02:48

Levin

All right. Thank you so much for that extremely kind introduction, and thank you for having me here to share some thoughts with you. You can find all of the peer reviewed stuff, the papers, the data sets, everything is at this address, and then here is a personal blog of what I think some of these things mean. What I’m going to talk to you about today is bioelectricity, and specifically the use of bioelectricity as an interface to the plasticity of the agential material that makes up your body. And I think this has massive implications for biomedicine going forward.

I like to think of the endgame of our field as something called the anatomical compiler. Just think: someday you should be able to sit in front of a computer and draw the anatomy of the animal, plant, organ, biobot—whatever it is—you should be able to draw it, and this system will then compile that specification into a set of stimuli that would have to be given to cells to get them to build exactly what you want. So in this case I’m showing you this three-headed flatworm. But if we had something like this, then birth defects, traumatic injury, cancer, aging, degenerative disease, all of these things would go away. If you could convince cells to build whatever you wanted them to build, all of these things would go away.

Now, why don’t we have something like this? We’re actually very far away from it. Where we stand today with molecular medicine is that we’re very good at this kind of information: which cells, and what the cells are doing, what individual proteins are binding to what other proteins, which genes turn on and off other genes. The molecular information is very strong. But we’re quite a distance away from being able to restore limbs and repair birth defects and things like this. So why is that? I’m going to argue that this is because where medicine is today is where computer science was in the 1940s and 1950s.

In those days, in order to reprogram a computer to get it to do something different, you would have to physically interact with the hardware. Here she is: she’s rewiring the machine to get it to do something different. And so what I think we’ve just now started scratching the surface of is to understand actually the plasticity, and more specifically the intelligence, of the living material—meaning that it is reprogrammable. And for the same reason that you would laugh if I told you today that, on your laptop, to switch from Microsoft Word to PowerPoint you’d have to get out your soldering iron and start rewiring the thing. Right? We don’t do that anymore. Why? Because we understand that the material that we’re dealing with is reprogrammable. And living material is that and more.

So this is what we are made of. We’re made of individual cells. This is a free-living organism called the Lacrymaria, but it gives you an idea of what individual cells can do. This thing is incredibly competent in its own little sphere of influence here. There’s no brain. There’s no nervous system. It handles all of its physiological, metabolic, and so on and needs, all in one cell. In fact, all of us were a single cell once, and these cells did this amazing process of embryonic development where they became one of these complex organisms, or even perhaps a human. And, in fact, even below the single cell level, the molecular pathways within single cells already have learning capacity, right? The different signaling pathways and gene regulatory network components come together into a collective intelligence that is able to form six different kinds of memories, including Pavlovian conditioning. You don’t need a brain. You don’t need neurons. You don’t even need the cell. Just the molecular pathway alone has this capacity, and we are now creating devices that we’re using to train these pathways. And there’s many applications, like drug conditioning and so on.

So the idea here is that bodies are made of multiple levels—not just of different scales of organization, not just the nested dolls structurally, but actually every level has its own capability of solving problems in different spaces. We’re familiar with animals solving problems in the behavioral space, but your molecular networks, your cells, your tissues, all of them are constantly navigating these other problems. And we are made of this amazing multi-scale competency architecture. I’m going to give you just one example because time is short. I’m going to give you just one example of the kind of problem solving I mean.

This is a tadpole of the frog Xenopus laevis. You’ve got the brain here, here’s some nostrils, here’s the mouth, these are the eyes, and this is the gut. These tadpoles have to become frogs. In order for a tadpole to become a frog, it has to rearrange its face. So the eyes have to move, the mouth has to move, the nostrils—everything has to change. And you might think that this is a hardwired process, that somehow the genetics specifies that every organ moves in the correct distance, the correct direction, and then you get your frog. Well, we decided to test this, because any time you’re going to make a claim about the level of intelligence of something, you have to do experiments, you cannot just assume. So we decided to test that. We made so-called Picasso tadpoles where everything is scrambled. So the eyes on top of the head, the mouth is off to the side here, everything is mixed up, kind of like a Mr. Potatohead doll. Everything is mixed up. And then what we found is something amazing: that these animals give rise to pretty normal frogs.

And that’s because these organs don’t just move the right distance in the right direction—because then they would be wrong—they actually move in whatever way is needed through novel paths to get to where they’re going, and they make a correct frog face.

So this ability to reach your goal from different starting positions, get your goal satisfied despite novelty—things that you did not know were going to happen—is a key aspect of intelligence, of intelligent behavior. And so now you have to ask a simple question: how do these cells and tissues know what a correct frog face looks like? Okay? How do they store the memory of the endpoint? And we know they can remember the endpoint because they stop when they get there. When they achieve the normal frog face, then they stop. So how can we actually think about a collection of tissues storing these kinds of memories?

Well, we took our inspiration from what happens in the brain, which is a sort of familiar system where groups of cells store memories and guide behavior—in this case, in three-dimensional space. And the way it works in the brain is this. You have a network of cells. So here’s a neuron, it’s touching this other neuron down here. It has these little proteins called ion channels, which let charged molecules in and out. And as a result, it acquires a voltage, and that voltage may or may not be propagated to its neighbors. And the flow of electrical signaling through this network is what underlies all cognitive activity. And so here is a video that this group took of a living zebrafish brain, and you can see this amazing electrophysiology going on here. And it’s the commitment of neuroscience that if we could decode this—so this is the project of neural decoding—if we could decode this, then we would be able to read out the memories, the goals, the preferences of this animal. And so that is what we would like to do, but outside the brain: we want to do it for the rest of the body.

And the reason that’s possible is because, actually, this amazing system of using bioelectricity to integrate information, store memories, and guide intelligent behavior is way older than brains. It, in fact, evolved around the time of bacterial biofilms. It’s extremely ancient. And, in fact, every cell in your body has these ion channels. Most cells have these electrical synapses to their neighbors. And your tissues are running these electrophysiological networks. And so you might ask the question: what do they think about? We know what our brain thinks about. What do the body tissues think about? And so I’m going to tell you that one thing they think about is shape. They think about arranging the body in the correct shape and then maintaining that against aging, against injury, and against cancer.

So here, much like this video of this brain, we can start taking a look at the bioelectrical signals. This is a frog embryo. What you’re seeing is a timelapse of a frog embryo. And you can see all the electrical conversations that these cells are having with each other. Could we decode this? And here’s what some of these patterns look like. First of all, this is something we call the electric face. So again, here’s a timelapse of a frog embryo putting its face together. And there’s a lot going on here, but if you look at one frame of that video, you can see that, prior to the appearance of the craniofacial organs, this is the map that it’s going to build. Here’s where the animal’s right eye is going to go, here’s where the mouth is, here are the placodes. So what you are seeing here is literally reading out the electrical memories that tell the cells what a correct face is supposed to look like. And this is what guides normal development.

So we can now begin to read out what it is that these cells remember as the correct thing to build. And not only does this bioelectricity serve as a kind of cognitive glue that binds individual cells into a global vision of what the whole large-scale thing is supposed to look like, it actually does this for multiple embryos. Here you can see, if we poke this embryo, all of these guys find out about it. See this? So this injury wave, this bioelectrical communication, tends to merge subunits into a coherent whole. And you can see here these are individual cells.

By the way, the way that we are monitoring all of this is with voltage-sensitive fluorescent dyes. That’s a technology that we developed: to use these dyes to help understand what the cellular collectives are thinking.

Now, watching these patterns is all well and good. And, in fact, you can use them to diagnose birth defects and so on. But of course the more important thing is to start to rewrite these pattern memories. So if I’m telling you that these are memories, on the one hand, you want to be able to read and interpret them, and on the other you want to be able to reset them for therapeutics. And in order to reset them, we don’t use electrodes or fields or magnets. There are no waves, no frequencies, nothing like that. What we’re doing is manipulating the natural interface that these cells are using to control each other.

So on their surface they have these ion channels which set the voltage, and then here they communicate that voltage to each other. So just like neuroscientists do, we take all of those tools and we can use pharmacology to turn the channels on and off. We can use optogenetics and so on. So we can control the voltage and the communication between cells. So I’m going to show you very quickly three stories that illustrate why this is powerful and why this is important. And they work not because we’re so smart, they work because the system actually is using this electrical communication as a cognitive medium, as a decision-making substrate for determining growth and form of the organism.

So the first thing I’m going to show you is a quick story about cancer. So if we take nasty human oncogenes like K-RAS and P53 mutations and so on, and we inject them into tadpoles, they will eventually make a tumor. But before the tumor becomes apparent, you can already see, using this voltage imaging, that these cells have an aberrant voltage from their neighbors. And what happens is that that voltage causes them to disconnect from the network. Once you’ve disconnected from the network, you can no longer remember this grandiose goal that you had before, where the collective was working on building and maintaining organs. As far as you’re concerned, you’re an amoeba. The rest of the body is external environment, and that border between self and world has shrunk. The cognitive light cone of that cell has drastically shrunk. It is not more selfish than other cells, it just has a smaller self. So cancer is in large part a dissociative identity disorder of the cellular collective intelligence, and it happens by breaking these electrical connections.

Now, that weird way of thinking about it has implications. It means that instead of trying to kill these cells, you can actually try to force them to reconnect with the pattern, with the other cells that are holding the memory pattern. And so we’ve done that here by co-injecting—so here you inject the oncogene, but you also inject an ion channel that’s going to force the cell to be in the correct electrical state. And so these are the same animal. And so you can see the oncoprotein is blazingly strongly expressed. It’s all over the place, but there’s no tumor, okay? And there’s no tumor because it’s not the genetics that drives it, it’s not the mutation that determines the outcome, it’s the physiology and the cellular decision-making. And these cells are remaining connected and they are working on the same goal as they were before, making nice skin, nice muscle, whatever. Okay. So that’s a story at the level of single cells.

Now I’m going to show you what this means for birth defects. So here is a brain of a tadpole. And you can see here a forebrain, midbrain, and hindbrain. And what we can do is we can introduce a mutant to a gene called notch. And that’s a very important neurogenesis gene. And so these animals have a very abnormal brain. The forebrain is missing. The midbrain and hindbrain are a big bubble. You can see the difference. These animals are profoundly affected. They have no behavior to speak of. What we were able to do is to build a computational model of the electrical pattern that normally tells the brain what size and shape it’s supposed to be. And we simply ask the question: given this kind of disorder, what channels would you have to open and close to get back to the correct shape? And the computational model gave us an answer. And we found a couple of drugs already human approved. So this is already in use in patients for other reasons. But when you use them, here’s what happens. Now you get a normal brain. They have actually learning rates indistinguishable from controls. And yet they still have that mutation, okay? So this is an example—and I’m not saying this will always be possible—but this is an example of fixing what is fundamentally a hardware error, meaning the mutation: you fix it in software. You fix it by a computer-designed, brief biochemical intervention that resets the electrical patterns so that the tissues know what to do, and then they make a correct brain.

And the final story that I’m going to tell you is about limb regeneration. So adult frogs do not regenerate their legs, unlike salamanders. So if they happen to lose a leg, then 45 days later, there’s basically nothing. So we asked the question: could we communicate with these cells through the bioelectrical interface and guide them towards the leg-growing path in anatomical space instead of the scarring path? And so we designed a cocktail. Basically, a 24-hour application of that cocktail ends up with driving about a year and a half of leg growth. So at that point, immediately, within the first 24 hours, you get the proregenerative genes coming on here. This is MSX1. Then, by 45 days, you’ve already got some toes, you’ve got a toenail. Eventually, a pretty respectable leg, and it’s touch sensitive and it’s motile. Okay?

So again, keep in mind that, in this case, we did not have to manipulate that process during that whole time. We didn’t have to talk to the stem cells. There are no scaffolds here. We didn’t have to micromanage it at all. We provided a very early signal that said: go down the leg-building path. That’s it.

And so at this point I have to do a disclosure, because David Kaplan and I have a company called Morphoceuticals, where we are trying to push this forward to biomedical use such that, eventually—so now we’re trying this in mammals—and so eventually you will have these wearable bioreactors (not just for the limbs, but potentially for all organs) that would provide the correct bioelectrical payload in terms of ion channel drugs. So that would then trigger the growth—not trying to control every aspect of it, because you have no idea how to do that, but to provide a trigger stimulus.

And the final thing that I want to show you is the ability to induce novel organs, just to kind of nail the idea that what we’re doing here is reprogramming the pattern memories of these cells. So I showed you that little eye spot in the electric face, and we wondered what would happen if we reproduced that same pattern somewhere else. So what you can do is inject into this early embryo RNA encoding a particular ion channel that produces a little pattern of particular voltage. And sure enough, those cells get the message and they build an eye. Okay? In this case, on the gut. These eyes have all the same layers—right? The lens, optic nerve, all the same stuff.

And just notice what this means. First of all, it means that bioelectric, as I’ve shown you in these other examples, is instructive. It’s instructive at the organ level. We did not have to say which genes to turn on. We didn’t have to tell the stem cells what to do. We found a high-level subroutine call that says: “Build an eye here,” okay, and the cells are very competent in doing that. The material, as I was pointing out, is not only competent to receive low-information content stimuli and then have a very complex downstream response, but also it does this cool thing that other collective intelligences do—for example, ants. When ants come along a piece of food that’s too big for them to move, what do they do? They recruit other members of the community. Well, these cells do the same thing. If we inject a few cells, they can tell there’s not enough of them to build an eye, so what do they do? They recruit a bunch of cells from the environment that we did not inject at all. So there’s the ability for the material to scale itself to the message that they receive.

And, just to point out, if anybody is interested in plants, this is another great example of the plasticity of life. You might think that the oak genome encodes for this shape, because this is what you see most of the time. These acorns give rise to exactly this shape, this flat green thing. But along comes this non-human bioengineer, this wasp, which is a parasite which puts down some signals for the plant cells, and it hacks them. It hacks the morphogenesis exactly the way that I’ve been showing you that we can hack the morphogenetic outcomes in animals. And it causes these plant cells to build this incredible spiky round thing, or even this stuff. So these are galls. And we would have had no idea what these cells are capable of if we didn’t see this amazing example of bioprompting or reprogrammability. And, in fact, it’s kind of interesting that the sophistication of what is built is roughly parallel to the sophistication of the hacker. So bacteria and fungi make these kind of boring lumpy things. Nematodes and mites do a little better. But by the time you get to insects you get this beautiful kind of construct. So this is what we’re trying to do. It took millions of years for the wasps to be able to do this. We want to accelerate this process.

And so the last example I want to show you is a new kind of technology, which are basically synthetic biobots. So when you look at this, you might think that this is something we got from the bottom of a pond somewhere. But actually, I could tell you that, if you were to sequence it, it’s 100% Homo sapiens. These are human adult tracheal epithelial cells. We have a process that allows them to reboot their multicellularity into this little creature. It’s self-motile. Now, why is this interesting for biomedicine? What does this do? Well—and by the way, you would never guess that the human genome would make something like this. This is nothing like any stage of human development.

Well, one thing they have the capability of doing is healing wounds. So if you make a bunch of human neurons in a culture like this, and you put a big scratch through the middle, right—so kind of a wound assay—and then you put these bots into their environment, they form this thing called the superbot cluster. And here you can see what they’re starting to do. You lift them up four days later, you see that what they’ve done is knit the two sides of the wound together. So who would have thought that your tracheal epithelial cells that sit there quietly for a long time, just kind of getting rid of the mucus and so on, are capable of having a completely different life in a different form factor with the ability to heal some of your wounds? And this is just the beginning. This is just the first thing we discovered. They probably do a lot more.

And so we’re envisioning these anthrobots as personalized autonomous therapeutics. In other words, they’re made of your own cells. If we inject them into your body, you don’t need immune-suppressing drugs. You’re not going to reject them. They biodegrade within a few weeks. And, in the meantime, there might be many applications in which these things could be cleaning out joints, looking for cancer cells, dropping off pro-regenerative molecules, fixing up neural connections, and so on.

And so the bottom line is this. Much of biomedicine today is focused around these bottom-up technologies—so at the level of the hardware. But there’s a whole frontier of medicine that’s opening up which are in these top-down interventions that take advantage of the intelligence of the living material—not to micromanage molecular states, but to convince the cells and reset set points. We can train them. Here are the electroceuticals that I’ve been showing you, right, which are basically just signals to get the bioelectric pattern memories shifted in the right way. And, of course, AI is going to be very important in enabling us to communicate to all the different layers of the body. So my claim here is that future medicine is going to look a lot more like a kind of somatic psychiatry and not like chemistry, because the name of the game is going to be to really take advantage of the intelligence of these other layers of the body.

And the final thing I will just say is that, because of the plasticity of life and because of the innate problem-solving capacities of tissues, pretty much any combination of evolved material, engineered material, and software is some kind of possible embodied mind. So, in other words, cyborgs and hybrids and augmented humans and weird kinds of creatures that you could only begin to imagine—some of these already exist. Many are coming. They will be here with us in the future. And that means that we need to let go of old categories around living things versus machines and all that, because the entire variety of life (what Darwin called “endless forms most beautiful”) are a tiny corner in the space of possible beings. And I think we need to take very seriously the idea that this technology is not just about fixing all of the medical situations that plague us today, but also to release a kind of freedom of embodiment, where people really can reimagine their life in a very different way than the body they happen to have been given as an accident of the trial-and-error process of evolution. And we need to really work on a new way of synthbiosis, of living in a mutually beneficial way with beings that are going to be different from us.

So I’ll stop here. I’m just going to thank the postdocs and the students who have done the work that I showed you today. We have lots of amazing collaborators. I thank our funders who have supported this work. And the disclosures—these are the companies that have supported us over the years. So thank you very much, and I will stop there.

26:24

Levin

Sure. Yeah, yeah, no problem.

26:24

Levin

Yeah, yeah, great question. Absolutely. And we’re working on this. I mean, basically, after the individual cells disconnect from the normal network, they will eventually end up connecting within themselves to form something else that again tries to reinflate that cognitive light cone that was shrunk to the level of a single cell, and then they make a tumor, and then they compete with the rest of the body. And so, yeah, that process is absolutely a good target for cancer therapies. And we’re working on this stuff now.

27:42

Levin

Yeah, great question. And I have a talk on my site that’s about an hour just exactly on that question. To briefly sort of address it. Yeah, the software/hardware analogy is actually pretty good in this case. The genetics is what specifies the hardware available to cells. So the genetics tells every cell what ion channels it’s going to have, what voltage-transducing machinery it’s going to have, and so on. And everything that happens after that is really a function of the physiological software, which is both bioelectrical, but also biochemical, biomechanical, and so on. And we have a number of cases—and in this other lengthy talk I go through all of them—where you can actually see where the information diverges completely. Where, if you track the genetics or the transcriptomics or the proteomics, you get the wrong answer. And I kind of showed you this already in the case of the tadpole: when you look at the mutation, you would make a prediction, “Oh, it’s going to have a brain defect,” and that’s in fact not what happens in the cancer. In the cancer example you would find the oncogene mutation. You would say, “Okay, it’s going to have a tumor.” And again, you would be wrong, because the genetics gives you some information, and for certain things that’s sufficient, but for many things—especially these kind of anatomical outcomes—looking at the hardware is just not at all sufficient.

29:24

Levin

Yeah, thank you. That’s a very good question. Let me clarify. Bioelectricity is only interesting because it happens to be the cognitive glue that enables the scaling of intelligence. Forming into bioelectrical networks is how the tiny little goals of single cells—metabolic goals and proliferative goals and so on—are scaled up into grandiose goals like building a limb or a face and so on. It is the cognitive glue. That’s why it’s interesting. It’s otherwise not special by itself. But it happens to be very convenient, and that’s what evolution has chosen.

I would claim—and this is a controversial claim; this is not the mainstream view, so take this with whatever grain of salt you want, but here’s my claim. I think there is a general theory of biology that is being developed now. I mean, this is what we’re trying to do, and some other people. And that theory is going to be in the shape of things familiar to behavior science, not things familiar to physics and chemistry. I don’t think you should be looking for equations. I don’t think you should be looking for emergence, complexity theory, dynamical systems theory. These are all nice, but these are not the backbone of biology. I think the backbone of biology and things we call life are just systems that are very good at scaling up the cognitive properties of their parts into bigger and bigger cognitive light cones.

And so what we are going to get, it’s natural that the unified theories of physics come out in numbers or various other—I’m not even sure that’s true anymore—but various other kinds of constructs. The overall theory of biology is going to be all around goals, memories, preferences, and basically terms that you would recognize from psychology and behavior science. And that’s because the fundamental interesting thing about life is not any of the dynamics that are currently studied in chemistry and so on, it’s the creative problem-solving of the material. And it starts very early on. It goes below the single cell level, and you don’t need cells for it. But the story of life is the story of scaling up intelligence. And so this is why we use bioelectricity: because it’s an interface, one way to demonstrate what I’m talking about. It’s a convenient interface to the intelligence of life. That’s its only goal. It’s only a role here. And I think the theory of biology is going to be basically a theory of intelligence. And it’s already begun. This is not a science fiction pipe dream. Those theories are exactly what enable us to regenerate the limbs and normalize tumors, repair birth defects, and so on. It’s precisely because that way of seeing the biological material is fruitful and opens new avenues in therapeutics.

32:39

Levin

Yeah, a couple of things. There are pathologies that are fundamentally bioelectrical errors. I’m sure there are many pathologies that are not. So this is not a blanket solution for everything. Memory loss is a whole other—if you want to email me about it, I’ll point you to some stuff that we’ve done on this. The storage of memory, and how it moves across tissues in the body, and how much of it is in the brain and how much of it is not—these are all really interesting kinds of things, and there are some developments coming on that front that I think are going to overturn some of the current assumptions. So it’s too early to say much yet for sure, but I do think that there are some radically different therapeutics coming on that front.

34:11

Levin

Yeah, of course, you picked some big ones. Okay, I’ll do the last one first. In some cases, it’s very helpful to look at genes as the unit of selection, and so on. I think, fundamentally, what’s going on in biology is the unit of selection is the perspective. It is observers—and when I say “observers,” I don’t mean humans, necessarily; not just humans, but every active system is an observer that has a perspective of some degree—and it is different perspectives trying to interpret, hack, compete with, and cooperate with each other. All of this is really a differential battle of perspective. And I think that’s true for bioelectrics, and I could tell you a whole thing about how, when we inject the ion channel to make the eye, there’s a battle of world views that goes on, basically, where there’s a bunch of cells that are saying to their neighbors, “Hey, help us make this eye,” and they are using their cancer-suppression mechanism to say to the cells we injected, “No, you guys have a weird goal. You should be like us and be nice, normal skin.” And those two stories kind of battle each other out in the bioelectric patterns until one of them wins.

Anyway, what is it going to look like in the future? I suspect right now that what’s going to happen is that there’s going to be a software system with an AI front end, which will probably speak in normal human language. And what’s going to happen is it’s going to have access to the various measurables that are available in your body. There’s a ton of people working on all kinds of wearables that are collecting data about your body, various scans that you might do, maybe electrical, probably other things too. And what it’s going to be able to do is, basically, in effect, allow you to communicate with the various subsystems of your body. So you’re going to have a conversation with your various organs and systems, and/or your doctor will, and what you’re going to end up doing is all of the kinds of things that you do in the behavioral sciences. For some of it, you will be training your cells and tissues with specific stimuli. In some cases you will be resetting set points. In some cases you will be providing other kinds of information. And those will come through electroceuticals, which are drugs, ion channel modifying compounds that you would take systemically. And in some cases it might be optogenetics, meaning light patterns put down in certain cell groups that turn channels on and off, and they are able to transmit information through the electrical interface.

So, you know, it’s too early to paint the entire picture. But I think we can do quite a lot with electroceuticals and with optogenetics—if we could crack the bioelectric code. What we really are doing now is trying to understand what are the capabilities of the tissue? What are the messages that get the tissue to do specific things? That’s it. Once we have that, it’s a roadmap for pretty transformative applications.

37:55

Levin

Yes, I think that’s right. I think any mature theory of how networks learn, in this case, is going to have to be a multi-scale theory that takes into account the fact that the individual cells have agendas, and memories, and preferences, and problem-solving competencies—and even the molecular mechanisms inside of them have it, too. I don’t see any way how we could get to the bottom of these things and have all of the applications that will come of it without having a mature theory of the scaling of intelligence from the lower levels up through the higher levels.

39:05

Levin

Wow! Yeah. I mean, I don’t think we can predict the next ten years, never mind 100,000 years out. But I will just say this. I mean, if I have to think about it, the way that I envision this is that—you know how, when you first went to school and you heard about cavemen, and it really sinks in that like, wow, if you stepped on a sharp stick, you’ll get an infection and you’ll die. How did they live this way? And this is what I see: people in the future—and I don’t think it will be a very long out future—they will look back and will say, “You’re telling me that these people had to live their entire life subjected to dumb bacteria, viruses, some kind of effect of some stray cosmic ray hitting their cells when they were in embryo? They had to live in whatever body they were given at birth by accident? Not chosen for them by anybody for their well-being, but just the results of trial and error process of mutation and selection? And they had to live like this? And their IQs were limited to whatever they were given? And they would age and have lower back pain and astigmatism and kidney failure and all this loss of mental acuity and all this? Unbelievable! How did people live this way?” And that’s what I see. I see a world in which most of the things that we struggle with today are just even unimaginable. And I cannot imagine myself that a mature species come back—even under a hundred years from now—you come back and you look, and we’re still walking around with all of these susceptibilities and limitations. It just can’t be. And I think we can see a way past it. Assuming we all survive, I think that’s where we’re going.

41:29

Levin

Yeah, I think it is. And I think we’re going to have the same problem that we have in ethology or behavioral science or exobiology if we were to meet aliens. What you’re dealing with is a mind that is not really like your mind. And so the things they care about, the things that they can think about, the space that they’re operating in is different. So you’re not going to have a conversation with your liver about the movie that you saw and so on, but you absolutely could have a conversation with your liver about what it’s like to live in physiological state space, and what happened yesterday when you drank too much, and your hopes for the future where things sort of balance out correctly with your potassium flux, and so on. So these are not conventional human minds, but they are absolutely intelligences that you can have some kind of relationship with.

42:52

Levin

I don’t know if you want exactly that! It’s not all it’s cracked up to be. But I’m happy to help you with this. Send me an email and you can come to my Zoom office hours, where I talk about this question with a lot of people, and I can give you some guidance.

43:26

Levin

I don’t think you can do away with cancer once and for all, because cancer is a fundamental failure mode of the system that keeps us together. The question isn’t, “Why do we get cancer?” The question is, “Why isn’t it all cancer all the time? Why do we have anything but cancer?” And it’s because of these communication networks that allow cells to join together to have bigger goals—goals about shape instead of metabolism. And I don’t think you’re ever going to get rid of that once and for all, I don’t think. But we will, of course, have effective treatments and preventative strategies for you. I just don’t think you can make it disappear.

But fixing things prior to birth—absolutely. And this is what our program on detection and repair of birth defects is all about. So I think, yes, I think all kinds of augmentations will be possible. I think repair of birth defects will be possible for sure.

44:37

Levin

This gets into things that are still not known. I mean, some aspects that are due to brain structure and physiology I think will be completely fixable. But there are other things. One way of saying it is: “the thought that breaks the thinker,” you know? There are problems that are not organic disease. There are ways of thinking or experiences that lead to specific patterns of thought that are harmful. Those things are not going to be handled at the level of repairing the brain. Now you’re into psychoanalysis, and environment, and conversations, and love, and whatever else. So some of it will have an organic path, but you will still have the issue of people who get depressed because they realize certain existential questions about the universe that drive them crazy and whatever. Those things will always be here.

45:42

Levin

Thank you so much, everybody. Amazing questions. And thank you for having me.

45:52

Levin

Well, two things. My lab website is drmichaellevin.org. One word, drmichaellevin.org. And my blog is thoughtforms.life. Thoughtforms.life. And there’s all kinds of wacky pieces there about all the things that I talked about today.

46:23

Levin

Thank you. I appreciate that a lot. Have a look at Curt’s channel. He and I have done a bunch of interviews that were really good. So thank you, everyone.