The following is a conversation with David Eagleman, a neuroscientist and one of the great science communicators of our time, exploring the beauty and mystery of the human brain. He's an author of a lot of amazing books about the human mind, and his new one called LiveWired. LiveWired is a work of 10 years on a topic that is fascinating to me, which is neuroplasticity or the malleability of the human brain.

Quick summary of the sponsors. Athletic Greens, BetterHelp, and Cash App. Click the sponsor links in the description to get a discount and to support this podcast. As a side note, let me say that the adaptability of the human mind at the biological, chemical, cognitive, psychological, and even sociological levels is the very thing that captivated me many years ago when I first began to wonder how we might engineer something like it in the machine.

The open question today in the 21st century is what are the limits of this adaptability? As new, smarter and smarter devices and AI systems come to life, or as better and better brain-computer interfaces are engineered, will our brain be able to adapt, to catch up, to excel? I personally believe yes, that we're far from reaching the limitation of the human mind and the human brain, just as we are far from reaching the limitations of our computational systems.

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You have a new book coming out on "The Changing Brain." Can you give a high-level overview of the book? It's called "LiveWired," by the way. - Yeah. So the thing is, we typically think about the brain in terms of the metaphors we already have, like hardware and software. That's how we build all our stuff.

But what's happening in the brain is fundamentally so different. So I coined this new term LiveWire, which is a system that's constantly reconfiguring itself physically as it learns and adapts to the world around it. It's physically changing. - So it's LiveWire, meaning like hardware, but changing. - Yeah, exactly.

Well, the hardware and the software layers are blended. And so, typically, engineers are praised for their efficiency in making something really clean and clear, like, okay, here's the hardware layer, then I'm gonna run software on top of it. And there's all sorts of universality that you get out of a piece of hardware like that that's useful.

But what the brain is doing is completely different. And I am so excited about where this is all going because I feel like this is where our engineering will go. So currently, we build all our devices a particular way. But I can't tear half the circuitry out of your cell phone and expect it to still function.

But you can do that with the brain. So just as an example, kids who are under about seven years old can get one half of their brain removed. It's called a hemispherectomy. And they're fine. They have a slight limp on the other side of their body, but they can function just fine that way.

And this is generally true. Sometimes children are born without a hemisphere. And their visual system rewires so that everything is on the single remaining hemisphere. What thousands of cases like this teach us is that it's a very malleable system that is simply trying to accomplish the tasks in front of it by rewiring itself with the available real estate.

- How much of that is a quirk or a feature of evolution? Like how hard is it to engineer? 'Cause evolution took a lot of work. Trillions of organisms had to die to create this thing we have in our skull. 'Cause you said you kind of look forward to the idea that we might be engineering our systems like this in the future, like creating live wire systems.

How hard do you think is it to create systems like that? - Great question. It has proven itself to be a difficult challenge. What I mean by that is even though it's taken evolution a really long time to get where it is now, all we have to do now is peek at the blueprints.

It's just three pounds, this organ, and we just figure out how to do it. But that's the part that I mean is a difficult challenge because there are tens of thousands of neuroscientists. We're all poking and prodding and trying to figure this out, but it's an extremely complicated system.

But it's only gonna be complicated until we figure out the general principles. Exactly like if you had a magic camera and you could look inside the nucleus of a cell and you'd see hundreds of thousands of things moving around or whatever, and then it takes Crick and Watts and say, oh, you're just trying to maintain the order of the base pairs and all the rest is details.

Then it simplifies it and we come to understand something. That was my goal in live wire, which I've written over 10 years, by the way, is to try to distill things down to the principles of what plastic systems are trying to accomplish. - But to even just linger, you said it's possible to be born with just one hemisphere and you still are able to function.

First of all, just to pause on that, I mean, that's amazing. I don't know if people quite, I mean, you kind of hear things here and there. This is why I'm really excited about your book is I don't know if there's definitive sort of popular sources to think about this stuff.

I mean, there's a lot of, I think from my perspective, what I heard is there's been debates over decades about how much neuroplasticity there is in the brain and so on and people have learned a lot of things and now it's converging towards people that are understanding this much more neuro, much more plastic than people realize.

But just like linger on that topic, like how malleable is the hardware of the human brain? Maybe you said children at each stage of life. - Yeah, so here's the whole thing. I think part of the confusion about plasticity has been that there are studies at all sorts of different ages and then people might read that from a distance and they think, oh, well, Fred didn't recover when half his brain was taken out and so clearly you're not plastic, but then you do it with a child and they are plastic.

And so part of my goal here was to pull together the tens of thousands of papers on this, both from clinical work and from, all the way down to the molecular and understand what are the principles here? The principles are that plasticity diminishes, that's no surprise. By the way, we should just define plasticity.

It's the ability of a system to mold into a new shape and then hold that shape. That's why we make things that we call plastic because they are moldable and they can hold that new shape, like a plastic toy or something. - And so maybe we'll use a lot of terms that are synonymous.

So something is plastic, something is malleable, changing, live wire, the name of the book is synonymous. - So I'll tell you, exactly right, but I'll tell you why I chose live wire instead of plasticity. So I use the term plasticity in the book, but sparingly, because that was a term coined by William James over 100 years ago and he was, of course, very impressed with plastic manufacturing, that you could mold something into shape and then it holds that.

But that's not what's actually happening in the brain. It's constantly rewiring your entire life. You never hit an end point. The whole point is for it to keep changing. So even in the few minutes of conversation that we've been having, your brain is changing, my brain is changing. Next time I see your face, I will remember, oh yeah, like that time Lex and I sat together and we did these things.

- I wonder if your brain will have a Lex thing going on for the next few months. It'll stay there until you get rid of it 'cause it was useful for now. - Yeah, no, I'll probably never get rid of it. Let's say for some circumstance, you and I don't see each other for the next 35 years.

When I run into you, I'll be like, oh yeah. - That looks familiar. - Yeah, yeah, and we sat down for a podcast back when there were podcasts. Exactly. - Back when we lived outside virtual reality. - Exactly. - So you chose LiveWIRE to mold our plastic. - Exactly, because plastic implies, I mean, it's the term that's used in the field and so that's why we need to use it still for a while.

But yeah, it implies something gets molded into shape and then holds that shape forever. But in fact, the whole system is completely changing. - Then back to how malleable is the human brain at each stage of life? So what, just at a high level, is it malleable? - So yes, and plasticity diminishes.

But one of the things that I felt like I was able to put together for myself after reading thousands of papers on this issue is that different parts of the brain have different plasticity windows. So for example, with the visual cortex, that cements itself into place pretty quickly over the course of a few years.

And I argue that's because of the stability of the data. In other words, what you're getting in from the world, you've got a certain number of angles, colors, shapes, you know, it's essentially the world is visually stable. So that hardens around that data. As opposed to, let's say the somatosensory cortex, which is the part that's taking information from your body, or the motor cortex right next to it, which is what drives your body.

The fact is bodies are always changing. You get taller over time, you get fatter, thinner over time, you might break a leg and have to limp for a while, stuff like that. So because the data there is always changing, and by the way, you might get on a bicycle, you might get a surfboard, things like that.

Because the data is always changing, that stays more malleable. And when you look through the brain, you find that it appears to be this, you know, how stable the data is determines how fast something hardens into place. But the point is, different parts of the brain harden into place at different times.

- Do you think it's possible that depending on how much data you get on different sensors, that it stays more malleable longer? So like, you know, if you look at different cultures that experience, like if you keep your eyes closed, or maybe you're blind, I don't know, let's say you keep your eyes closed for your entire life, then the visual cortex might be much less malleable.

The reason I bring that up is like, you know, maybe we'll talk about brain-computer interfaces a little bit down the line, but you know, like is this, is the malleability a genetic thing, or is it more about the data, like you said, that comes in? - Ah, so the malleability itself is a genetic thing.

The big trick that Mother Nature discovered with humans is make a system that's really flexible, as opposed to most other creatures to different degrees. So if you take an alligator, it's born, its brain does the same thing every generation. If you compare an alligator 100,000 years ago to an alligator now, they're essentially the same.

We, on the other hand, as humans, drop into a world with a half-baked brain, and what we require is to absorb the culture around us, and the language, and the beliefs, and the customs, and so on, that's what Mother Nature has done with us, and it's been a tremendously successful trick.

We've taken over the whole planet as a result of this. - So that's an interesting point, I mean, just to linger on it, that, I mean, this is a nice feature, like if you were to design a thing to survive in this world, do you put it at age zero, already equipped to deal with the world in a like hard-coded way, or do you put it, do you make it malleable and just throw it in, take the risk that you're maybe going to die, but you're going to learn a lot in the process, and if you don't die, you'll learn a hell of a lot to be able to survive in the environment.

- So this is the experiment that Mother Nature ran, and it turns out that, for better or worse, we've won. I mean, yeah, we put other animals into zoos, and we, yeah, that's right. - AI might do better. - Okay, fair enough, that's true. And maybe what the trick Mother Nature did is just the stepping stone to AI, but.

- So that's a beautiful feature of the human brain, that it's malleable, but let's, on the topic of Mother Nature, what do we start with? Like how blank is the slate? - Ah, so it's not actually a blank slate. What it's, terrific engineering that's set up in there, but much of that engineering has to do with, okay, just make sure that things get to the right place.

For example, like the fibers from the eyes getting to the visual cortex, or all this very complicated machinery in the ear getting to the auditory cortex and so on. So things, first of all, there's that. And then what we also come equipped with is the ability to absorb language and culture and beliefs and so on.

So you're already set up for that. So no matter what you're exposed to, you will absorb some sort of language. That's the trick, is how do you engineer something just enough that it's then a sponge that's ready to take in and fill in the blanks? - How much of the malleability is hardware?

How much is software? Is that useful at all in the brain? So what are we talking about? So there's neurons, there's synapses, and all kinds of different synapses, and there's chemical communication, like electrical signals, and there's chemical communication from the synapses. What, I would say, the software would be the timing and the nature of the electrical signals, I guess, and the hardware would be the actual synapses.

So here's the thing. This is why I really, if we can, I wanna get away from the hardware and software metaphor, because what happens is, as activity passes through the system, it changes things. Now, the thing that computer engineers are really used to thinking about is synapses, where two neurons connect.

Of course, each neuron connects with 10,000 of its neighbors, but at a point where they connect, what we're all used to thinking about is the changing of the strength of that connection, the synaptic weight. But in fact, everything is changing. The receptor distribution inside that neuron, so that you're more or less sensitive to the neurotransmitter.

Then the structure of the neuron itself, and what's happening there, all the way down to biochemical cascades inside the cell, all the way down to the nucleus, and for example, the epigenome, which is these little proteins that are attached to the DNA that cause conformational changes, that cause more genes to be expressed or repressed.

All of these things are plastic. The reason that most people only talk about the synaptic weights is because that's really all we can measure well. And all this other stuff is really, really hard to see with our current technology, so essentially that just gets ignored. But in fact, the system is plastic at all these different levels.

And my way of thinking about this is an analogy to pace layers. So pace layers is a concept that Stewart Brand suggested about how to think about cities. So you have fashion, which changes rapidly in cities. You have governance, which changes more slowly. You have the structure, the buildings of a city, which changes more slowly, all the way down to nature.

You've got all these different layers of things that are changing at different paces, at different speeds. I've taken that idea and mapped it onto the brain, which is to say you have some biochemical cascades that are just changing really rapidly when something happens, all the way down to things that are more and more cemented in there.

And this is actually, this actually allows us to understand a lot about particular kinds of things that happen. For example, one of the oldest, probably the oldest rule in neurology is called Ribo's Law, which is that older memories are more stable than newer memories. So when you get old and demented, you'll be able to remember things from your young life.

Maybe you'll remember this podcast, but you won't remember what you did a month ago or a year ago. And this is a very weird structure, right? No other system works this way, where older memories are more stable than newer memories. But it's because through time, things get more and more cemented into deeper layers of the system.

And so this is, I think, the way we have to think about the brain, not as, okay, you've got neurons, you've got synaptic weights, and that's it. - So yeah, so the idea of liveware and livewired is that it's like a, it's a gradual, yeah, it's a gradual spectrum between software and hardware.

And so the metaphors completely doesn't make sense. 'Cause like when you talk about software and hardware, it's really hard lines. I mean, of course, software is unlike hardware, but even hardware, but like, so there's two groups, but in the software world, there's levels of abstractions, right? There's the operating system, there's machine code, and then it gets higher and higher levels.

But somehow that's actually fundamentally different than the layers of abstractions in the hardware. But in the brain, it's all like the same. And I love the city, the city metaphor. I mean, yeah, it's kind of mind-blowing, 'cause it's hard to know what to think about that. Like if I were to ask the question, this is an important question for machine learning, is how does the brain learn?

So essentially you're saying that, I mean, it just learns on all of these different levels at all different paces. - Exactly right. And as a result, what happens is as you practice something, you get good at something, you're physically changing the circuitry. You're adapting your brain around the thing that is relevant to you.

So let's say you take up, do you know how to surf? - Nope. - Okay, great. Let's say you take up surfing now at this age. What happens is you'll be terrible at first, you don't know how to operate your body, you don't know how to read the waves, things like that.

And through time you get better and better. What you're doing is you're burning that into the actual circuitry of your brain. You're of course conscious when you're first doing it, you're thinking about, okay, where am I doing? What's my body weight? But eventually when you become a pro at it, you are not conscious of it at all.

In fact, you can't even unpack what it is that you did. Think about riding a bicycle. You can't describe how you're doing it. You're just doing it, you're changing your balance when you come, you know, you do this to go to a stop. So this is what we're constantly doing is actually shaping our own circuitry based on what is relevant for us.

Survival of course being the top thing that's relevant, but interestingly, especially with humans, we have these particular goals in our lives, computer science, neuroscience, whatever. And so we actually shape our circuitry around that. - I mean, you mentioned this gets slower and slower with age, but is there, like I've, I think I've read and spoken offline, even on this podcast with a developmental neurobiologist, I guess would be the right terminology, is like looking at the very early, like from embryonic stem cells to like, to the creation of the brain.

And like, that's like, what, that's mind blowing how much stuff happens there. So it's very malleable at that stage. And then, but after that, at which point does it stop being malleable? - So that's the interesting thing is that it remains malleable your whole life. So even when you're an old person, you'll be able to remember new faces and names.

You'll be able to learn new sorts of tasks. And thank goodness, 'cause the world is changing rapidly in terms of technology and so on. I just sent my mother an Alexa and she figured out how to go in the settings and do the thing. And I was really impressed by that, that she was able to do it.

So there are parts of the brain that remain malleable their whole life. The interesting part is that really your goal is to make an internal model of the world. Your goal is to say, okay, the brain is trapped in silence and darkness, and it's trying to understand how the world works out there, right?

- I love that image. Yeah, I guess it is. - Yeah. - You forget, it's like this lonely thing is sitting in its own container and trying to actually throw a few sensors, figure out what the hell's going on. - You know what I sometimes think about is that movie, "The Martian" with Matt Damon.

I mean, it was written in a book, of course, but the movie poster shows Matt Damon all alone on the red planet. And I think, God, that's actually what it's like to be inside your head and my head and anybody's head is that you're essentially on your own planet in there.

And I'm essentially on my own planet. And everyone's got their own world where you've absorbed all of your experiences up to this moment in your life that have made you exactly who you are and same for me and everyone. And we've got this very thin bandwidth of communication and I'll say something like, "Oh yeah, that tastes just like peaches." And you'll say, "Oh, I know what you mean." But the experience, of course, might be vastly different for us.

But anyway, yes, so the brain is trapped in silence and darkness, each one of us. And what it's trying to do, this is the important part, it's trying to make an internal model of what's going on out there, what's my place in, how do I function in the world?

How do I interact with other people? Do I say something nice and polite? Do I say something aggressive and mean? Do I, you know, all these things that it's putting together about the world. And I think what happens when people get older and older, it may not be that plasticity is diminishing.

It may be that their internal model essentially has set itself up in a way where it says, "Okay, I've pretty much got a really good understanding of the world now and I don't really need to change." When much older people find themselves in a situation where they need to change, they can actually or are able to do it.

It's just that I think this notion that we all have that plasticity diminishes as we grow older is in part because the motivation isn't there. - I see. - But if you were 80 and you get fired from your job and suddenly had to figure out how to program a WordPress site or something, you'd figure it out.

- Got it. So the capability, the possibility of change is there. But let me ask the highest challenge, the interesting challenge to this plasticity, to this liveware system. If we could talk about brain-computer interfaces and Neuralink, what are your thoughts about the efforts of Elon Musk, Neuralink, BCI in general in this regard, which is adding a machine, a computer, the capability of a computer to communicate with the brain and the brain to communicate with a computer at the very basic applications and then like the futuristic kind of thoughts?

- Yeah. First of all, it's terrific that people are jumping into doing that 'cause it's clearly the future. The interesting part is our brains have pretty good methods of interacting with technology. So maybe it's your fat thumbs on a cell phone or something, or maybe it's watching a YouTube video and getting into your eye that way.

But we have pretty rapid ways of communicating with technology and getting data. So if you actually crack open the skull and go into the inner sanctum of the brain, you might be able to get a little bit faster, but I'll tell you, I'm not so sanguine on the future of that as a business.

And I'll tell you why. It's because there are various ways of getting data in and out. And an open-head surgery is a big deal. Neurosurgeons don't wanna do it 'cause there's always risk of death and infection on the table. And also it's not clear how many people would say, I'm gonna volunteer to get something in my head so that I can text faster, 20% faster.

So I think it's, Mother Nature surrounds the brain with this armored bunker of the skull because it's a very delicate material. And there's an expression in neurosurgery about the brain is, the person is never the same after you open up their skull. Now, whether or not that's true or whatever, who cares?

But it's a big deal to do an open-head surgery. So what I'm interested in is how can we get information in and out of the brain without having to crack the skull open? - Got it, without messing with the biological part, like directly connecting or messing with the intricate biological thing that we got going on that seems to be working.

- Yeah, exactly. And by the way, where Neuralink is going, which is wonderful, is going to be in patient cases. It really matters for all kinds of surgeries that a person needs, whether for Parkinson's or epilepsy or whatever. It's a terrific new technology for essentially sewing electrodes in there and getting more higher density of electrodes.

So that's great. I just don't think as far as the future of BCI goes, I don't suspect that people will go in and say, "Yeah, drill a hole in my head and do that." - Well, it's interesting 'cause I think there's a similar intuition, but say in the world of autonomous vehicles, that folks know how hard it is and it seems damn impossible.

The similar intuition about, I'm sticking on the Elon Musk thing, is just a good, easy example. Similar intuition about colonizing Mars. If you really think about it, it seems extremely difficult and almost, I mean, just technically difficult to a degree where you wanna ask, is it really worth doing, worth trying?

And then the same is applied with BCI. But the thing about the future is it's hard to predict. So the exciting thing to me with, so once it does, once, if successful, it's able to help patients, it may be able to discover something very surprising of our ability to directly communicate with the brain.

So exactly what you're interested in is figuring out how to play with this malleable brain, but help assist it somehow. I mean, it's such a compelling notion to me that we're now working on all these exciting machine learning systems that are able to learn from data. And then if we can have this other brain that's a learning system that's live wired on the human side and then be able to communicate, it's like a self-play mechanism was able to beat the world champion at Go.

So they can play with each other, the computer and the brain, like when you sleep. I mean, there's a lot of futuristic kind of things that it's just exciting possibilities. But I hear you, we understand so little about the actual intricacies of the communication of the brain that it's hard to find the common language.

- Well, interestingly, the technologies that have been built don't actually require the perfect common language. So for example, hundreds of thousands of people are walking around with artificial ears and artificial eyes, meaning cochlear implants or retinal implants. So this is, you take a essentially digital microphone, you slip an electrode strip into the inner ear and people can learn how to hear that way.

Or you take an electrode grid and you plug it into the retina at the back of the eye and people can learn how to see that way. The interesting part is those devices don't speak exactly the natural biological language, they speak the dialect of Silicon Valley. And it turns out that as recently as about 25 years ago, a lot of people thought this was never gonna work.

They thought it wasn't gonna work for that reason, but the brain figures it out. It's really good at saying, okay, look, there's some correlation between what I can touch and feel and hear and so on. And the data that's coming in or between, I clap my hands and I have signals coming in there and it figures out how to speak any language.

- Oh, that's fascinating. So like no matter if it's Neuralink, so directly communicating with the brain or it's a smartphone or Google Glass or the brain figures out the efficient way of communication. - Well, exactly, exactly. And what I've proposed is the potato head theory of evolution, which is that all our eyes and nose and mouth and ears and fingertips, all this stuff is just plug and play.

And the brain can figure out what to do with the data that comes in. And part of the reason that I think this is right, and I care so deeply about this, is when you look across the animal kingdom, you find all kinds of weird peripheral devices plugged in and the brain figures out what to do with the data.

And I don't believe that mother nature has to reinvent the principles of brain operation each time to say, oh, now I'm gonna have heat pits to detect infrared. Now I'm gonna have something to detect, you know, electro receptors on the body. Now I'm gonna detect something to pick up the magnetic field of the earth with cryptochromes in the eye.

And so instead the brain says, oh, I got it. There's data coming in. Is that useful? Can I do something with it? Oh, great, I'm gonna mold myself around the data that's coming in. - It's kind of fascinating to think that we think of smartphones and all this new technology as novel.

It's totally novel as outside of what evolution ever intended or like what nature ever intended. It's fascinating to think that like the entirety of the process of evolution is perfectly fine and ready for the smartphone and the internet. Like it's ready. It's ready to be valuable to that. And whatever comes to cyborgs, to virtual reality, we kind of think like this is, you know, there's all these like books written about what's natural and we're like destroying our natural selves by like embracing all this technology.

It's kind of, you know, we're probably not giving the brain enough credit. Like this thing is just fine with new tech. - Oh, exactly. It wraps itself around. And by the way, wait till you have kids. You'll see the ease with which they pick up on stuff. And as Kevin Kelly said, technology is what gets invented after you're born.

But the stuff that already exists when you're born, that's not even tech, that's just background furniture. Like the fact that the iPad exists for my son and daughter, like that's just background furniture. So yeah, it's because we have this incredibly malleable system, it just absorbs whatever is going on in the world and learns what to do with it.

- But do you think, just to linger for a little bit more, do you think it's possible to co-adjust? Like we're kind of, you know, for the machine to adjust to the brain, for the brain to adjust to the machine I guess that's what's already happening. - Sure, that is what's happening.

So for example, when you put electrodes in the motor cortex to control a robotic arm for somebody who's paralyzed, the engineers do a lot of work to figure out, okay, what can we do with the algorithm here so that we can detect what's going on from these cells and figure out how to best program the robotic arm to move given the data that we're measuring from these cells.

But also the brain is learning too. So, you know, the paralyzed woman says, wait, I'm trying to grab this thing. And by the way, it's all about relevance. So if there's a piece of food there and she's hungry, she'll figure out how to get this food into her mouth with the robotic arm because that is what matters.

- Well, that's, okay, first of all, that paints a really promising and beautiful, for some reason, really optimistic picture that our brain is able to adjust to so much. You know, so many things happened this year, 2020, that you think like, how are we ever going to deal with it?

And it's somehow encouraging and inspiring that we're going to be okay. - Well, that's right. I actually think, so 2020 has been an awful year for almost everybody in many ways, but the one silver lining has to do with brain plasticity, which is to say we've all been on our gerbil wheels.

We've all been in our routines. And as I mentioned, our internal models are all about how do you maximally succeed? How do you optimize your operation in this circumstance where you are, right? And then all of a sudden, bang, 2020 comes, we're completely off our wheels. We're having to create new things all the time and figure out how to do it.

And that is terrific for brain plasticity because, and we know this because there are very large studies on older people who stay cognitively active their whole lives. Some fraction of them have Alzheimer's disease physically, but nobody knows that when they're alive. Even though their brain is getting chewed up with the ravages of Alzheimer's, cognitively, they're doing just fine.

Why? It's because they're challenged all the time. They've got all these new things going on, all this novelty, all these responsibilities, chores, social life, all these things happening. And as a result, they're constantly building new roadways, even as parts degrade. And that's the only good news is that we are in a situation where suddenly we can't just operate like automaton anymore.

We have to think of completely new ways to do things. And that's wonderful. - I don't know why this question popped into my head. It's quite absurd, but are we gonna be okay? - Yeah. - You say this is the promising silver lining, just from your own, 'cause you've written about this and thought about this outside of maybe even the plasticity of the brain, but just this whole pandemic kind of changed the way, it knocked us out of this hamster wheel like that of habit.

A lot of people had to reinvent themselves. Unfortunately, and I have a lot of friends who either are ready or are going to lose their business, is basically it's taking the dreams that people have had and said, like, said this dream, this particular dream you've had will no longer be possible.

So you have to find something new. What are your, are we gonna be okay? - Yeah, we'll be okay in the sense that, I mean, it's gonna be a rough time for many or most people, but in the sense that it is sometimes useful to find that what you thought was your dream was not the thing that you're going to do.

This is obviously the plot in lots of Hollywood movies that someone says, I'm gonna do this, and then that gets foiled and they end up doing something better. But this is true in life. I mean, in general, even though we plan our lives as best we can, it's predicated on our notion of, okay, given everything that's around me, this is what's possible for me next.

But it takes 2020 to knock you off that, where you think, oh, well, actually, maybe there's something I can be doing that's bigger, that's better. - Yeah, you know, for me, one exciting thing, and I just talked to Grant Sanderson. I don't know if you know who he is.

It's the 3Blue1Brown. It's a YouTube channel. He does, he's a, if you see it, you would recognize it. He's like a really famous math guy, and he's a math educator, and he does these incredible, beautiful videos. And now I see sort of at MIT, folks are struggling to try to figure out, you know, if we do teach remotely, how do we do it effectively?

So you have these world-class researchers and professors trying to figure out how to put content online that teaches people. And to me, a possible future of that is, you know, Nobel Prize-winning faculty become YouTubers. Like that, that to me is so exciting. Like what Grant said, which is like the possibility of creating canonical videos on the thing you're a world expert in.

You know, there's so many topics that just, the world doesn't, you know, there's faculty. I mentioned Russ Tedrick. There's all these people in robotics that are experts in a particular beautiful field on which there's only just papers. There's no popular book. There's no clean canonical video showing the beauty of a subject.

And one possibility is they try to create that and share it with the world. - This is the beautiful thing. This, of course, has been happening for a while already. I mean, for example, when I go and I give book talks, often what'll happen is some 13-year-old will come up to me afterwards and say something and I'll say, "My God, that was so smart.

"Like, how did you know that?" And they'll say, "Oh, I saw it on a TED Talk." Well, what an amazing opportunity. Here you got the best person in the world on subject X giving a 15-minute talk as beautifully as he or she can. And the 13-year-old just grows up with that.

That's just the mother's milk, right? As opposed to when we grew up, you know, I had whatever homeroom teacher I had and, you know, whatever classmates I had. And hopefully that person knew what he or she was teaching and often didn't and, you know, just made things up. So the opportunity now has become extraordinary to get the best of the world.

And the reason this matters, of course, is because obviously, back to plasticity, the way our brain gets molded is by absorbing everything from the world, all of the knowledge and the data and so on that it can get, and then springboarding off of that. And we're in a very lucky time now because we grew up with a lot of just-in-case learning.

So, you know, just in case you ever need to know these dates in Mongolian history, here they are. But what kids are growing up with now, like my kids, is tons of just-in-time learning. So as soon as they're curious about something, they ask Alexa, they ask Google Home, they get the answer right there in the context of their curiosity.

The reason this matters is because for plasticity to happen, you need to care. You need to be curious about something. And this is something, by the way, that the ancient Romans had noted. They had outlined seven different levels of learning, and the highest level is when you're curious about a topic.

But anyway, so kids now are getting tons of just-in-time learning, and as a result, they're gonna be so much smarter than we are. And we can already see that. I mean, my boy is eight years old, my girl is five. But I mean, the things that he knows are amazing because it's not just him having to do the rote memorization stuff that we did.

- Yeah, it's just fascinating what the brain, what young brains look like now 'cause of all those TED Talks just loaded in there. - Yes. - And there's also, I mean, a lot of people write kind of, there's a sense that our attention span is growing shorter, but it's complicated because, for example, most people, majority of people, it's the 80-plus percent of people listen to the entirety of these things, two, three hours for it.

Podcasts, long-form podcasts are becoming more and more popular. So it's all really giant, complicated mess. And the point is that the brain is able to adjust to it and somehow form a worldview within this new medium of information that we have. You have these short tweets and you have these three, four-hour podcasts and you have Netflix, movie.

I mean, it's just adjusting to the entirety of things, just absorbing it and taking it all in. And then pops up COVID that forces us all to be home and it all just adjusts and figures it out. - Yeah, yeah, exactly. - It's fascinating. Been talking about the brain as if it's something separate from the human that carries it a little bit.

Like whenever you talk about the brain, it's easy to forget that that's us. Like how much is the whole thing predetermined? Like how much is it already encoded in there? And how much is it the-- - What's the it? - What's the it? The actions, the decisions, the judgments, the-- - You mean like who you are?

- Who you are. - Oh, yeah, yeah, okay, great question. Right, so there used to be a big debate about nature versus nurture. And we now know that it's always both. You can't even separate them because you come to the table with a certain amount of nature, for example, your whole genome and so on.

The experiences you have in the womb, like whether your mother is smoking or drinking, things like that, whether she's stressed, so on, those all influence how you're gonna pop out of the womb. From there, everything is an interaction between all of your experiences and the nature. What I mean is, I think of it like a space-time cone where you have, you drop into the world, and depending on the experiences that you have, you might go off in this direction, or that direction, or that direction, because there's interaction all the way, your experiences determine what happens with the expression of your genes.

So some genes get repressed, some get expressed, and so on. And you actually become a different person based on your experiences. There's a whole field called epigenomics, which is, or epigenetics, I should say, which is about the epigenome, and that is the layer that sits on top of the DNA and causes the genes to express differently.

That is directly related to the experiences that you have. So if, just as an example, they take rat pups, and one group is placed away from their parents, and the other group is groomed, and licked, and taken good care of, that changes their gene expression for the rest of their life.

They go off in different directions in this space-time cone. So yeah, this is, of course, why it matters that we take care of children and pour money into things like education, and good childcare, and so on, for children broadly, because these formative years matter so much. - So is there a free will?

- This is a great question. - I apologize for the absurd high-level philosophical questions. - No, no, these are my favorite kind of questions. Here's the thing, here's the thing. We don't know, if you ask most neuroscientists, they'll say that we can't really think of how you would get free will in there, because as far as we can tell, it's a machine.

It's a very complicated machine. Enormously sophisticated, 86 billion neurons, about the same number of glial cells. Each of these things is as complicated as the city of San Francisco. Each neuron in your head has the entire human genome in it. It's expressing millions of gene products. These are incredibly complicated biochemical cascades.

Each one is connected to 10,000 of its neighbors, which means you have, you know, like half a quadrillion connections in the brain. So it's incredibly complicated, but it is fundamentally appears to just be a machine. And therefore, if there's nothing in it that's not being driven by something else, then it seems it's hard to understand where free will would come from.

So that's the camp that pretty much all of us fall into, but I will say our science is still quite young. And you know, I'm a fan of the history of science. And the thing that always strikes me as interesting is when you look back at any moment in science, everybody believes something is true, and they just, they simply didn't know about, you know, what Einstein revealed or whatever.

And so who knows? - And they all feel like that we've, at any moment in history, they all feel like we've converged to the final answer. - Exactly, exactly. Like all the pieces of the puzzle are there. And I think that's a funny illusion that's worth getting rid of.

And in fact, this is what drives good science is recognizing that we don't have most of the puzzle pieces. So as far as the free will question goes, I don't know. At the moment, it seems, wow, it would be really impossible to figure out how something else could fit in there.

But you know, a hundred years from now, our textbooks might be very different than they are now. - I mean, could I ask you to speculate where do you think free will could be squeezed into there? Like what's that even, is it possible that our brain just creates kinds of illusions that are useful for us?

Or like where could it possibly be squeezed in? - Well, let me give a speculation answer to your very nice question, but you know, and the listeners to this podcast, don't quote me on this. - It's not a quote. - Yeah, exactly, I'm not saying this is what I believe to be true, but let me just give an example.

I give this at the end of my book, "Incognito." So the whole book of "Incognito" is about, you know, all the what's happening in the brain. And essentially I'm saying, look, here's all the reasons to think that free will probably does not exist. But at the very end, I say, look, imagine that you are, you know, imagine that you're a Kalahari Bushman and you find a radio in the sand and you've never seen anything like this.

And you look at this radio and you realize that when you turn this knob, you hear voices coming from, there are voices coming from it. So being a, you know, a radio materialist, you try to figure out like, how does this thing operate? So you take off the back cover and you realize there's all these wires.

And when you take out some wires, the voices get garbled or stop or whatever. And so what you end up developing is a whole theory about how this connection, this pattern of wires gives rise to voices. But it would never strike you that in distant cities, there's a radio tower and there's invisible stuff beaming.

And that's actually the origin of the voices. And this is just necessary for it. So I mentioned this just as a speculation. Say, look, how would we know, what we know about the brain for absolutely certain is that when you damage pieces and parts of it, things get jumbled up.

But how would you know if there's something else going on that we can't see, like electromagnetic radiation, that is what's actually generating this? - Yeah, you paint a beautiful example of how totally, because we don't know most of how, because we don't know most of how our universe works, how totally off base we might be with our science.

Until, I mean, yeah, I mean, that's inspiring. That's beautiful. It's kind of terrifying. It's humbling. It's all of the above. - And the important part just to recognize is that of course we're in the position of having massive unknowns. And we have, of course, the known unknowns. And that's all the things we're pursuing in our labs, trying to figure out, but there's this whole space of unknown unknowns that we haven't even realized we haven't asked yet.

- Let me kind of ask a weird, maybe a difficult question. Part of it has to do with, I've been recently reading a lot about World War II. I'm currently reading a book I recommend for people, which is, as a Jew, it's been difficult to read, but The Rise and Fall of the Third Reich.

So let me just ask about like the nature of genius, the nature of evil. If we look at somebody like Einstein, we look at Hitler, Stalin, modern day Jeffrey Epstein, just folks who through their life have done, with Einstein, done works of genius, and with the others I mentioned, have done evil on this world.

What do we think about that in a live wired brain? Like how do we think about these extreme people? - Here's what I'd say. This is a very big and difficult question, but what I would say briefly on it is, first of all, I saw a cover of Time Magazine some years ago, and it was a big sagittal slice of the brain, and it said something like, "What makes us good and evil?" And there was a little spot pointing to it, there was a picture of Gandhi, and there was a little spot that was pointing to Hitler.

And these Time Magazine covers always make me mad because it's so goofy to think that we're gonna find some spot in the brain or something. Instead, the interesting part is, because we're live wired, we are all about the world and the culture around us. So somebody like Adolf Hitler got all this positive feedback about what was going on, and the crazier and crazier the ideas he had, he's like, "Let's set up death camps "and murder a bunch of people," and so on.

Somehow he was getting positive feedback from that, and all these other people, they all spun each other up. And you look at anything like, I mean, look at the cultural revolution in China or the Russian Revolution or things like this, where you look at these and you think, my God, how do people all behave like this?

But it's easy to see groups of people spinning themselves up in particular ways, where they all say, "Well, would I have thought "this was right in a different circumstance? "I don't know, but Fred thinks it's right, "and Steve thinks it's right. "Everyone around me seems to think it's right." And so part of the maybe downside of having a live wired brain is that you can get crowds of people doing things as a group.

So it's interesting to, we would pinpoint Hitler as saying, "That's the evil guy," but in a sense, I think it was Tolstoy who said, "The king becomes slave to the people." In other words, Hitler was just a representation of whatever was going on with that huge crowd that he was surrounded with.

So I only bring that up to say that it's very difficult to say what it is about this person's brain or that person's brain. He obviously got feedback for what he was doing. The other thing, by the way, about what we often think of as being evil in society is my lab recently published some work on in-groups and out-groups, which is a very important part of this puzzle.

So it turns out that we are very engineered to care about in-groups versus out-groups, and this seems to be a really fundamental thing. So we did this experiment in my lab where we brought people in, we stick them in the scanner, and I don't know, and stop me if you know this, but we show them on the screen six hands, and the computer boop, boop, boop, boop, goes around, randomly picks a hand, and then you see that hand gets stabbed with a syringe needle.

So you actually see a syringe needle enter the hand and come out, and it's really, what that does is that triggers parts of the pain matrix, this area in your brain that involved in feeling physical pain. Now, the interesting thing is it's not your hand that was stabbed. So what you're seeing is empathy.

This is you seeing someone else's hand get stabbed, and you feel like, oh God, this is awful, right? Okay. We contrast that, by the way, with somebody's hand getting poked with a Q-tip, which looks visually the same, but you don't have that same level of response. Now what we do is we label each hand with a one-word label, Christian, Jewish, Muslim, atheist, Scientologist, Hindu.

And now, do, do, do, do, the computer goes around, picks a hand, stabs the hand, and the question is, how much does your brain care about all the people in your out-group versus the one label that happens to match you? And it turns out for everybody across all religions, they care much more about their in-group than their out-group, and when I say they care, what I mean is you get a bigger response from their brain.

Everything's the same. It's the same hands. It's just a one-word label. You care much more about your in-group than your out-group. And I wish this weren't true, but this is how humans are. - I wonder how fundamental that is, or if it's the emergent thing about culture. Like, if we lived alone, like, if it's genetically built into the brain, like this longing for tribe.

- So I'll tell you, we addressed that. So here's what we did. There are two, actually, there are two other things we did as part of this study that I think matter for this point. One is, so, okay, so we show that you have a much bigger response. And by the way, this is not a cognitive thing.

This is a very low-level, basic response to seeing pain in somebody, okay. - Great study, by the way. - Thanks, thanks, thanks. What we did next is we next have it where we say, okay, the year is 2025, and these three religions are now in a war against these three religions.

And it's all randomized, right? But what you see is your thing, and you have two allies now against these others. And now it happens over the course of many trials. You see everybody gets stabbed at different times. And the question is, do you care more about your allies? And the answer is yes.

Suddenly, people who a moment ago, you didn't really care when they got stabbed, now, simply with this one word thing that they're now your allies, you care more about them. But then what I wanted to do was look at how ingrained is this or how arbitrary is it? So we brought new participants in, and we said, here's a coin, toss the coin.

If it's heads, you're an Augustinian. If it's tails, you're a Justinian. These are totally made up. Okay, so they toss it, they get whatever. We give them a band that says Augustinian on it, whatever tribe they're in now. And they get in the scanner, and they see a thing on the screen that says, the Augustinians and Justinians are two warring tribes.

Then you see a bunch of hands. Some are labeled Augustinian, some are Justinian. And now, you care more about whichever team you're on than the other team, even though it's totally arbitrary, and you know it's arbitrary 'cause you're the one who tossed the coin. So it's a state that's very easy to find ourselves in.

In other words, just before walking in the door, they'd never even heard of Augustinian versus Justinian, and now their brain is representing it simply because they're told they're on this team. - You know, now I did my own personal study of this. So once you're an Augustinian, that tends to be sticky because I've been a Packers fan, going to be a Packers fan my whole life.

Now, when I'm in Boston with the Patriots, it's been tough going for my life where I brain to switch to the Patriots. (laughing) So once you become, it's interesting, once the tribe is sticky. - Yeah, I bet that's true. That's it, you know. - You know, we never tried that about saying, "Okay, now you're a Justinian, you were an Augustinian." We never saw how sticky it is, but there are studies of this, of monkey troops on some island, and what happens is they look at the way monkeys behave when they're part of this tribe and how they treat members of the other tribe of monkeys.

And then what they do, I've forgotten how they do that exactly, but they end up switching a monkey so he ends up in the other troop. And very quickly, they end up becoming a part of that other troop and hating and behaving badly towards their original troop. - These are fascinating studies, by the way.

- Yeah. - This is beautiful. In your book, you have a good light bulb joke. "How many psychiatrists does it take to change a light bulb? "Only one, but the light bulb has to want to change." Sorry. (laughing) I'm a sucker for a good light bulb joke. - Okay, so given, I've been interested in psychiatry my whole life, just maybe tangentially.

I've kind of early on dreamed to be a psychiatrist until I understood what it entails. But is there hope for psychiatry, for somebody else to help this live-wired brain to adjust? - Oh yeah, I mean, in the sense that, and this has to do with this issue about us being trapped on our own planet.

Forget psychiatrists, just think of like when you're talking with a friend and you say, "Oh, I'm so upset about this." And your friend says, "Hey, just look at it this way." All we have access to under normal circumstances is just the way we're seeing something. And so it's super helpful to have friends and communities and psychiatrists and so on to help things change that way.

So that's how psychiatrists sort of helped us. But more importantly, the role that psychiatrists have played is that there's this sort of naive assumption that we all come to the table with, which is that everyone is fundamentally just like us. And when you're a kid, you believe this entirely, but as you get older and you start realizing, okay, there's something called schizophrenia and that's a real thing.

And to be inside that person's head is totally different than what it is to be inside my head, or their psychopathy. And to be inside the psychopath's head, he doesn't care about other people. He doesn't care about hurting other people. He's just doing what he needs to do to get what he needs.

That's a different head. There's a million different things going on, and it is different to be inside those heads. This is where the field of psychiatry comes in. Now, I think it's an interesting question about the degree to which neuroscience is leaking into and taking over psychiatry and what the landscape will look like 50 years from now.

It may be that psychiatry as a profession changes a lot or maybe goes away entirely, and neuroscience will essentially be able to take over some of these functions. But it has been extremely useful to understand the differences between how people behave and why, and what you can tell about what's going on inside their brain, just based on observation of their behavior.

- This might be years ago, but I'm not sure. There's an Atlantic article you've written about moving away from a distinction between neurological disorders, quote-unquote brain problems, and psychiatric disorders or quote-unquote mind problems. So on that topic, how do you think about this gray area? - Yeah, this is exactly the evolution that things are going.

There was psychiatry, and then there were guys and gals in labs poking cells, and so on. Those were the neuroscientists. But yeah, I think these are moving together for exactly the reason you just cited. And where this matters a lot, the Atlantic article that I wrote was called "The Brain on Trial," where this matters a lot is the legal system, because the way we run our legal system now, and this is true everywhere in the world, is someone shows up in front of the judge's bench, or let's say there's five people in front of the judge's bench, and they've all committed the same crime.

What we do, 'cause we feel like, hey, this is fair, is we say, all right, you're gonna get the same sentence. You'll all get three years in prison or whatever it is. But in fact, brains can be so different. This guy's got schizophrenia, this guy's a psychopath, this guy's tweaked out on drugs, and so on and so on, that it actually doesn't make sense to keep doing that.

And what we do in this country more than anywhere in the world is we imagine that incarceration is a one-size-fits-all solution. And you may know we have the, America has the highest incarceration rate in the whole world, in terms of the percentage of our population we put behind bars.

So there's a much more refined thing we can do as neuroscience comes in and changes, and has the opportunity to change the legal system, which is to say, this doesn't let anybody off the hook. It doesn't say, oh, it's not your fault, and so on. But what it does is it changes the equation so it's not about, hey, how blameworthy are you?

But instead is about, hey, what do we do from here? What's the best thing to do from here? So if you take somebody with schizophrenia and you have them break rocks in the hot summer sun in a chain gang, that doesn't help their schizophrenia. That doesn't fix the problem.

If you take somebody with a drug addiction who's in jail for being caught with two ounces of some illegal substance, and you put them in prison, it doesn't actually fix the addiction. It doesn't help anything. Happily, what neuroscience and psychiatry bring to the table is lots of really useful things you can do with schizophrenia, with drug addiction, things like this.

And that's why, so I don't know if you know this, but I run a national nonprofit called the Center for Science and Law. And it's all about this intersection of neuroscience and the legal system. And we're trying to implement changes in every county, in every state. I'll just, without going down that rabbit hole, I'll just say one of the very simplest things to do is to set up specialized court systems where you have a mental health court that has judges and juries with expertise in mental illness.

Because if you go, by the way, to a regular court and the person says, or the defense lawyer says, this person has schizophrenia, most of the jury will say, meh, I call bullshit on that. Why? Because they don't know about schizophrenia. They don't know what it's about. And it turns out people who know about schizophrenia feel very differently as a juror than someone who happens not to know any about schizophrenia.

They think it's an excuse. So you have judges and juries with expertise in mental illness, and they know the rehabilitative strategies that are available. That's one thing. Having a drug court where you have judges and juries with expertise in rehabilitative strategies and what can be done and so on.

A specialized prostitution court and so on. All these different things. By the way, this is very easy for counties to implement this sort of thing. And this is, I think, where this matters to get neuroscience into public policy. - What's the process of injecting expertise into this? - Yeah, I'll tell you exactly what it is.

A county needs to run out of money first. I've seen this happen over and over. So what happens is a county has a completely full jail and they say, you know what? We need to build another jail. And then they realize, God, we don't have any money. We can't afford this.

We've got too many people in jail. And that's when they turn to, God, we need something smarter. And that's when they set up specialized court systems. (laughing) - We all function best when our back is against the wall. - And that's what COVID is good for. It's because we've all had our routines and we are optimized for the things we do.

And suddenly our backs are against the wall, all of us. - Yeah, it's really, I mean, one of the exciting things about COVID. I mean, I'm a big believer in the possibility of what government can do for the people. And when it becomes too big of a bureaucracy, it starts functioning poorly, it starts wasting money.

It's nice to, I mean, COVID reveals that nicely. And lessons to be learned about who gets elected and who goes into government. Hopefully this inspires talented young people to go into government, to revolutionize different aspects of it. Yeah, so that's the positive silver lining of COVID. I mean, I thought it'd be fun to ask you, I don't know if you're paying attention to the machine learning world and GPT-3.

So the GPT-3 is this language model, this neural network that's able to, it has 175 billion parameters. So it's very large in its strength in an unsupervised way on the internet. It just reads a lot of unstructured texts and it's able to generate some pretty impressive things. The human brain compared to that has about a thousand times more synapses.

People get so upset when machine learning people compare the brain. And we know synapses are different. It was very different, very different. - But like, what do you think about GPT-3? - Here's what I think, here's what I think. A few things. What GPT-3 is doing is extremely impressive, but it's very different from what the brain does.

So it's a good impersonator, but just as one example, everybody takes a passage that GPT-3 has written and they say, wow, look at this, and it's pretty good, right? But it's already gone through a filtering process of humans looking at it and saying, okay, well, that's crap, that's crap.

Oh, here's a sentence that's pretty cool. Now here's the thing. Human creativity is about absorbing everything around it and remixing that and coming up with stuff. So in that sense, we're sort of like GPT-3, we're remixing what we've gotten in before. But we also know, we also have very good models of what it is to be another human.

And so, I don't know if you speak French or something, but I'm not gonna start speaking in French 'cause then you'll say, wait, what are you doing? I don't understand it. Instead, everything coming out of my mouth is meant for your ears. I know what you'll understand. I know the vocabulary that you know and don't know.

I know what parts you care about. That's a huge part of it. And so, of all the possible sentences I could say, I'm navigating this thin bandwidth so that it's something useful for our conversation. - Yeah, in real time, but also throughout your life. I mean, we're co-evolving together.

We're learning how to communicate together. - Exactly, but this is what GPT-3 does not do. All it's doing is saying, okay, I'm gonna take all these sentences and remix stuff and pop some stuff out. But it doesn't know how to make it so that you, Lex, will feel like, oh yeah, that's exactly what I needed to hear.

That's the next sentence that I needed to know about for something. - Well, of course, it could be all the impressive results. We'll see. The question is, if you raise the number of parameters, whether it's going to be after some-- - It will not be. It will not be.

Raising more parameters won't, here's the thing. It's not that I don't think neural networks can't be like the human brain, 'cause I suspect they will be at some point 50 years, you know, who knows? But what we are missing in artificial neural networks is we've got this basic structure where you've got units and you've got synapses and they're connected.

And that's great. And it's done incredibly mind-blowing, impressive things, but it's not doing the same algorithms as the human brain. So when I look at my children as little kids, you know, as infants, they can do things that no GPT-3 can do. They can navigate a complex room. They can navigate social conversation with an adult.

They can lie. They can do a million things. They are active thinkers in our world and doing things. And this, of course, I mean, look, we totally agree on how incredibly awesome artificial neural networks are right now, but we also know the things that they can't do well, like, you know, like be generally intelligent, do all these different things.

- Reason about the world, efficiently learn, efficiently adapt. - Exactly. - But it's still the rate of improvement. It's, to me, it's possible that we'll be surprised. - I agree. It's possible we'll be surprised. But what I would assert, and I'm glad I'm getting to say this on your podcast so we can look back at this in two years and 10 years, is that we've got to be much more sophisticated than units and synapses between them.

Let me give you an example, and this is something I talk about in LiveWIRE, is despite the amazing impressiveness, mind-blowing impressiveness, computers don't have some basic things. Artificial neural networks don't have some basic things that we like, caring about relevance, for example. So as humans, we are confronted with tons of data all the time, and we only encode particular things that are relevant to us.

We have this very deep sense of relevance that I mentioned earlier is based on survival at the most basic level, but then all the things about my life and your life, what's relevant to you, that we encode. This is very useful. Computers at the moment don't have that. They don't even have a yen to survive and things like that.

- So we filter out a bunch of the junk we don't need. We're really good at efficiently zooming in on things we need. Again, could be argued, you know, let me put on my Freud hat, maybe it's a, I mean, that's our conscious mind. There's no reason that neural networks aren't doing the same kind of filtration.

I mean, in the sense with GPT-3 is doing, so there's a priming step. It's doing an essential kind of filtration when you ask it to generate tweets from, I don't know, from an Elon Musk or something like that. It's doing a filtration of it's throwing away all the parameters it doesn't need for this task.

And it's figuring out how to do that successfully. And then ultimately it's not doing a very good job right now but it's doing a lot better job than we expected. - But it won't ever do a really good job. And I'll tell you why. I mean, so let's say we say, hey, produce an Elon Musk tweet.

And we see like, oh, wow, it produced these three. That's great. But again, we're not seeing the 3000 that produced that didn't really make any sense. It's because it has no idea what it is like to be a human. And all the things that you might want to say and all the reasons you wouldn't, like when you go to write a tweet, you might write something you think, ah, it's not gonna come off quite right in this modern political climate or whatever.

Like, you know, you change things. So- - And it somehow boils down to fear of mortality and all of these human things at the end of the day, all contained with that tweeting experience. (laughing) - Well, interestingly, the fear of mortality is at the bottom of this, but you've got all these more things like, you know, oh, I want to, just in case the chairman of my department reads this, I want it to come off well there just in case my mom looks at this tweet, I want to make sure she, you know, and so on.

- So those are all the things that humans are able to sort of throw into the calculation. I mean- - What it requires though is having a model of your chairman, having a model of your mother, having a model of, you know, the person you want to go on a date with who might look at your tweet and so on.

All these things are, you're running models of what it is like to be them. So in terms of the structure of the brain, again, this may be going into speculation land, I hope you go along with me. (laughing) Is, okay, so the brain seems to be intelligent and our AI systems aren't very currently.

So where do you think intelligence arises in the brain? Like what is it about the brain? - So if you mean where location wise, it's no single spot. It would be equivalent to asking, I'm looking at New York city, where is the economy? The answer is you can't point to anywhere.

The economy is all about the interaction of all of the pieces and parts of the city. And that's what, you know, intelligence, whatever we mean by that in the brain is interacting from everything going on at once. - In terms of a structure, so we look, humans are much smarter than fish, maybe not dolphins, but dolphins are mammals, right?

- I assert that what we mean by smarter has to do with live wiring. So what we mean when we say, oh, we're smarter, is oh, we can figure out a new thing and figure out a new pathway to get where we need to go. And that's because fish are essentially coming to the table with, you know, okay, here's the hardware, go, swim, mate, eat.

But we have the capacity to say, okay, look, I'm gonna absorb, oh, oh, but you know, I saw someone else do this thing and I read once that you could do this other thing and so on. - So do you think there's, is there something, I know these are mysteries, but like architecturally speaking, what feature of the brain of the live wire aspect of it that is really useful for intelligence?

So like, is it the ability of neurons to reconnect? Like, is there something, is there any lessons about the human brain you think might be inspiring for us to take into the artificial, into the machine learning world? - Yeah, I'm actually just trying to write some up on this now called, you know, if you want to build a robot, start with the stomach.

And what I mean by that, what I mean by that is a robot has to care, it has to have hunger, it has to care about surviving, that kind of thing. Here's an example. So the penultimate chapter of my book, I titled "The Wolf and the Mars Rover." And I just look at this simple comparison of you look at a wolf, it gets its leg caught in a trap.

What does it do? It gnaws its leg off, and then it figures out how to walk on three legs. No problem. Now the Mars Rover, Curiosity, got its front wheel stuck in some Martian soil, and it died. This project that cost billions of dollars died 'cause it's got its wheels.

Wouldn't it be terrific if we could build a robot that chewed off its front wheel and figured out how to operate with a slightly different body plan? That's the kind of thing that we want to be able to build and to get there, what we need, the whole reason the wolf is able to do that is because its motor and somatosensory systems are live wired.

So it says, "Oh, you know what? "Turns out we've got a body plan that's different "than what I thought a few minutes ago, "but I have a yen to survive, "and I care about relevance," which in this case is getting to food, getting back to my pack and so on.

"So I'm just gonna figure out how to operate with this. "Oh, whoops, that didn't work. "Oh, okay, I'm kind of getting it to work." But the Mars Rover doesn't do that. It just says, "Oh, geez, I was pre-programmed "to have four wheels, now I have three, I'm screwed." - Yeah, I don't know if you're familiar with a philosopher named Ernest Becker.

He wrote a book called "The Nile of Death," and there's a few psychologists, Sheldon Solomon, I think I just spoke with him on his podcast, who developed terror management theory, which is, like, Ernest Becker is a philosopher that basically said that fear of mortality is at the core of it.

- Yeah. - And so, I don't know, it sounds compelling as an idea that we're all, I mean, that all of the civilization we've constructed is based on this, but it's-- - I'm familiar with his work. Here's what I think. I think that, yes, fundamentally, this desire to survive is at the core of it, I would agree with that, but how that expresses itself in your life ends up being very different.

The reason you do what you do is, I mean, you could list the hundred reasons why you chose to write your tweet this way and that way, and it really has nothing to do with the survival part. It has to do with trying to impress fellow humans and surprise them and say something.

- Yeah, so many things built on top of each other. - Yeah, exactly. - But it's fascinating to think that in artificial intelligence systems, we wanna be able to somehow engineer this drive for survival, for immortality. I mean, because as humans, we're not just about survival. We're aware of the fact that we're going to die, which is a very kind of, we're aware of, like, most people aren't, by the way.

- Aren't? - Aren't. Confucius said, he said, "Each person has two lives. "The second one begins when you realize "that you have just one." - Yeah. - But most people, it takes a long time for most people to get there. - I mean, you could argue this kind of Freudian thing, which Erzbeker argues is they actually figured it out early on, and the terror they felt was like the reason it's been suppressed, and the reason most people, when I ask them about whether they're afraid of death, they basically say no.

They basically say, like, "I'm afraid I won't get, "like, submit the paper before I die." Like, they kind of see, they see death as a kind of inconvenient deadline for a particular set of, like, a book you're writing. As opposed to, like, what the hell, this thing ends. It's like, at any moment, like, most people, as I've encountered, do not meditate on the idea that, like, right now you could die.

Like, right now. In the next five minutes, it could be all over. And, you know, meditate on that idea. I think that somehow brings you closer to, like, the core of the motivations, and the core of the human cognition. - I think it might be the core, but like I said, it is not what drives us day to day.

Yeah, there's so many things on top of it. But it is interesting. I mean, as the ancient poet said, "Death whispers at my ear, live, for I come." So it is certainly motivating when we think about that. Okay, I've got some deadline. I don't know exactly what it is, but I better make stuff happen.

It is motivating, but I don't think, I mean, I know for, just speaking for me personally, that's not what motivates me day to day. It's instead, oh, I want to get this, you know, program up and running before this, or I want to make sure my coauthor isn't mad at me because I haven't gotten this in, or I don't want to miss this grant deadline, or, you know, whatever the thing is.

- Yeah, it's too distant in a sense. Nevertheless, it is good to reconnect. But for the AI systems, none of that is there. Like a neural network does not fear its mortality. And that seems to be somehow fundamentally missing the point. - I think that's missing the point, but I wonder, it's an interesting speculation about whether you can build an AI system that is much closer to being a human without the mortality and survival piece, but just the thing of relevance.

Just, I care about this versus that. Right now, if you have a robot roll into the room, it's gonna be frozen, 'cause it doesn't have any reason to go there versus there. It doesn't have any particular set of things about this is how I should navigate my next move because I want something.

- Yeah, the thing about humans is they seem to generate goals. They're like, you said live-wired. I mean, it's very flexible in terms of the goals and creative in terms of the goals we generate when we enter a room. You show up to a party without a goal usually, and then you figure it out along the way.

- Yes, but this goes back to the question about free will, which is when I walk into the party, if you rewound it 10,000 times, would I go and talk to that couple over there versus that person? I might do this exact same thing every time because I've got some goal stack, and I think, okay, well, at this party, I really wanna meet these kind of people, or I feel awkward, or whatever my goals are.

By the way, so there was something that I meant to mention earlier, if you don't mind going back, which is this, when we were talking about BCI. So I don't know if you know this, but what I'm spending 90% of my time doing now is running a company. Do you know about this?

- Yes, I wasn't sure what the company is involved in. - Right, so-- - Can you talk about it? - Yeah, yeah. So when it comes to the future of BCI, you can put stuff into the brain invasively, but my interest has been how you can get data streams into the brain non-invasively.

So I run a company called Neosensory, and what we build is this little wristband. We've built this in many different form factors. - Oh, wow, that's it? - Yeah, this is it. And it's got these vibratory motors in it. So these things, as I'm speaking, for example, it's capturing my voice and running algorithms and then turning that into patterns of vibration here.

So people who are deaf, for example, learn to hear through their skin. So the information is getting up to their brain this way, and they learn how to hear. So it turns out on day one, people are pretty good, better than you'd expect at being able to say, "Oh, that's weird.

"Was that a dog barking? "Was that a baby crying? "Was that a door knock, a doorbell?" People are pretty good at it. But with time, they get better and better, and what it becomes is a new qualia, in other words, a new subjective internal experience. So on day one, they say, "Whoa, what was that?

"Oh, that was the dog barking." But by three months later, they say, "Oh, there's a dog barking somewhere. "Oh, there's the dog." - That's fascinating. - And by the way, that's exactly how you learn how to use your ears. So what you, of course, you don't remember this, but when you were an infant, all you have are, your eardrum vibrating causes spikes to go down, your auditory nerves and impinging your auditory cortex.

Your brain doesn't know what those mean automatically, but what happens is you learn how to hear by looking for correlations. You clap your hands as a baby, you look at your mother's mouth moving, and that correlates with what's going on there. And eventually, your brain says, "All right, I'm just gonna summarize this "as an internal experience, as a conscious experience." And that's exactly what happens here.

The weird part is that you can feed data into the brain, not through the ears, but through any channel that gets there. As long as the information gets there, your brain figures out what to do with it. - That's fascinating. Like expanding the set of sensors, and it could be arbitrarily, could expand arbitrarily, which is fascinating.

- Well, exactly. And by the way, the reason I use this skin, there's all kinds of cool stuff going on in the AR world with glasses and with it. But the fact is your eyes are overtaxed and your ears are overtaxed, and you need to be able to see and hear other stuff.

But you're covered with the skin, which is this incredible computational material with which you can feed information. And we don't use our skin for much of anything nowadays. My joke in the lab is that I say we don't call this the waste for nothing, 'cause originally we built this as the vest, and you're passing in all this information that way.

And what I'm doing here with the deaf community is what's called sensory substitution, where I'm capturing sound and, I'm just replacing the ears with the skin, and that works. One of the things I talk about in LiveWire is sensory expansion. So what if you took something like your visual system, which picks up on a very thin slice of the electromagnetic spectrum, and you could see infrared or ultraviolet.

So we've hooked that up, infrared and ultraviolet detectors, and I can feel what's going on. So just as an example, the first night I built the infrared, one of my engineers built it, the infrared detector, I was walking in the dark between two houses, and suddenly I felt all this infrared radiation.

I was like, where does that come from? And I just followed my wrist, and I found an infrared camera, a night vision camera. But I immediately, oh, there's that thing there. Of course I would have never seen it, but now it's just part of my reality. - That's fascinating.

- Yeah, and then of course, what I'm really interested in is sensory addition. What if you could pick up on stuff that isn't even part of what we normally pick up on like the magnetic field of the earth, or Twitter, or stock market, or things like that. - Or the, I don't know, some weird stuff, like the moods of other people or something like that.

- Sure, now what you need is a way to measure that. So as long as there's a machine that can measure it, it's easy, it's trivial to feed this in here, and it comes to be part of your reality. It's like you have another sensor. - And that kind of thing is without doing, like if you look at Neuralink, I forgot how you put it, but it was eloquent, without getting, cutting into the brain, basically.

- Yeah, exactly, exactly. So this costs, at the moment, $399. - That's not gonna kill you. - Yeah, it's not gonna kill you. You just put it on, and when you're done, you take it off. Yeah, and so, and the name of the company, by the way, is Neosensory for new senses, because the whole idea is-- - Beautiful.

- You can, as I said, you come to the table with certain plug and play devices, and then that's it. Like I can pick up on this little bit of the electromagnetic radiation, I can pick up on this little frequency band for hearing and so on, but I'm stuck there, and there's no reason we have to be stuck there.

We can expand our umwelt by adding new senses, yeah. - What's umwelt? - Oh, I'm sorry, the umwelt is the slice of reality that you pick up on. So each animal has its own-- - Hell of a word. - Umwelt, yeah, exactly. - Nice. - I'm sorry, I forgot to define it before.

It's such an important concept, which is to say, for example, if you are a tick, you pick up on butyric acid, you pick up on odor, and you pick up on temperature, that's it. That's how you construct your reality, is with those two sensors. If you are a blind echolocating bat, you're picking up on air compression waves coming back, you know, echolocation.

If you are the black ghost knifefish, you're picking up on changes in the electrical field around you with electroreception. That's how they swim around and tell there's a rock there and so on. But that's all they pick up on. That's their umwelt. That's the signals they get from the world from which to construct their reality.

And they can be totally different umwelts. - That's fascinating. - And so our human umwelt is, you know, we've got little bits that we can pick up on. One of the things I like to do with my students is talk about, imagine that you are a bloodhound dog, right?

You are a bloodhound dog with a huge snout with 200 million scent receptors in it, and your whole world is about smelling. You've got slits in your nostrils, like big nosefuls of air and so on. Do you have a dog? - Nope, used to. - Used to, okay, right.

So you know, you walk your dog around and your dog is smelling everything. The whole world is full of signals that you do not pick up on. And so imagine if you were that dog and you looked at your human master and thought, my God, what is it like to have the pitiful little nose of a human?

How could you not know that there's a cat 100 yards away or that your friend was here six hours ago? And so the idea is because we're stuck in our umwelt, because we have this little pitiful nose, is we think, okay, well, yeah, we're seeing reality, but you can have very different sorts of realities depending on the peripheral plug and play devices you're equipped with.

- It's fascinating to think that like, if we're being honest, probably our umwelt is, you know, some infinitely tiny percent of the possibilities of how you can sense quote unquote reality. Even if you could, I mean, there's a guy named Donald Hoffman, yeah, who basically says we're really far away from reality in terms of our ability to sense anything.

Like we're very, we're almost like we're floating out there that's almost like completely detached from the actual physical reality. It's fascinating that we can have extra senses that could help us get a little bit closer. - Exactly, and by the way, this has been the fruits of science is realizing, like, for example, you know, you open your eyes and there's the world around you, right?

But of course, depending on how you calculate it, it's less than a 10 trillionth of the electromagnetic spectrum that we call visible light. The reason I say it depends is because, you know, it's actually infinite in all directions presumably. - Yeah, and so that's exactly that. And then science allows you to actually look into the rest of it.

- Exactly, so understanding how big the world is out there. - And the same with the world of really small and the world of really large. - Exactly. - That's beyond our ability to sense. - Exactly, and so the reason I think this kind of thing matters is because we now have an opportunity for the first time in human history to say, okay, well, I'm just gonna include other things in my OOM-VEL, so I'm gonna include infrared radiation and have a direct perceptual experience of that.

And so I'm very, you know, I mean, so, you know, I've given up my lab and I run this company 90% of my time now. That's what I'm doing. I still teach at Stanford and I'm, you know, teaching courses and stuff like that, but-- - This is like, this is your passion.

The fire is on this. - Yeah, I feel like this is the most important thing that's happening right now. I mean, obviously I think that 'cause that's what I'm devoting my time and my life to, but-- - I mean, it's a brilliant set of ideas. It certainly is like, it's a step in a very vibrant future, I would say.

Like, the possibilities there are endless. - Exactly, so if you ask what I think about Neuralink, I think it's amazing what those guys are doing and working on, but I think it's not practical for almost everybody. For example, for people who are deaf, they buy this and, you know, every day we're getting tons of emails and tweets and whatever from people saying, "Wow, I picked up on this." And then I had no idea that was a, I didn't even know that was happening out there.

And they're coming to hear. By the way, this is, you know, less than a 10th of the price of a hearing aid and like 250 times less than a cochlear implant. - That's amazing. People love hearing about what, you know, brilliant folks like yourself could recommend in terms of books.

Of course, you're an author of many books. So I'll, in the introduction, mention all the books you've written. People should definitely read "Livewired." I've gotten a chance to read some of it. It's amazing. But is there three books, technical, fiction, philosophical, that had an impact on you when you were younger or today and books, perhaps some of which you would want to recommend that others read?

- You know, as an undergraduate, I majored in British and American literature. That was my major, 'cause I love literature. I grew up with literature. My father had these extensive bookshelves. And so I grew up in the mountains in New Mexico. And so that was mostly where I spent my time was reading books.

But, you know, I love, you know, Faulkner, Hemingway. I love many South American authors, Gabriel Garcia Marquez and Italo Calvino. I would actually recommend "Invisible Cities." I just, I loved that book. - By? - Italo Calvino, sorry. It's a book of fiction. Anthony Doar wrote a book called "All the Light We Cannot See," which actually was inspired by incognito by exactly what we were talking about earlier about how you can only see a little bit of the, what we call visible light in the electromagnetic radiation.

I wrote about this in incognito and then he reviewed incognito for the Washington Post. - Oh, no, that's awesome. - And then he wrote this book. The book has nothing to do with that, but that's where the title comes from. - Yeah. - "All the Light We Cannot See" is about the rest of the spectrum.

But that's an absolutely gorgeous book. - That's a book of fiction. - Yeah, it's a book of fiction. One that people are surprised. - What's it about? - It takes place during World War II about these two young people, one of whom is blind. - Anything else? So what I need, so you mentioned Hemingway.

- I mean. - "Old Man and the Sea." What's your favorite? - "Snow's the Kill of Ninjaro." - Oh, wow, okay. - It's a collection of short stories that I love. As far as nonfiction goes, I grew up with "Cosmos," both watching the PBS series and then reading the book, and that influenced me a huge amount in terms of what I do.

From the time I was a kid, I felt like I wanna be Carl Sagan. That's what I loved. And in the end, I studied space physics for a while as an undergrad, but then I, in my last semester, discovered neuroscience last semester, and I just thought, wow, I'm hooked on that.

- So the Carl Sagan of the brain. - That was my aspiration. - Is the aspiration. I mean, you're doing an incredible job of it. So you open the book "Livewired" with a quote by Heidegger. "Every man is born as many men and dies as a single one." Well, what do you mean?

- I'll tell you what I meant by it. So he had his own reason why he was writing that, but I meant this in terms of brain plasticity, in terms of "Livewired," which is this issue that I mentioned before about this cone, the space-time cone that we are in, which is that when you dropped into the world, you, Lex, had all this different potential.

You could have been a great surfer or a great chess player, or you could have been thousands of different men when you grew up, but what you did is, things that were not your choice and your choice along the way, you ended up navigating a particular path, and now you're exactly who you are.

You still have lots of potential, but the day you die, you will be exactly Lex. You will be that one person. - So in that context, first of all, it's just a beautiful, it's a humbling picture, but it's a beautiful one, 'cause it's all the possible trajectories, and you pick one, you walk down that road, and it's the Robert Frost poem.

But on that topic, let me ask the biggest and the most ridiculous question. So in this "Livewired" brain, when we choose all these different trajectories and end up with one, what's the meaning of it all? What's, is there a why here? What's the meaning of life, David Engelman? - That's it.

(laughing) I mean, this is the question that everyone has attacked from their own "Livewired" point of view, by which I mean, culturally, if you grew up in a religious society, you have one way of attacking that question. So if you grew up in a secular or scientific society, you have a different way of attacking that question.

Obviously, I don't know. I abstain on that question. (laughing) - I mean, I think one of the fundamental things, I guess, in that, in all those possible trajectories, is you're always asking. I mean, that's the act of asking, what the heck is this thing for, is equivalent to, or at least runs in parallel to all the choices that you're making.

'Cause it's kinda, that's the underlying question. - Well, that's right. And by the way, you know, this is the interesting thing about human psychology. You know, we've got all these layers of things at which we can ask questions. And so if you keep asking yourself the question about, what is the optimal way for me to be spending my time?

What should I be doing? What charity should I get involved with? If you're asking those big questions, that steers you appropriately. If you're the type of person who never asks, "Hey, is there something better "I could be doing with my time?" Then presumably you won't optimize whatever it is that is important to you.

- So you've, I think, just in your eyes, in your work, there's a passion that just is obvious and it's inspiring, it's contagious. If you were to give advice to a young person today in the crazy chaos that we live today, about life, about how to discover their passion, is there some words that you could give?

- First of all, I would say the main thing for a young person is stay adaptable. And this is back to this issue of why COVID is useful for us because it forces us off our tracks. The fact is the jobs that will exist 20 years from now, we don't even have names for, we can't even imagine the jobs that are gonna exist.

And so when young people that I know go into college and they say, "Hey, what should I major in?" And so on, college is and should be less and less vocational as in, "Oh, I'm gonna learn how to do this and then I'm gonna do that the rest of my career." The world just isn't that way anymore with the exponential speed of things.

So the important thing is learning how to learn, learning how to be live wired and adaptable. That's really key. And what I tell, what I advise young people, what I talk to them is, you know, what you digest, that's what gives you the raw storehouse of things that you can remix and be creative with.

And so eat broadly and widely. And obviously this is the wonderful thing about the internet world we live in now is you kind of can't help it. You're constantly, whoa, you go down some mole hole of Wikipedia and you think, oh, I didn't even realize that was a thing.

I didn't know that existed. And so- - Embrace that. - Embrace that, yeah, exactly. And what I tell people is just always do a gut check about, okay, I'm reading this paper and yeah, I think that, but this paper, wow, that really, I really cared about that in some way.

I tell them just to keep a real sniff out for that. And when you find those things, keep going down those paths. - Yeah, don't be afraid. I mean, that's one of the challenges and the downsides of having so many beautiful options is that sometimes people are a little bit afraid to really commit, but that's very true.

If there's something that just sparks your interest and passion, just run with it. I mean, it goes back to the Heiderer quote. I mean, we only get this one life and that trajectory, it doesn't last forever. So just if something sparks your imagination, your passion is run with it.

- Yeah, exactly. - I don't think there's a more beautiful way to end it. David, it's a huge honor to finally meet you. Your work is inspiring so many people. I've talked to so many people who are passionate about neuroscience, about the brain, even outside that read your book.

So I hope you keep doing so. I think you're already there with Carl Sagan. I hope you continue growing. Yeah, it was an honor talking with you today. Thanks so much. - Great, you too, Lex, wonderful. - Thanks for listening to this conversation with David Eagleman, and thank you to our sponsors, Athletic Greens, BetterHelp, and Cash App.

Click the sponsor links in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow us on Spotify, support on Patreon, or connect with me on Twitter @LexFriedman. And now let me leave you with some words from David Eagleman in his book, "Some," for details from the afterlives.

Imagine for a moment that we're nothing but the product of billions of years of molecules coming together and ratcheting up through natural selection. That we're composed only of highways of fluids and chemicals sliding along roadways within billions of dancing cells. That trillions of synaptic connections hum in parallel. That this vast egg-like fabric of micro-thin circuitry runs algorithms undreamt of in modern science.

And that these neural programs give rise to our decision-making, loves, desires, fears, and aspirations. To me, understanding this would be a numinous experience, better than anything ever proposed in any holy text. Thank you for listening, and hope to see you next time. (upbeat music) (upbeat music) Thanks for watching.