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David Eagleman: Neuroplasticity and the Livewired Brain | Lex Fridman Podcast #119

David Eagleman is a neuroscientist at Stanford. Support this podcast by supporting our sponsors: - Athletic Greens: https://athleticgreens.com/lex - BetterHelp: https://betterhelp.com/lex - Cash App: download app & use code "LexPodcast" EPISODE LINKS: David's Website: https://www.eagleman.com/ David's Twitter: https://twitter.com/davideagleman Livewired (book): https://amzn.to/3ba4ezv Incognito (book): https://amzn.to/3lkNASh PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 - Introduction 5:05 - Livewired 16:39 - Hardware vs software 25:53 - Brain-computer interfaces 35:12 - 2020 is a challenge for neuroplasticity 46:08 - Free will 50:43 - Nature of evil 58:55 - Psychiatry 1:06:28 - GPT-3 1:13:31 - Intelligence in the brain 1:21:51 - Neosensory 1:31:27 - Book recommendations 1:34:07 - Meaning of life 1:36:53 - Advice for young people CONNECT: - Subscribe to this YouTube channel - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/LexFridmanPage - Instagram: https://www.instagram.com/lexfridman - Medium: https://medium.com/@lexfridman - Support on Patreon: https://www.patreon.com/lexfridman

Lex FridmanhostDavid Eaglemanguest
Aug 26, 20201h 41mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:005:05

    Introduction

    1. LF

      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. A 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. If you enjoy this thing, subscribe on YouTube, review it with five stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter @LexFridman. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I give you timestamps so you can skip. But please do check out the sponsors by clicking the links in the description. It's the best way to support this podcast. This show is brought to you by Athletic Greens, the all-in-one daily drink to support better health and peak performance. Even with a balanced diet, it's difficult to cover all of your nutritional bases. That's where Athletic Greens will help. Their daily drink is like nutritional insurance for your body that's delivered straight to your door. As you may know, I fast often, sometimes intermittent fasting for 16 hours, sometimes 24 hours, dinner to dinner, sometimes more. I break the fast with Athletic Greens. It's delicious, refreshing, just makes me feel good. I think it's like 50 calories, less than a gram of sugar, but has a ton of nutrients to make sure my body has what it needs despite what I'm eating. Go to, uh, athleticgreens.com/lex to claim a special offer of a free vitamin D3K2 for a year. If you listen to The Joe Rogan Experience, you might have listened to him rant about how awesome vitamin D is for your immune system. So there you have it. So click the athleticgreens.com/lex in the description to get the free stuff and to support this podcast. This show is sponsored by BetterHelp, spelled H-E-L-P, help. Check it out at betterhelp.com/lex. They figure out what you need and match you with a licensed professional therapist in under 48 hours. It's not a crisis line. It's not self-help. It's professional counseling done securely online. I'm a bit from the David Goggins line of creatures, and so have some demons to contend with, usually on long runs or all nights full of self-doubt. I think suffering is essential for creation, but you can suffer beautifully in a way that doesn't destroy you. For most people, I think a good therapist can help in this. So it's at least worth a try. Check out their reviews. They're good. It's easy, private, affordable, available worldwide. You can communicate by text any time and schedule a weekly audio and video session. Check it out at betterhelp.com/lex. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, invest in the stock market with as little as one dollar. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend A Cent Of Money as a great book on this history. Debits and credits on ledgers started around 30,000 years ago, and the first decentralized cryptocurrency released just over 10 years ago. So given that history, cryptocurrency still very much in its early days of development, but it's still aiming to and just might redefine the nature of money. So again, if you get Cash App from the App Store or Google Play and use code LEXPODCAST, you get ten dollars. And Cash App will also donate ten dollars to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now here's my conversation with David Eagleman.

  2. 5:0516:39

    Livewired

    1. LF

      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.

    2. DE

      Yeah. 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. It's, um... So I coined this new term liveware, which is a system that's constantly reconfiguring itself physically as it, uh, as it learns and adapts to the world around it. It's physically changing.

    3. LF

      So it's, uh, liveware, meaning like as, uh, like hardware but changing?

    4. DE

      Yeah, exactly. Well, it's, uh, the hardware and the software layers are blended. And so, um, you know, typically engineers are praised for their efficiency in making something really clean and clear. Like, "Okay, here's the hardware layer. Then I can 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, uh, all our devices a particular way, but, you know, I can't tear half the circuitry out of your cell phone and expect it to still function. But you can do that with, uh, 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, and, and they're fine. They have a slight limp on the other side of their body, but, um, they can function just fine that way and, uh, and this is generally true. You know, sometimes children are born without a hemisphere and their visual system rewires so that everything is on the, 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.

    5. LF

      How much of that is a, is a quirk or a feature of evolution? Like, how, how hard is it to engineer? 'Cause evolution took a lot of work.

    6. DE

      Exactly.

    7. LF

      Bil- trillions of organisms had to die for, to create this thing we have, uh, in our skull. Uh, like, 'cause you said, uh, you kind of look forward to the idea that, uh, 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?

    8. DE

      Great question, and it's 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, um, we, all we have to do now is peek at the, at the blueprints. It's just three pounds, this organ, and, and we just figure out how to do it. But that's the part that I mean is a difficult challenge, because, you know, uh, there are tens of thousands of neuroscientists who are 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, you know, 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, you know, it takes Crick and Watson to say, "Oh, you know, 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, 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.

    9. LF

      But, but to even just linger, you said, uh, it's possible to be born with just one hemisphere and you still are able to function. First of all, just, just to pause on that, I mean, that's kind of, that's amazing. That's, that's, uh, I don't know if people quite... I mean, you kind of hear things here and there, this is why I'm, I kinda, I'm really excited about your book, is I don't know if there's definitive sort of popular sources to, to think about this stuff. I mean, there's a lot of, I think from my perspective, what I heard is there's, like, been debates over decades about how, 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 are understanding there's more more neuro- m- much more plastic than people realize. But just, like, linger on that, uh, topic, like, how malleable is the hardware of the human brain? Maybe you said children at each stage of life.

    10. DE

      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, um, part of my goal here was to pull together the tens of thousands of papers on this, both from clinical work and from, you know, 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, maybe I should just define plasticity.

    11. LF

      Yeah.

    12. DE

      You know, it's the ability of a system to, to mold into a new shape and then hold that shape. That's why, you know, we make things that we call plastic, um, because they are moldable and they can hold that new shape, like a plastic toy or something.

    13. LF

      And so may- maybe we use, maybe we'll use a lot of terms that are synonymous. So, uh, uh, something is plastic, something is malleable, uh, changing, livewire, the name of the book, is, is like sy-

    14. DE

      S- so I'll tell, exactly right, but I'll tell you why I chose live wired instead of plasticity. So I used the term plasticity in the book, but, um, but sparingly, because that was a term coined by William James over 100 years ago and, 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, you know, few minutes of conversation that we've been having, your brain is changing. My brain is changing. Um, next time I see your face, I will remember, "Oh, yeah, like that time Lex and I sat together and we did these things," and-

    15. LF

      I wonder if your brain will have, like, a Lex thing going on for the next few months. Like, it'll stay there until you get rid of it.

    16. DE

      But, but I'll probab-

    17. LF

      'Cause it was useful for now (laughs) .

    18. DE

      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.

    19. LF

      Yeah.

    20. DE

      When I run into you, I'll be like, "Oh, yeah."

    21. LF

      You'll be like, "Huh, that looks familiar."

    22. DE

      Yeah, yeah.

    23. LF

      (laughs)

    24. DE

      And we, yeah, we sat down for a podcast-

    25. LF

      Yeah.

    26. DE

      ... back when there were podcasts.

    27. LF

      (laughs) Yeah, right.

    28. DE

      Yeah, exactly.

    29. LF

      Back when we lived outside virtual reality.

    30. DE

      (laughs)

  3. 16:3925:53

    Hardware vs software

    1. DE

      blanks?

    2. LF

      How much of the malleability is hardware, how much is software? Is that useful at all in the brain? So like what are, what, what are we talking about? So there's like, there's neurons, there's, uh, uh, synapses and the all kinds of different synapses and there's chemical communication like electrical signals and there's chemical communication from this in the synapses. Uh, 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?

    3. DE

      So here's the thing. This is why really if we can I want to 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, uh, computer engineers are really used to thinking about is, is synapses where two neurons connect. Of course each neuron connects with 10,000 of its neighbors, but at a point where they connect, um, what we're all used to thinking about is the changing of the strength of that connection, the synaptic weight. Um, 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, 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 the, um, you know, these little proteins that are attached to the DNA that cause conformational changes that cause more genes to be ex- uh, expressed or, 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.

    4. LF

      Mm-hmm.

    5. DE

      But, but in fact the system is plastic at all these different levels and, and my, my way of thinking about this is...... an analogy to pace layers. So pace layers is a concept that Stewart Brand, um, suggested about how to think about cities. So you have fashion, which changes rapidly in cities. You have, um, um, governance, which changes more slowly. You have the structure, the buildings of a city, which changes more slowly. All the way down to, 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, and mapped it onto the brain, which is to say you have some biochemical cascades that are just changing really rapidly when something happens-

    6. LF

      Mm-hmm.

    7. DE

      ... all the way down to things that are more and more cemented in there. And this is actually, uh, 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 Ribot'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, your young life, maybe you'll remember this podcast, but you won't remember what you did a month ago or a year ago.

    8. LF

      Mm-hmm.

    9. DE

      And this is a very weird structure, right? N- no other system works this way, where older memories are more stable than, than newer memories. Um, but it's because through time, things get more and more cemented into deeper layers of the system. And, um, 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."

    10. LF

      So yeah. So the idea of liveware and live-wired is that, is that, it's a, it's like a, it's a gradual, uh, it's a gradual spectrum between software and hardware. And so the metaphor's 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, um, un- unlike hardw- but even hardware... But like, so there's two groups, but in the software world there's levels of abstractions, right? There's the, 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, it's hard to know what to, uh, think about that. Like if I were to ask the question, uh, this is an important question for machine learning is, um, 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.

    11. DE

      E- exactly right. And as a result, what happens is as you practice something, get good at something, you're physically changing the circuitry. You're, you're, you're adapting your brain around the thing that is relevant to you. So let's say you take up, um, do you know how to surf?

    12. LF

      Nope. (laughs)

    13. DE

      Okay, great. So let's say you take up surfing-

    14. LF

      Yeah.

    15. DE

      ... now at this age. Um, what happens is, you know, you'll be terrible at first 'cause 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?" Um, 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, 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 and so on. So, um, 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, the top thing that's relevant. But interestingly, uh, especially with humans, we have these particular goals in our lives, computer science, neuroscience, whatever, and so we actually shape our circuitry around that.

    16. LF

      I mean, you mentioned this gets slower and slower with age, but is there... Like I've, I think I've, uh, read and spoken offline even on this podcast with a, a developmental neurobiologist, I guess would be the right terminology, is like looking at the very early, like from, from embryonic stem cells to like, to, to the b- to 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. Uh, it's... And then, but after that, wha- at which point does it stop being malleable? (chuckles)

    17. DE

      So, so, 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, you know, figured out how to go in the settings and do the thing, and I was really, yeah, I was really impressed by it that she was able to do it. So there are parts of the brain that remain malleable their whole life. The, the interesting part is that really your goal is to make an internal model of the world. Your goal is to say, "Okay, uh, the brain, uh, is trapped in silence and darkness and it's trying to understand how the world works out there," right?

    18. LF

      (laughs) I love that image. Yeah. I- I guess it is.

    19. DE

      Y- yeah.

    20. LF

      You forget. (laughs) You forget. It's like this, it's... (laughs) This lonely thing is sitting in its own container and, uh, trying to actually, through a few sensors, figure out what the he- what the hell's going on.

    21. DE

      You know what I sometimes think about is, um, the-

    22. LF

      (laughs)

    23. DE

      ... that, that movie The Martian with Matt Damon?

    24. LF

      Mm-hmm.

    25. DE

      The, um... I mean, it was written in a book of course, but the, the, 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're, 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, um, 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, uh, the experience of course might be, might be vastly different for us.Um, 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, as in, "How do I function in the world? W- how do I c- how do I interact with other people? Do I say something nice and polite or 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."

    26. LF

      Mm-hmm.

    27. DE

      Right? So when old, when, when, when much older people find themselves in a situation where they need to change, they can, they actually 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. Um, but-

    28. LF

      I see.

    29. DE

      ... but if you were 80 and you got fired from your job and suddenly had to figure out how to program a WordPress site or something, you'd figure it out.

    30. LF

      Got it. So the, the capability, the possibility of change is, is

  4. 25:5335:12

    Brain-computer interfaces

    1. LF

      there.

    2. DE

      Mm-hmm.

    3. LF

      But then that's the, the highest challenge, the interesting challenge to this, uh, plasticity, to this, uh, live-wire system, uh, if we could talk about brain computer interfaces and Neuralink, uh, what are your thoughts about the efforts of Elon Musk, Neuralink, BCI in general in this regard, which is adding a, a machine, a computer, uh, the capability of a computer to communicate with the brain and the brain to communicate with the computer at the very basic applications, and then, like, the futuristic kind of thoughts?

    4. DE

      Yeah. First of all, it's terrific that people are jumping in and doing that 'cause it's clearly the, the future. The interesting part is, our brains have pretty good methods of interacting with technology. You know, so maybe it's your fat thumbs on a phone or something, but, um, or maybe it's watching a YouTube video and getting in through 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, um, you might be able to get a little bit faster, but I'll tell you, uh, I, I'm, I, 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. Um, 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, you know, 20% faster." So I think it's, you know, Mother Nature surrounds the brain with this armored, you know, bunker of the skull because it's a very delicate material, and there's an expression in neurosurgery, um, uh, how, uh, ab- about the brain is, you know, the person is never the same after you open up their skull. Now, whether or not that's true or whatever-

    5. LF

      Mm-hmm.

    6. DE

      ... 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?

    7. LF

      Got it. Without messing with the biological s- uh, part, like directly, uh, connecting or messing with the, with the intricate biological thing that we got going on that seems to be working.

    8. DE

      Yeah, exactly. And by the way, where Neuralink is going, which is wonderful, is going to be in patient cases. It, 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, uh, 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 this." (laughs)

    9. LF

      (laughs) Well, it's interesting 'cause, uh, I think there's a similar intuition by, 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 just 'cause it's a good, easy example. Uh, similar intuition about colonizing Mars, it, like, if you really think about it, it seems extremely difficult and, uh, and almost, I mean, just technically difficult to the, to a degree where you wanna ask, "Is it really worth doing? Worth trying?" And then the same, the same is applied with BCI, but the thing about the future (laughs) is it's hard to predict. Uh, the, th- so the exciting thing to me with, um, so o- once it does, once, if successful, it's able to help patients, it may be able to discover something, uh, s- very surprising a- about our ability to directly communicate with the brain. So exactly what you're interested in is figuring out how to, uh, play with this malleable brain, uh, with, like, uh, uh, 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, you know, uh, from, from data, and then if we can con- have this other brain that's a learning system that's live wired and when on the human side and it'll then be able to communicate, it's like, uh, a self-play mechanism was able to beat the ga- uh, the, the world champion at Go so they can play with each other, the computer and the brain, uh, like when you sleep. I mean, there's a lot of futuristic kind of things that it's just, um, exciting possibilities, but I, 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.

    10. DE

      Uh, uh, 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 know, you take a, essentially a 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, and it turns out that as-

    11. LF

      (laughs)

    12. DE

      ... as recently as about 25 years ago, a lot of people thought this was never gonna work. They thought it was, it wasn't gonna work for that reason, but the brain figures it out. It's really good at saying, "Okay look-

    13. LF

      Interesting.

    14. DE

      "... 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, you know, I clap my hands and I, and I have signals coming in the air, and it figures out how to speak any language.

    15. LF

      Oh, that's fascinating. So like, uh, no matter your, m- no matter if it's Neurolink, uh, so directly communicating with the brain, or it's a smartphone or Google Glass or, the brain figures out the efficient way of communication.

    16. DE

      Well exactly, exactly. And what I propose is, is the potato head theory of evolution, which is, which is, um, that all, you know, our eyes and nose and mouth and ears and fingertips, all this stuff is just plug and play.

    17. LF

      Mm-hmm.

    18. DE

      And the brain can figure out what to do with the data that comes in. And, 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, um, principles of brain operation each time to say, "Oh, now I'm gonna have heat pits that detect infrared. Now I'm gonna have something to detect, uh, you know, electroreceptors 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 on. 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."

    19. LF

      It's, it's kind of fascinating to think that we think of smartphones and all this new technology as novel, as 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-

    20. DE

      Oh, yeah.

    21. LF

      ... and the internet. Like it's ready. It's ready to be malleable to that and whatever comes, t- to cyborgs to virtual reality. We kind of think like, this is, you know, there's all these, like, books written about natural, what's natural, and we're, like, destroying our natural selves by, like, embracing all this technology. It's kind of, it's, you know, w- not, probably not giving the brain enough credit, like-

    22. DE

      Yeah.

    23. LF

      ... this, this, this thing, (laughs) this thing is just fine with new tech.

    24. DE

      Oh, exactly, it wraps itself around.

    25. LF

      You know?

    26. DE

      And by the way, wait till you have kids. You'll see the ease with which they pick up on stuff and-

    27. LF

      (laughs) Yeah.

    28. DE

      ... as Kevin Kelly said, um, "Technology is what gets invented after you're born."

    29. LF

      (laughs)

    30. DE

      But the stuff that already exists when you're born, that's not even tech, that's just background furniture.

  5. 35:1246:08

    2020 is a challenge for neuroplasticity

    1. DE

    2. LF

      (sighs) Well, that's, uh... Okay, first of all, that paints a really promising and beautiful and for some reason really optimistic picture that, you know, our brain is able to, to adjust to so much.

    3. DE

      Yeah.

    4. LF

      Um, that, you know, so many things happened this year, 2020, that you think like, "How are we ever going to deal with it?" And it- it's somehow encouraging and inspiring that like we're going to be okay.

    5. DE

      Well, that's right. I, 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 w- you know, on our gerbil wheels, we've all been in our routines, and, and, uh, you know, 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, um, there are very large studies on older people who stay cognitively active their whole lives. Some f- 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, they're, 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, and, and that's the only good news is that we are in a situation where suddenly we can't just operate like automata anymore. We have to think of completely new ways to do things, and that's wonderful.

    6. LF

      I don't know wh- why this question popped into my head, it's quite absurd, but, uh, (laughs) are we gonna be okay?

    7. DE

      Yeah. (laughs)

    8. LF

      (laughs) You, you said there's, it's a 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-

    9. DE

      Yeah.

    10. LF

      ... just this, uh, this whole pandemic kinda changed the way... It, it knocked us out of this, uh, hamster wheel (laughs) like that of habit. A lot of people had, had to reinvent themselves. Unfortunately, and I have a lot of friends who e- either already or ha- or are going to lose their business. You know, it's basically, it- it's taking the dreams that people have had and said like, said, "This, this dream, this particular dream you've had will no longer be possible, so you have to find something new." What, what are your (laughs) are we gonna be okay?

    11. DE

      Yeah. We'll be okay in the sense that... I mean, it is 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, was not the thing that you're going to do. Um, 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, um, 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 could be doing that's bigger, that's better."

    12. LF

      Yeah. You know, for me, one exciting thing... And I just talked to, um, Grant Sanderson. I don't know if you know who he is. He's, uh, 3blue1brown. It's a YouTube channel. He does... He's, uh... I- i- if you see it, you will 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 he's 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, um, world-class researchers, uh, 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, uh, faculty become YouTubers.

    13. DE

      (laughs)

    14. LF

      Like, like, that, that to me is so exciting. Uh, like what Grant said, uh, which is, like, the possibility of creating canonical videos on the thing you're a world expert in. Uh, you know, there's so many topics that just, the world doesn't... You know, there's p- there's faculty. I mentioned Russ Tedrake. There's all t- all these people in robotics that are experts in a particular, beautiful field-

    15. DE

      Yeah.

    16. LF

      ... on which there's only just papers. (laughs)

    17. DE

      Yeah.

    18. LF

      There's, there's no popular book. There's no, uh, there's no clean, canonical video showing the beauty of a subject. And one possibility is, uh, they, they try to create that and, uh, and share it with the world.

    19. DE

      This is, this is the beautiful thing. This, of course, has been happening for a while already.

    20. LF

      Right.

    21. DE

      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, how did you know that?"

    22. LF

      Yeah.

    23. DE

      And they'll say, "Oh, I saw it on a TED Talk." Well, what a a- amazing opportunity. Here you got the, the, the, the best person in the world on subject X giving a, a 15-minute talk as, 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?

    24. LF

      Yeah.

    25. DE

      As opposed to when we grew up, you know, I had whatever homeroom teacher I had-

    26. LF

      (laughs)

    27. DE

      ... and, uh, w- you know, whatever classmates I had, and, and hopefully that person knew what, what he or she was teaching and often didn't, and you know, just made things up. So, the, the-

    28. LF

      (laughs)

    29. DE

      ... 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 that we... The way our brain gets molded is by absorbing everything from the world, all of the... all of the knowledge and the data and so on that it can get, and then, um, 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. Um, but what, 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, uh, this is something, by the way, that the ancient Romans had, 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.

    30. LF

      Mm-hmm. (laughs) Yeah.

  6. 46:0850:43

    Free will

    1. DE

    2. LF

      So, is there a free will? (laughs)

    3. DE

      Th- this is, this is a, uh, a great question. It's-

    4. LF

      I apologize for the, (laughs) for the absurd high-level philosophical questions

    5. NA

      Very interesting.

    6. DE

      No, no. These are my favorite kind of questions.

    7. LF

      (laughs)

    8. DE

      Here, here's the thing. Here's the thing.

    9. LF

      Yeah.

    10. DE

      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, 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, it's incredibly complicated thing, 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, I'm a fan of the history of science and wha- eh, 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-

    11. LF

      Mm-hmm.

    12. DE

      ... what Einstein revealed or whatever. And so, who knows? I mean, in a-

    13. LF

      And they, they all feel like that we've, at any moment in s- history, they all feel like we've converged to the final answer.

    14. DE

      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, 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, 100 years from now, our textbooks might be very different than they are now.

    15. LF

      I mean, could I ask you to speculate where do you think free will could be squeezed into there? Like, what's that even... Um, is it, is it, is it possible that our brain just creates kinds of illusions that are useful for us? Or like what... W- where could it possibly be squeezed in? (laughs)

    16. DE

      Well, l- let me, let me give a speculation answer to your very nice question, but, but, you know, don't... And, and the listeners to this podcast-

    17. LF

      We all know.

    18. DE

      Don't quote me on this.

    19. LF

      It's not a quote. (laughs)

    20. DE

      Yeah, exactly. I'm not- 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, um, 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, you look at this radio and, 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, 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.

    21. LF

      Yeah.

    22. DE

      So I mention this just as a speculation.

    23. LF

      Beautiful.

    24. DE

      Say, look, how would we know what we know about the brain for absolutely certain is that if, 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?

    25. LF

      Yeah. You paint a beautiful example of, uh, of how totally, because we don't know most of how our universe works, how totally off base we might be (laughs) with our science.

    26. DE

      Yeah.

    27. LF

      Until, I mean, we, I mean, um, yeah, I mean, that's inspiring, that's beautiful. It's kinda terrifying, it's humbling. It's all, all, all, all of the above. But-

    28. DE

      And the important, and the important part, just to recognize, is that of course we're in the position of having massive unknowns. And you know, w- w- we have, of course, the known unknowns, and that's all the things we're pursuing in our labs and trying to figure out there. But there's this whole space of unknown unknowns, things we haven't even realized we haven't

  7. 50:4358:55

    Nature of evil

    1. DE

      asked yet.

    2. LF

      Let me kinda ask a, a weird, maybe a difficult question.

    3. DE

      Mm-hmm.

    4. LF

      Part of it has to do (laughs) with, I've been, uh, recently reading a lot about World War II. I'm currently reading a book I recommend for people, which is, uh, uh, as a Jew it's been difficult to read, but, uh, The Rise and Fall of the Third Reich.

    5. DE

      Yeah.

    6. LF

      Um, so let me a- just ask about, like the nature of genius, the nature of evil. If we look at somebody like, uh, Einstein. We look at Hitler, Stalin, modern day Jeffrey Epstein, just, um, 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, how do we think about these extreme people?

    7. DE

      He- he- here's, here's what I'd say. And this is a very big and difficult question, but what I would say briefly on it is, um, you know, first of all, I saw a cover of Time Magazine some years ago, uh, and it was a big, you know, sagittal slice of the brain. And it said something like, um, "What makes us good and evil?" And there was a little spot pointing to it, and there was a picture of Gandhi.

    8. LF

      (laughs)

    9. DE

      And there was a little spot, it was pointing to Hitler. And, 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.

    10. LF

      Yeah.

    11. DE

      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, and 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, they're all, you know, spun each other up. And you look at anything like, I mean, look at the, you know, um, the, the cultural, uh, revolution in China or the, um, you know, the, 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."

    12. LF

      Right. (laughs)

    13. DE

      "Everyone around me seems to think it's right." And so, um, part of the maybe downside of having a live-wired brain is that you can get crowds of people doing things, um, a- as a group. So it's interesting to, you know, we would pinpoint Hitler as saying, "That's the evil guy." But in a sense, uh, I think it was Tolstoy who said the, "The king becomes, um, slave to the, to the people." In other words, you know, Hitler was just a representation of whatever was going on with that huge crowd that he was surrounded with. So, um, so I only bring that up to say that it's, you know, 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, uh, about what we often think of as being evil in society is, um, 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, we are very, you know, engineered to care about in-groups versus out-groups. And this seems to be like a really fundamental thing.

    14. LF

      Mm-hmm.

    15. DE

      So we did this experiment in my lab where we brought people in, we stick them in the scanner, and we, uh, know, and stop me if you know this, but, uh, we show them on the hand... Uh, sorry, we show them on the screen six hands. And, uh, the computer, boop-boop-boop-boop, goes around and randomly picks a hand, and then you see that hand get stabbed with a syringe needle. So you actually see a syringe needle enter the hand and come out. And it's really, uh, what that does is that triggers, uh, parts of the pain matrix, this, areas in your brain-

    16. LF

      Mm-hmm.

    17. DE

      ... that are involved in feeling physical pain. Now the interesting thing is, it's not your hand that was stabbed, so what you're seeing is, is empathy. This is you seeing someone else's hand get stabbed and you feel like, "Oh God, that's awful." Right? Okay. Um, we contrast it, by the way, with somebody's hand getting poked with a, a Q-tip, which is, you know, looks visually the same but it's, um, you don't have that same level of response. Now what we do is we label each hand with a s- with a one-word label. Christian, Jewish, Muslim, atheist, Scientologist, Hindu. And now, doo-doo-doo-doo, 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?

    18. LF

      Mm-hmm.

    19. DE

      And it turns out for everybody across all religions, they care much more about their in-group than their out-group.

    20. LF

      (laughs)

    21. DE

      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.

    22. LF

      I wonder how fundamental that is, or if it's a, it's the emergent thing about culture. Like, if we lived alone with... Like, if it's genetically built into the brain, like this, this longing for tribe.

    23. DE

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

    24. LF

      Great study, by the way.

    25. DE

      Thanks. Thanks.

    26. LF

      (laughs)

    27. DE

      What we did next is, we, 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 what happens over the course of many trials is you see everybody get 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 (clears throat) simply with this one word thing that you're, 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 a tails, you're a Justinian." These are totally made up.

    28. LF

      Mm-hmm.

    29. DE

      Okay, so they toss it, they get whatever. We give them a, a, a band that says, you know, Augustinian on it, whatever tribe they're in now. Um, 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-

    30. LF

      (laughs)

  8. 58:551:06:28

    Psychiatry

    1. LF

      in, in your, in your book you have, uh, (laughs) you have a good light bulb joke. Uh, how many psychiatrists does it take to change a light bulb? Only one, but the light bulb has to want to change. (laughs) Sorry.

    2. DE

      (laughs) Yeah.

    3. LF

      I'm a sucker for a good light bulb joke.

    4. DE

      (laughs)

    5. LF

      Okay, so given, uh, you know, I've b- I've been interested in psychiatry, uh, my whole life, just maybe tangentially. I've kind of early on dreamed to be a psychiatrist, until I understood what it entails. (laughs) Uh, but, you know, what, um, you know, is there hope for psychiatry? Uh, for somebody else to help this live wire brain to adjust?

    6. DE

      Oh. Oh, yeah. I mean, in the sense that, and this has to do with this issue about us being trapped on our own planet. I- u- uh, forget psychiatrists, just think of like when you're talking with a friend and you say, "Oh, I'm so upset about this and th-" And your friend says, "Hey, just look at it this way." Uh, you know, 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 in communities, and psychiatrists and so on to help things change that way. So that's how psychiatrists sort of help to us. But, but more importantly, the, 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.

    7. LF

      Mm-hmm.

    8. DE

      And when you're a kid you, 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, and to be inside that person's head is totally different than what it is to be inside my head. Or, there's psychopathy and, and to be inside this 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, to get what he needs. Um, that's a different head. There's a million different things going on, and it is different to be inside those heads. That 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, um, you know, 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.

    9. LF

      Uh, you, uh, this, this might be years ago, uh, but I'm not sure. In your, uh, there's an Atlantic article you've written, um-... uh, about moving away from a distinction between neurological disorders, quote unquote, "brain problems," and, uh, psychiatric disorders or quote unquote, "mind problems." So- so on that topic, how do you think about this gray area?

    10. DE

      Yeah. This is exactly, this is exactly the evolution that things are going is, you know, 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- are moving together for exactly the reason you just cited. And where this matters a lot, The Atlantic article, uh, that I wrote was called The Brain on Trial, where this matters a lot is- it's the legal system. Because the way we run our legal system now, and this is true everywhere in the world, is you know, someone shows up in front of the judge's bench or let's say there's, you know, 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, um, it actually doesn't make sense to keep doing that. And what we- 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, um, 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, uh, in a chain gang all s-... you know, that- that- that doesn't help their schizophrenia. That doesn't fix the problem. Um, if you take somebody with a drug addiction who's in jail for, you know, 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. Um, 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. Um, and that's why... So I- I- 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 between neuroscience and the legal system, and we're trying to implement changes in every county, in every state. Um, I'll just... Uh, 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, um, or- or the- the defense lawyer says, "This person has schizophrenia," most of the jury will say, "Nah, I call bullshit on that." Why? Because they don't know about schizo-... They don't n-... They don't know what it's about.

    11. LF

      Mm-hmm.

    12. DE

      And it turns out people who- uh, who know about schizophrenia feel very differently as a juror than someone who d- happens not to know anybody with schizophrenia. They think it's an excuse. So, um, you have judge and jurors 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 jurors with expertise in rehabilitative strategies and what can be done and so on, a specialized prostitution court and so on, all these different, uh, things. By the way, this is very easy for counties to implement this sort of thing, and this is- this is, I think, where this matters to get neuroscience into public policy.

    13. LF

      What's the process of- of injecting expertise into this, so do you-

    14. DE

      Yeah. I'll tell you exactly what it is. A county needs to run out of money first.

    15. LF

      (laughs)

    16. DE

      I've seen this happen over and over. So what happens is a county has a completely full jail-

    17. LF

      Mm-hmm.

    18. DE

      ... 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.

    19. LF

      (laughs) Oh, we all function best when our- when our-

    20. DE

      (laughs)

    21. LF

      ... back is against the wall.

    22. DE

      And that's what COVID is good for.

    23. LF

      Yeah.

    24. DE

      It's because we- 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.

    25. LF

      Yeah. It's really... I mean, one of the exciting things about, uh, COVID... I mean, I'm- I'm a big believer in the- the possibility of what government can do for the people, and, uh, when it becomes too big of a bureaucracy, starts functioning poorly, starts wasting money, it's nice to, uh... I mean, COVID is in-... reveals that nicely and, uh, you know, lessons to be learned about who gets elected and who goes into government. Hopefully, this, hopefully, this inspires talented a- young people to go into government to revolutionize different aspects of it. Yeah. So that's, uh-

    26. DE

      That's right.

    27. LF

      ... that's- that's the positive silver lining of- uh, of COVID.

  9. 1:06:281:13:31

    GPT-3

    1. LF

      I mean, I thought it'd be fun to ask you... I don't know if you're paying attention to machine learning world and GPT-3. Uh (laughs) uh, so the GPT-3 is this language model, this neural network that's able to, uh... it has 175 billion, uh, parameters, so it's very large and it's trained in an unsupervised (laughs) way on the internet. It just, uh, re- reads a lot of unstructured text and it's able to generate some pretty impressive things. Um, the human brain compared to that has about, you know, 1,000 times more synapses. People get so upset when machine learning people compare the brain.

    2. DE

      (laughs)

    3. LF

      And like we know, synapses are d-... It was very different, very different.

    4. DE

      Right.

    5. LF

      But like, do you, um... What do you think about GPT-3? (laughs)

    6. DE

      Here's what I think.

    7. LF

      Okay.

    8. DE

      Here's what I think, uh, a few things. What GPT-3 is doing is extremely impressive, but it's very different from what the brain does. So, um, it's a good impersonator, but just as one example, everybody takes a passage that GPT-3 has- 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 cr- okay. Oh, here's w- 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, you know, we're, 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, um, you know, I don't know if you speak, uh, 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 you." 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.

    9. LF

      Yeah, in real time, but also throughout your life. I mean, you're, uh, the, it's you're co-evolve, we're co-evolving together. We're learning-

    10. DE

      Exactly.

    11. LF

      ... how to, uh, communicate together.

    12. DE

      Exactly. But this is the, 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. Um, that's the next sentence that I needed to know about for something."

    13. LF

      (laughs) Well, of course, it could be, uh, all the impressive results we see, the question is when, if you raise the number of parameters, whether it's going to be after some fi-

    14. DE

      It will not be.

    15. LF

      (laughs) So-

    16. DE

      It will not be. No, raising more parameters won't-

    17. LF

      Yeah.

    18. DE

      Here's the thing, I- i- 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 year, 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-

    19. LF

      Mm-hmm. Yeah.

    20. DE

      ... th- th- they're connected. And, and that's great, and it's done incredibly mind-blowing, impressive things, but it's not doing the same algorithms as a human brain. Y- uh, 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, um, they can lie, they can do a million things. They, they, they are active thinkers in our world in doing things, and this, of course... I mean, look, we totally agree on in- 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 -

    21. LF

      Yeah. Reason-

    22. DE

      ... things -

    23. LF

      ... reason about the world efficiently, learn efficiently, adapt-

    24. DE

      Exactly.

    25. LF

      ... efficiently. But, it's still the rate of improvement, it's, uh, to me, it's po- it's possible that we'll be surprised, like, uh... (laughs)

    26. DE

      I agree. Possible we'll be surprised. But what I would s- what I would assert, and I'm, and, and I'm glad I'm getting to say this on your podcast-

    27. LF

      (laughs)

    28. DE

      ... so we can look back on this in 2 years, in 10 years, and so on, is that we've got to be much more sophisticated than units and synapses between them.

    29. LF

      Okay.

    30. DE

      L- l- let me give you an example, and this is something I talk about in Live Wired, is despite the amazing impressiveness, mind-blowing impressiveness, um, computers don't have s- 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. Um, 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.

  10. 1:13:311:21:51

    Intelligence in the brain

    1. DE

    2. LF

      So, in terms of the structure of the brain, again, this may be going into speculation land. I hope you go along with me. (laughs)

    3. DE

      Yeah, sure. I'll help you.

    4. LF

      Is, uh... 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, what is it about the brain that-

    5. DE

      S- 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.

    6. LF

      But in terms of a structure, so we look, humans are much smarter than fish, maybe not dolphins, but m- dolphins are mammals, right?

    7. DE

      But I assert that what we mean by smarter has to do with live wiring. So, so what we mean when-

    8. LF

      Right.

    9. DE

      ... we say, "Oh, we're smarter," is, oh, you 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, and I re- read once that you could do this other thing," and so on.

    10. LF

      So do you think there's... Is there something... I know the, the, the, these are mysteries, but like, architecturally speaking, what feature of the brain of, uh, 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... Uh, is there any lessons about the human brain you think might be inspiring for us in- to take into the artificial... into the machine learning world?

    11. DE

      Yeah. I'm actually just trying to write something up on this now called, you know, if you wanna build a robot, start with the stomach.

    12. LF

      (laughs)

    13. DE

      And what I mean by that, what I mean by that is-

    14. LF

      (laughs)

    15. DE

      ... a robot has to care. It has to have hunger. It has to care about surviving-

    16. LF

      Uh-huh.

    17. DE

      ... that kind of thing. Uh, here's an example. So the penultimate chapter of my book, um, I titled The, The Wolf and the Mars Rover. And I just... Look at the 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 cost- that cost billions of dollars, died 'cause it's got a wheel, so 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 I've got a body plan that's different than what I thought a few minutes ago, but I ha- 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, oops, that didn't work. Oh, oh, okay, I'm kind of getting it to work." But the Mars rover doesn't do that. It just says, "Oh, jeez, I was pre-programmed to have four wheels, now I have three. I'm screwed."

    18. LF

      Yeah, you know, I, I don't know if you're familiar with a philosopher named Ernest Becker. He wrote, uh, d- a book called Denial of Death, and there's a few psychologists, Sheldon Solomon, I think he... I just spoke with him on this podcast-

    19. DE

      Mm-hmm.

    20. LF

      ... um, who developed, uh, terror management theory, which is, uh, th- the, like, Ernest Becker is a philosopher that basically said that, uh, um, mortality, fear of mortality is at the core of it.

Episode duration: 1:41:23

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