's get on with this particular thing." And all of that is great as long as you don't lose track of the stuff that you glossed over, and that was what I'm afraid is happening in a lot of different ways. And in terms of... L- look, I'm, I'm, I'm very interested in, in, in life, uh, b- you know, beyond Earth and all, all of these kinds of things, although we should also talk about what I call SUTI, S-U-T-I, the search for unconventional terrestrial intelligences. I think, I think, I think we got much bigger issues than, than actually recognizing aliens off Earth. But I'll make this claim. I think the categorical stuff is actually hurting that search because, because if we try to define categories, uh, with the kinds of criteria that we've gotten used to, we are going to be very poorly set up to recognize life in novel embodiments. I think we have a kind of mind blindness. I think this is really key. It's much w- to, to me, to me, um, the cognitive spectrum is much more interesting than the spectrum of life. I think really what we're talking about is the spectrum of cognition. And, uh, it is... I know, it's weird as a biologist to say, I don't, I don't think life is all that interesting a category. I think the categories of, of different types of minds, I think is extremely interesting. And to the extent that we think our categories are complete and are cutting nature at its joints, we are going to be very poorly placed to recognize novel systems. So for example, a lot of people will say, "Well, this is intelligent and this isn't," right? And there's a binary thing and s- and, and that's useful and occasionally that's useful for some things. I would like to say instead of that, let's make a s- let's, let's, let's admit that we have a spectrum, but instead of just saying, "Oh, look, everything's intelligent," right? 'Cause if you do that, you're right, you can't, you can't do anything after that. What I'd like to say instead is, "No, no, you have to be very specific as to what kind and how much." In other words, what problem spaces they're operating in? What kind of mind does it have? What kind of cognitive capacities does it have? You have to actually be much more specific. And, and we can even name, right? That's fine. We can name different types of, I mean, this is doing predictive processing. This can't do that, but it can form memories. What kind? Well, habituation and sensitization, but not associative conditioning. Like, it's fine to have categories for specific capabilities, but it's, it's, uh, it, it actually, I think it actually makes, makes for much more rigorous discussions because it makes you say, "What is it that you are claiming this thing does?" And it works in both directions, so. And so some people will say, "Well, that's a s- that's a cell. That can't be intelligent." And I'll say, "Well, let's be very specific. Here are some claims about... Here is some problem solving that it's doing. T- tell me why that doesn't... m- v- you know, why doesn't that match?" Or in the opposite direction, somebody comes to me and says, "You're right, you're right. You know, the whole, the whole solar system, man. It's just, like, this amazing..." I'm like, "W- okay, well, what is it doing? Like, t- tell me, tell me what, what tools of cognitive and behavioral science are you using to, to, to reach that conclusion," right? And so I think, I think it's actually much more productive to take this operational stance and say, "Tell, tell me what protocols you think you can deploy with this thing that would lead you to, to, to use these terms."

   9. LFLex Fridman22:49

      To have a bit of a meta conversation about the conversation. Uh, I should say that part of the persuadability argument that we too intelligent creatures are doing is, uh, me playing devil's advocate every once in a while, and you did the same, which is kinda interesting, taking the opposite view and see what comes out.

   10. MLMichael Levin23:05

       Mm-hmm.

   11. LFLex Fridman23:06

       'Cause you don't know the result of the argument until you have the argument, and it's... seems productive to just take the other side of the argument.

   12. MLMichael Levin23:14

       For sure. It's a very important, uh, thinking aid to... For, first of all, uh, you know, what they call steel manning, right? To try to, try to make the strongest possible case for the other side and to ask yourself, okay, what are all the, what are all the places that I'm sort of glossing over because I don't know exactly what to say? And where are all the, where are all the holes in the argument and what would, what would a, you know, a really good critique really look like? Yeah.

   13. LFLex Fridman23:38

       Sorry to go back there, just to linger on the term 'cause it's so interesting, persuadability. Did I understand correctly that you mean that it's kind of synonymous with intelligence? So it's an engineering-centric view of an intelligent system because if it's persuadable, you're more focused on how can I steer the goals of the system, the behaviors of the system. Which meaning an intelligent system maybe is a, is a goal-oriented, goal-driven system with agency, and when you call it persuadable, you're thinking more like, okay, here's an intelligent system that I'm interacting with that I would like to get it to accomplish certain things. But fundamentally, they're...... synonymous or correlated? Persuadability and intelligence?

   14. MLMichael Levin24:28

       They're definitely correlated. So, so let me, eh, I, I wanna, I wanna, um, preface this with, with one thing. W- when I say it's an engineering perspective, I don't mean that the standard, uh, tools that we use in engineering and this idea of, of enforced control and steering is how we should view all of the world. I'm not saying that at all, and, and I want to be very clear on the- because, because, because people do email me and say, "Ah, this engineering thing. You're gonna drain the, you know, the life and the majesty out of these high end, like, human conversation." My whole, my whole point is not that at all. It's that, uh, of course, at the right side of the spectrum it doesn't look like engineering anymore, right? It looks like, it looks like friendship and love and psychoanalysis and all these other tools that we have. But here's what I wanna do. I wanna be very specific to my colleagues in regenerative medicine and re- just im- imagine if I, you know, if I, if I went to a bioengineering department or a genetics department and I started talking about high level, uh, y- you know, cognition and psychoanalysis, right? They, they don't wanna hear that. So, so I- I bring my, um, I focus on the engineering approach-

   15. LFLex Fridman25:28

       Mm-hmm.

   16. MLMichael Levin25:28

       ... because I w- I want to say, look, this is not a philosophical problem. This is not a linguistics problem. We are not trying to, uh, define terms in different ways to make anybody feel fuzzy. What I'm telling you is, if you want to reach certain capabilities, if you want to reprogram cancer, if you want to regrow new organs, you wanna defeat aging, you wanna do these specific things, you are leaving too much on the table by making an unwarranted assumption that the low level tools that we have, so these are the rules of chemistry and the k- kind of remolecular rewiring, that those are going to be sufficient to get to where you want to go. It's a, it's a, it's an assumption only, and it's an unwarranted assumption, and actually, we've done experiments now, so, so not philosophy but real experiments, that if you take these other tools, you can in fact persuade the system in ways that has never been done before. And, and, and we can, we can un- unpack all that. But it is, it is absolutely, um, correlated with intelligence, so let me, um, flesh that out a little bit. Um, what I think is scaling in all of these things, right, because I keep talking about the scaling, so what is it that's scaling? What I think is scaling is something I call the cognitive light cone, and the cognitive light cone is the size of the biggest goal state that you can pursue. This doesn't mean how far do your senses reach. This doesn't mean how far can you affect it. So the James Webb Telescope has enormous sensory reach, but that doesn't mean that's, that's the size of its cognitive light cone. The size of the cognitive light cone is the scale of the biggest goal you can actively pursue. But I do think it's a useful concept to enable us to think about very different types of agents of different composition, different provenance, you know, engineered, evolved, hybrid, whatever, all in the same framework. And by the way, the reason I use light cone is that it has this idea from physics that you're putting space and time kind of in the same diagram, which is which- which I like here. So if you tell me that all your goals revolve around maximizing the amount of sugar con- the amount of sugar in this- in this, you know, 10, 20 micron radius of space time and that you have, you know, 20 minutes memory going back and maybe five minutes predictive capacity going forward, that tiny little cognitive light cone, I'm gonna say probably a bacterium. And if you say to me that, "Well, I ca- I'm able to care about, um, several hundred yards sort of scale. I could never care about what happens three weeks from now two towns over, just impossible." Um, so you might be a dog. And if, and if you say to me, "Okay, I care about, uh, really what happens, you know, the financial markets on Earth, the, you know, l- long after I'm dead and this and that," say you're probably a human. And if you say to me, "I care in the linear range, I actively, not j-" I'm not just saying it, "I can actively care in the linear range about all the living beings on this planet," I'm gonna say, "Well, you're not a standard human. You must be something else because humans, I don't know, standard humans today I don't think can do that. You, you must be some kind of a Bodhisattva or some other thing that has these massive cognitive light cones." So I think what's scaling from zero, and I do think it goes all the way down, I think we can talk about, um, uh, even, even particles doing something like this. I think what scales is the size of the cognitive light cone. And so now this is an interesting, here I- I'll try for a definition of life or whatever, for whatever it's worth. I spent no time trying to make that stick but if we want it to. Uh, I think we call things alive to the extent that the cognitive light cone of that thing is bigger than that of its parts. So in other words, rocks aren't very exciting because the things it knows how to do are the things that its parts already know how to do, which is follow gradients and, and things like that. But living things are amazing at aligning their p- their competent parts so that the collective has a larger cognitive light cone than the parts. I'll give you a very simple example that comes up in, in biology and it comes up in our cancer, um, program all the time. Individual cells have little tiny cognitive light cones. They, what are their goals? Well, they're trying to manage pH, uh, metabolic state, uh, some other things. There are some goals in transcriptional space, some goals in, uh, uh, metabolic space, some goals in, uh, uh, physiological state space, but, but they, they're generally very tiny goals. One thing evolution did was to provide a kind of cognitive glue, which we can also talk about, that ties them together into a multicellular system, and those systems have grandiose goals. They're making limbs and, and if you're a salamander limb and you chop it off, they will regrow that limb with the right number of fingers, then they'll stop when it's done. The goal has been achieved. No individual cell knows what a finger is or how many fingers you're supposed to have, but the collective absolutely does. And that process of growing that cognitive light cone from a single cell to something much bigger, and of course the failure mode of that process, so cancer, right? When cells disconnect, they physiologically disconnect from the other cells. Their cognitive light cone shrinks. The boundary between self and world, which is what the cognitive light cone defines, uh, shrinks. Now they're back to an amoeba. As far as they're concerned, the rest of the body's just, uh, external environment, and they do what amoebas do. They go where life is good. They reproduce as much as they can, right? So that, that cognitive light cone, that, that, that is the thing that I'm talking about that scales. And so when we are looking for life, I don't think we're looking for specific materials. I don't think we're looking for specific metabolic states. I think we're looking for scales of cognitive light cone. We're looking for alignment of parts towards...... bigger goals in spaces that the parts could not comprehend.

   17. LFLex Fridman30:42

       And so, cognitive li- light cone, just to, uh, make clear, is about goals that you can actively pursue now. You said linear, like, within reach immediately.

   18. MLMichael Levin30:54

       No, I didn't... Sorry, I didn't mean that. First of all, the goal necessarily is, is often removed in time. So, in other words, when you're pursuing a goal, it means that you have a separation between current state and target state, at minimum. Your th- your thermostat, right? Let- let's just think about that. There, there's a separation in time because the thing you're trying to make happen, so that the temperature goes to a certain level, is not true right now. And all your actions are going to be around reducing that error, right? That basic homeostatic loop is all about closing that, that gap. When I meant... Wh- when I said linear range, this is what I meant. Uh, if I say to you, "This, this terrible thing happened to, uh, you know, 10 people." And, and, you know, you have some, some degree of activation about it. And then, I say, "No, no, no, actually it was 100, you know, uh, 10,000 people." You're not 1,000 times more activated about it. You're somewhat more activated, but it, but it's not 1,000. And if I say, "Oh my God, it was actually 10 million people," you're, you're not a million times more activated. You, you don't have that capacity in the linear range. You sorta, you sort of... Right? If you think about that curve, we sort of... We reach a saturation point. I have some amazing colleagues, uh, in the Buddhist community with whom we've written some papers about this. The radius of compassion is, like, can you grow your cognitive system to the point that, yeah, it really isn't just your family group, it really isn't just the 100 people you know in your, in your, you know, circle. Can you grow your cognitive, um, light cone to the point where... No, no, we care about the whole, whether it's all of humanity or the whole ecosystem or the whole whatever. Can you actually care about that the exact same way that we now care about a much smaller, um, set of people? That's what I mean by linear range.

   19. LFLex Fridman32:25

       But this is separated by time, like a thermostat. But a bacteria... I mean, (laughs) if you zoom out far enough, a bacteria could be formulated to have a goal state of creating human civilization because if you look at the... You know, bacteria-

   20. MLMichael Levin32:42

       Hmm.

   21. LFLex Fridman32:42

       ... has a role to play in the whole history of Earth.

   22. MLMichael Levin32:46

       Mm-hmm.

   23. LFLex Fridman32:46

       And so, if you anthropomorphize the goals (laughs) of a bacteria enough, I mean, it has a concrete role to play in the history of the evolution-

   24. MLMichael Levin32:58

       Yeah.

   25. LFLex Fridman32:58

       ... of human civilization. So, you do need to... In, when you define a cognitive light cone, you're looking at directly short-term behavior.

   26. MLMichael Levin33:08

       Well, no. How do you know what the cognitive light cone of something is?

   27. LFLex Fridman33:11

       Yeah.

   28. MLMichael Levin33:11

       Because it might... As, as you've said, it could be, it could be almost anything. The key is you have to do experiments. And the way you do experiments is you put barrier... You have to do interventional experiments. You have to put barriers between it and its goal, and you have to ask what happens. And intelligence is the degree of ingenuity that it has in overcoming barriers between it and its goal. Now, if it were to be that... Now, now, this is the c- this, this is, I think, uh, a totally doable, but, but impractical and very expensive experiment. But you could imagine setting up a, a scenario where the bacteria were blocked from becoming more complex, and you can ask if they would try to find ways around it or whether it's actually, nah, their goals are actually metabolic and as long as th- those goals are met, they're not gonna actually get around your barrier. The, the, the... This, this, this business of putting b- barriers between things and their goals is actually extremely powerful because we've deployed it in all kinds of... And, um, I'm sure, I'm sure we'll get to this later, but we've, we've deployed it in all kinds of weird systems that you wouldn't think are goal-driven systems. And what it allows us to do is to get beyond just the, the, the... What, what you called anthropomorphizing claims of say, you know, saying, "Oh, yeah, I th- you know, I think this s- thing is trying to do this or that." The question is, well, let's do the experiment. And one other thing I want to say about anthropomorphizing is people, people say this to me all the time. Um, I, I, I don't think that e- exists. I think that's kinda like, you know, uh, uh... And, and I'll s- I'll tell you why. I, I think it's like heresy or, like, uh, other, other terms that, uh, aren't really a thing. Because if you, if you unpack it, here's, here's what anthropomorphism means. Humans have a certain magic and you're making a category error by attributing that magic somewhere else. My point is, we have the same magic that everything has. We have a couple of interesting things beside, like our cognitive light cone and some other stuff. And it isn't that you have to keep the humans separate because there's some bright line. It's just... It's, it's that same old, uh... All, all I'm, all I'm arguing for is the scientific method, really. That's really all this is. All I'm saying is, you can't just make pronouncements such as, "H- humans are this and let's not, uh, sort of push that." W- you have to do experiments. After you've done your experiments, you can say either, "I've done it and I found... Look at that, that thing actually can predict the future for the next, you know, 12 minutes. Amazing." Or you say, "You know what? I've tried all the things in the behaviorist handbook, they just don't help me with this. It's a very low level of..." Like, that's it. "It's a, it's a very low level of intelligence. Fine." Right? Done. So, that's really all I'm arguing for is an empirical approach. And then, things like anthropomorphism go away. It's just a matter of have you done the experiment and what did you find?

   29. LFLex Fridman35:46

       And that's actually one of the things you're saying, that, uh, if you remove the categorization of things, you can use the tools-

   30. MLMichael Levin35:54

       Yeah.
6. 51:19 – 1:04:21

   Creating life in the lab - Xenobots and Anthrobots

   1. MLMichael Levin51:19

      inform you of.

   2. LFLex Fridman51:19

      Can you actually explain briefly what a Xenobot is and what an Anthrobot is?

   3. MLMichael Levin51:24

      So one of the things that we've been doing is trying to create novel beings that have never been here before. The reason is that typically when you have a biological system, an animal or a plant, and you say, "Hey, why does it have certain forms of behavior, certain forms of anatomy, certain forms of physiology? Why, why does it have those?" The answer is very ... is, is always the same. Well, there's a history of, uh, evolutionary selection, and there's a long, uh, long, um, history going, going back of adaptation, and there's certain environments, and this is what survived, and so that's why it has. So, uh, what I, what I wanted to do was, was break out of that mold and to ... to, to basically force us as a community to s- to dig deeper into where these things come from, and that means taking away the crutch where you just say, "Well, it's ev- it's evolutionary selection that's ... that, that's why it looks like that." So in order to do that, we have to make artificial, um, synthetic beings. Now, to be clear, we are starting with living cells, so it's not that they had no evolutionary history. The cells do. They had evolutionary history in frogs or humans or whatever, but the creatures they make and the capabilities that these creatures have were never directly selected for, and in fact, they never existed. So you can't tell the same kind of story, and what I mean is, we can take epithelial cells off of an early frog embryo, and we don't change the DNA. No synthetic biology circuits, no material scaffolds, no nanomaterials, no weird drugs, none of that. What we're mostly doing of ... is liberating them from the instructive influences of the rest of the cells that they were in in their bodies. And so when you do that, right n- normally these cells, uh, are bullied by their neighboring cells into having a very boring life. They become a two-dimensional outer covering for the, for the embryo, and they keep out the bacteria, and that's that. So you might ask, "Well, what are these cells capable of when you take them away from that influence?" So when you do that, they form another little, um, life form we call a Xenobot, and it's this, uh, self-motile little thing that has, uh, cilia covering its surface. The cilia are coordinated, so they row against the water, and then the thing starts to move, and has all kinds of amazing properties. It has different gene expression, so it has its own novel transcriptome. It's able to do things like kinematic self-replication, meaning make copies of itself from loose cells that you put in its environment. It has the ability to respond to sound, which n- normal embryos don't do. It has these novel capacities, and we did that, and we said, "Look, here are some amazing features of this novel system. Let's try to understand where they came from." And some people said, "Well, maybe it's a frog-specific thing, you know? Uh, may- maybe this is just something unique to frog cells." And so we said, "Okay, what's the furthest you can get from, from frog embryonic cells? How about human adult cells?" And so we took, uh, cells from adult human patients who were donating tracheal epithelia for, um, biopsies and things like that, and those cells, in ... again, no genetic change, nothing like that. They self-organized into something we call Anthrobots. Again, self-motile little creature. 9,000 different gene expressions, so about half the genome is now different. And, uh, they have interesting abilities. Uh, for example, they can heal human neural wounds. So in vitro, if you, if you pl- uh, plate some, um, some neurons and you put a big scratch through it so you damage them, Anthrobots can sit down, and they will, they will try ... they will spontaneously, without ha- us having to teach them to do it, they will spontaneously try to, uh, knit the neurons acro- uh ...

   4. LFLex Fridman54:42

      Uh, what is this video that we're looking at here?

   5. MLMichael Levin54:44

      So this is an Anthrobot. So often when I give talks about this, I show people this video, and I say, "What do you think this is?" And people will say, "Well, it looks like some primitive organism you got from the bottom of a pond somewhere." And I'll say, "Well, what do you think the genome would look like?" and they said, "Well, the genome would look like some primitive creature." Right, if you sequence that thing, you'll get 100% homo sapiens. And that doesn't look like any stage of normal human development. It doesn't act like, uh, like any stage of, of human development. It has the ability to move around. It has l- as I said, over 9,000 differential gene expressions. Uh, also interestingly, it is, uh, younger, um, than the cells that it comes from. So it actually has the ability to roll back its age, and we, we could, we could talk about that and, and what the implications of that are. But, uh, but, uh, to go back to your original question, what we're doing with these kind of systems-

   6. LFLex Fridman55:30

      Trying to talk to it.

   7. MLMichael Levin55:31

      We're trying to talk to it. That's exactly right, and not just to this. We're trying to talk to molecular networks, so gene ... So we found ... A couple years ago, we found that gene regulatory networks, nevermind the cells, but the molecular pathways inside of cells can have, uh, several different kinds of learning, including Pavlovian conditioning, and what we're doing now is trying to talk to it. The biomedical applications are obvious. Instead of, "Hey Siri," you want, uh, "Hey liver, why do I feel like crap today?" And you want an answer. "Well, you know, your potassium levels are this and that, and I don't feel, uh, you know, I don't feel good for these reasons." And you should be able to talk to these things, and there should be able to be an interface that allows us to communicate, right? And, and I think AI is gonna be a huge, uh, component of that interface of allowing us to talk to these systems. It's a, it's a tool to combat our mind blindness, to help us see diverse other-... very unconventional minds that are all around us.

   8. LFLex Fridman56:19

      Can you generalize that? So let's say we meet an alien or an unconventional mind, uh, here on Earth. Think of it as a black box. You show up. What's the, uh, procedure for trying to get some hooks into a communication protocol with the thing?

   9. MLMichael Levin56:43

      Yeah. That is exactly the mission of, of my lab. It is, it is to enable us to develop tools to recognize these things, to learn to, uh, communicate with them, to ethically relate to them, and-

   10. LFLex Fridman56:54

       Mm-hmm.

   11. MLMichael Levin56:54

       ... in general to expand our ability to, uh, to do this in, in the, in the, in the world around us. I specifically chose these kinds of things because they're not as alien as proper aliens would be, so we have some hope. I mean, we're made of them. We have s- many things in common. There's some hope of understanding them.

   12. LFLex Fridman57:11

       You're talking about xenobots and eth-

   13. MLMichael Levin57:12

       Xenobots...

   14. LFLex Fridman57:13

       ... and anthrobots.

   15. MLMichael Levin57:13

       ... and anthropods and cells and everything else. But they're alien in a couple of important ways. One is the space they live in is very hard for us to imagine. What space do they live in? Well, um, your body, your body cells, long before we had a brain that was good for navigating three-dimensional space, was navigating the space of anatomical possibilities. It was going from you start as an egg and you have to become, you know, a s- a snake or a, or a, or a, you know, a giraffe or whatever, or a human, whatever, whatever we're gonna be. And I specifically am telling you that this, this, n- this general idea when people model that with, uh, kind of cellular automata type of ideas, this open loop kind of thing where, well, everything just follows local rules and eventually there's complexity and, and, and here you go. Now, now you've got a, now you've got a giraffe or a human. Um, I w- I'm specifically telling you that that model is totally insufficient to grasp what's actually going on. What's actually going on, and there have been many, many experiments on this, is that the system is navigating a space. It is navigating a space of anatomical possibilities. If you try to block where it's going, it will try to get around you. If you try to challenge it with things it's never seen before, it will try to come up with a, with a solution. If you i- if you really, uh, defeat its ability to do that, which you can, you know, they're not infinitely intelligent so you can, you can defeat them, you will either get birth defects or you will get creative problem-solving such as what you're seeing here with xenobots and anthropods. If you can't be a human, w- you'll be some- you can, you'll find another way to be in. You can be an anthropod for example, or you'll be something else.

   16. LFLex Fridman58:42

       Just to clarify, what's the difference between cellular automata type of action where you're just responding to your local environment and creating some kinda complex behavior and, uh, operating in the space of anatomical possibilities?

   17. MLMichael Levin58:56

       Sure.

   18. LFLex Fridman58:56

       So there's a kinda goal, I guess, you're articular-

   19. MLMichael Levin58:59

       Yes.

   20. LFLex Fridman58:59

       There is a, some kind-

   21. MLMichael Levin59:01

       Yes.

   22. LFLex Fridman59:01

       ... of thing. There's a will to X, something.

   23. MLMichael Levin59:06

       The will thing, let's put that aside. (laughs)

   24. LFLex Fridman59:08

       Okay, sorry.

   25. MLMichael Levin59:08

       'Cause that's a, well it's, it's fine to-

   26. LFLex Fridman59:10

       There I go anthropomorphizing. There's just always love to quote Nietzsche, so there you go.

   27. MLMichael Levin59:13

       Yeah, yeah, yeah. And, and I'm not saying, I'm not saying that's wrong, I'm just saying I don't have data for that one, but I'll tell you the stuff that I'm quite certain of. There are a couple of different formalisms that we have in control theory. One of those formalisms is open loop complexity. In other words, I've got a bunch of sub-units, like a cellular automaton, they follow certain rules and you turn the crank, time goes forward, whatever happens, happens. Now clearly you can get complexity from this. Clearly you can get some very interesting looking things, right? So the game of life, all, all those kinds of cool things, right? You can get complexity, no, no, no problem. But the idea that that model is going to be sufficient to, uh, explain and control the, uh, things like morphogenesis is a hypothesis. It's, it's okay to make that hypothesis but it, we, we know, we know it's false despite the fact that that is, eh, what, what we learn, you know, in, in, in basic, um, uh, uh, cell biology and, and developmental biology classes when the first time you see something like this inevitably, especially if you're an engineer in those classes, you raise your hand and you go, "Hey, how does it know to do that? How does it know, uh, the, you know, four fingers instead of seven?" What they tell you is, "It doesn't know anything." Make sure it m- that that's, that's very clear. They all insist that, right? When we learn these things they insist nu- none, nothing here knows anything. There are rules of chemistry, they roll forward and this is what happens. Okay. Now that model is testable. We can ask, does that model explain what happens? And here's where that model falls down. If you have that model and situations change, either, either there's damage or so- some- something in the, in the environment that ha- that's happened, those kind of open loop models do not adjust to give you, uh, to give you the same goal by different means. This is William James' definition of intelligence is same goal by different means. And in particular, working them backwards, let's say you are in regenerative medicine and you say, "Okay, but this is the situation now, I want it to be different." What should the rules be? It's not reversible. So the thing with those kind of open loop models is they're not reversible. You don't know what to do to make the outcome that you want. All you know how to do is roll them forward, right? Now in biology we see the following. Uh, if, if you have a, uh, developmental system and you put barriers between... So, so I'm gonna give you two pieces of evidence that suggest that there is a goal. One piece of evidence is that if you try to block these things from the outcome that they normally have, they will do some amazing things, uh, sometimes very clever things, sometimes not at all the way that they normally do it. Right? So this is William James' definition by different means, by following different trajectories, they will go around various local maxima and minima to get to where they need to go. It is navigation of a space. It is not blind, turn the crank and wherever we end up is where we end up. That is not what we see experimentally. And more importantly I think, what we've shown, and this is, this is, um, uh, this is something that I'm particularly happy with in our lab, over the last 20 years we've shown the following. We can actually rewrite the goal states because we found them. We, we have shown through, uh, through th- our work on bioelectric imaging and bioelectric re- reprogramming, we have actually shown how those goal memories are encoded, at least in some cases. We certainly haven't got them all, but we have some.If you can find where the goal state is encoded, read it out and reset it, and the system will now implement a new goal based on what you just reset, that is the ultimate, uh, evidence that- that your goal, uh, directed model is working. Because if there was no goal, that shouldn't be possible. You shouldn't ... Right? O- once you can find it, read it, uh, inter- interpret it, and rewrite it, it means that ... By- by any engineering standard, it means that you're dealing with a homeostatic mechanism.

   28. LFLex Fridman1:02:53

       How do you find where the goal is encoded?

   29. MLMichael Levin1:02:55

       So, through lots and lots of hard work.

   30. LFLex Fridman1:02:58

       The barrier thing is part of that? Creating barriers and observing?
7. 1:04:21 – 1:18:02

   Memories and ideas are living organisms

   1. MLMichael Levin1:04:21

      is.

   2. LFLex Fridman1:04:21

      Another pothead question. Is it possible to look at, uh ... Speaking of unconventional organisms, and going to Richard Dawkins, for example, with memes. Is it possible to think of things like ideas? Like, how weird can we get? Can we look at ideas as organisms, then creating barriers for those ideas, and seeing are the ideas themselves ... If you take the actual individual ideas and trying to empathize and visualize what kind of space they might be operating in, can they be seen as organisms that have a mind?

   3. MLMichael Levin1:04:58

      Yeah. Um, okay, if you wanna get really weird, we can- we can get- we can get really weird here. Uh, think about the, uh, caterpillar-butterfly transition. Okay? So, you got a caterpillar. Soft-bodied kinda creature. It has a particular controller that's suitable for running a soft-bodied, you know, kinda robot. It has a brain for that task, and then it has to become this butterfly, hard-bodied creature. Flies around (inaudible) . During the process of metamorphosis, its brain is basically ripped up and rebuilt from s- from- from scratch, right? Now, what's been found is that if you train the caterpillar, so you give it a new memory, meaning that if you ... If the caterpillar sees this color disk, then it crawls over and eats some leaves. Turns out, the butterfly retains that memory. Now, the obvious question is, how the hell do you retain memories when the medium is being refactored like that? Let's put that aside. That's ... I- I'm gonna get somewhere even weirder than that. There's something else that's even more interesting than that. It's not just that you have to, uh, retain the memory. You have to remap that memory onto a completely new context, because guess what? The butterfly doesn't move the way the caterpillar moves, and it doesn't care about leaves. It wants nectar from- from flowers. And so if your go ... If that memory is going to survive, it can't just persist. It has to-

   4. LFLex Fridman1:06:10

      Be remapped.

   5. MLMichael Levin1:06:11

      ... be remapped into a novel context. Now, here's where I ... Now- now here's- here's where things get weird. We can take a couple of different perspectives here. We can take the perspective of the caterpillar facing some sort of crazy singularity and saying, "My God, I'm gonna- I'm gonna cease to exist, but- but, you know, I'll sort of be reborn in this new higher dimensional world where I'll fly." Okay, so that's one thing. We can take the perspective of the butterfly and say that, "Well, here I am, but, you know, I- I seem to be saddled with some- some tendencies and some memories, and I don't know where the hell they came from, and- and- and I don't remember exactly how I got them, and they seem to be a core part of my psychological makeup, and- and, you know, they're- they're ... They come from somewhere. I don't know where they come from." Right? So you can take that perspective. But there's a third perspective that I think is really interesting and useful, and the third perspective is that of the memory itself. If you take a perspective of the memory, which- which ... Well, so what is a memory? It is a pattern. It is an informational pattern that was continuously reinforced within one cognitive system. And now here I am. I'm this memory. What do I need to do to persist into the future? Well, now I'm facing the paradox of change. If I- if I try to remain the same, I'm gone. There's no way the butterfly is gonna retain me in- in the original form that I'm in now. What I need to do is- is change, adapt, and morph. Now, you might say, "Well, that's kinda crazy. Uh, well, how are you taking the perspective of a din- of a- of a pattern within an excitable medium?" Right? Agents are physical things. You're talking about the per- you're talking about information, right? So- so let- let me- let me tell you another, um, quick, uh, science fiction story. Imagine that, uh, some creatures come out from the center of the earth. They live down in the core. They're super dense. Okay? They're incredibly dense because they live down in the core. They have gamma ray vision for, you know, for ... And- and so on. So they come out to the surface. What do they see? Well, all of this stuff that we're seeing here, this is like a thin plasma to them. They- they are so dense. None- none of this is- is- is- is solid to them. They- they don't see any of this stuff. So they're walking around, you know? They're ... The- the planet is sort of, uh, you know, covered in this, like, thin gas, you know? And one of them is a scientist, and he's- and he's taking measurements of the gas, and he says to the others, "You know, I've been watching this gas, and there are, like, these little whirlpools in this gas, and they almost look like agents. They almost look like they're doing things. They- they're moving around. They kinda hold themselves together for a little bit, and they're trying to make stuff happen." And- and- and the- the others say-Well, that's crazy. Patterns in a gas can't be agents, we are agents. We're- we're solid. This is just patterns in an excitable medium. And, by the way, how long do they hold together? He says, "Well, about 100 years." Well, that's crazy. Nothing, you know, no- no real agent can- can exist to be- be that, dissipate that fast. Okay, we- we are all metabolic patterns, among other things, right? And so one of the things that, and so you see what I'm warming up to- to here. So- so one of the things that we've been trying to, uh, dissolve, and this is, like, some work that I've done with Chris Fields and others, is this distinction between thoughts and thinkers. So, uh, all agents are patterns within some excitable medium, we could talk about what- what that is, and they can spawn off others. And now you can have a really interesting spectrum. Here's the, here's the spectrum. Um, you can have fleeting thoughts which are like waves in- in- in the ocean when you throw a rock in. You know, they sort of, they sort of go through the excitable medium and then they're gone. They pass through and they're gone, right? So those are, those are kind of fleeting thoughts. Then you can have patterns that have a degree of persistence, so they might be hurricanes or solitons or persistent thoughts or ear worms or depressive thoughts. Those are harder to get rid of. They ca- they stick around for a little while, they often do a little bit of niche construction, so they change the actual brain to have, to make it easier to have more of those thoughts, right? Like, that's a, that's a thing. And so they- they- they stay around longer. Now, uh, what's- what's further than that? Well, fragments, personality fragments of a dissociative personality disorder, they're more- more stable and they're not just on autopilot. They have goals and they can do things, and then past that is a full-blown human personality, and who the hell knows what's past that? Maybe some sort of trans-human, you know, trans-personal, like, I don't know, right? But- but this idea, again, I'm back to this notion of a spectrum. It's, there is not a sharp distinction between, you know, we are real agents and then we have these- these- these thoughts. Yeah, patterns can be agents too, but again, you don't know until you do the experiment. So if you want to know whether a soliton or a hurricane or a thought within a cognitive system is its own agent, do the experiment. See what it can do. Does it, can it learn from experience? Does it have memories? Does it have goal states? Does it, uh, you know, what- what can it do, right? Does it have language? So- so, uh, coming back to then, your- your original question, yeah, we can definitely a- apply this methodology to ideas and concepts and- and- and social, um, uh, you know, whatevers, but you've got to do the experiment.

   6. LFLex Fridman1:11:04

      That's such a challenging thought experiment of, like, thinking about memories, from the caterpillar to the butterfly as an organism. I think at the very basic level, intuitively, we think of organisms as hardware.

   7. MLMichael Levin1:11:20

      Yeah.

   8. LFLex Fridman1:11:20

      And, uh, software is not possibly being able to be organisms, but-

   9. MLMichael Levin1:11:25

      Right.

   10. LFLex Fridman1:11:26

       ... what you're saying is that it's all just patterns in an excitable medium and we, it doesn't really matter what the pattern is we need to... and- (laughs) and what- and what the excitable medium is. We need to do the testing of what, how persistent is it, how goal-oriented is it? And there's certain kind of tests to do that, and you can apply that to memories, you can apply that to ideas, you can apply that to anything, really. I mean, you could probably think about, like, consciousness. You could... there's really no, um, boundary to what you can imagine. Probably really, really wild things could be, could be minds.

Episode duration: 3:18:08