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Speaker 1: The Craig Ferguson Pants on Fire Tour is on sale now.

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Speaker 1: It's a new show, it's new material, but I'm afraid

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Speaker 1: it's still only me, Craig Ferguson on my own, standing

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Speaker 1: on a stage telling comedy words. Come and see me,

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Speaker 1: buy tickets, bring your loved ones, or don't come and

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Speaker 1: see me. Don't buy tickets and don't bring your loved ones.

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Speaker 1: I'm not your dad. You come or don't come, but

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Speaker 1: you should at least know what's happening, and it is.

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Speaker 1: The tour kicks off late September and goes through the

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Speaker 1: end of the year and beyond. Tickets are available at

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Speaker 1: the Craig Ferguson Show dot com slash tour. They're available

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Speaker 1: at the Craig Ferguson show dot com slash tour or

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Speaker 1: at your local outlet in your region. My name is

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Speaker 1: Craig Ferguson. The name of this podcast is Joy. I

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Speaker 1: talk to interest in people about what brings them happiness.

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Speaker 1: On the podcast today, my guest is David Eagleman.

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Speaker 2: Professor David Eagleman to be precise. Professor Eagleman, or David

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Speaker 2: as I call him, is a neuroscientist he knows a

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Speaker 2: lot about the human brain, but as it turns out,

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Speaker 2: he knows a lot about artificial brains too.

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Speaker 3: He's just a very brainy guy.

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Speaker 4: So I'm going to sound a bit more stupid than

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Speaker 4: usual in Jomi, David. Let me just say this before

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Speaker 4: we start.

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Speaker 1: Do I call you David? Do I call you mister Eagleman?

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Speaker 1: Do I call you doctor Eagleman? Or do you call

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Speaker 1: you professor Eagleman?

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Speaker 3: Or sir? Please call me David. All right? Is it

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Speaker 3: a doctor? By the way, you're doctor? Yeah? Doctor Eagelman

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Speaker 3: would be what yes, but my mother would call me yes.

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Speaker 1: Now I gotta apologize because I'm going to not so

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Speaker 1: much to you personally, because I think you'll probably be

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Speaker 1: able to handle it, but to people who already know

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Speaker 1: and and understand what you do, I'm going to come

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Speaker 1: across as someone who doesn't know anything about what you do. Now,

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Speaker 1: let's just say that I actually do know what you're doing.

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Speaker 1: I know everything about your studies and and what you

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Speaker 1: kind of do. And I'm not an ideot, but everybody

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Speaker 1: knows I kind of a little bit. Because neuroscience is

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Speaker 1: I barely understand the Dictionary definition of neuroscience correct me

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Speaker 1: if I'm wrong. I think it is the study of

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Speaker 1: how the brain works due to the physicality of the brain.

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Speaker 3: Is that. Yeah, you don't even need the second half.

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Speaker 3: Just trying to figure out how the brain works, trying

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Speaker 3: to figure out what's going on with the brain. And

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Speaker 3: it can be anything from understanding how vision works, are hearing,

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Speaker 3: to understanding decision making, to understanding emotions, to understanding why

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Speaker 3: we have consciousness or how we perceive time. Any of

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Speaker 3: that falls under the umbrella of neuroscience.

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Speaker 1: But it's interesting because it seems to me to be

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Speaker 1: something that it's an interesting science because it seems to

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Speaker 1: kind of wonder the theology and metaphysics, and because everything

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Speaker 1: is perception. Even the study of neuroscience is perception. So

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Speaker 1: how do you feel like you kind of examining yourself

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Speaker 1: from the inside.

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Speaker 3: Yeah, that's right. Well, I would say at the edges,

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Speaker 3: neuroscience scratches lots of things, certainly philosophy, maybe theology, but

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Speaker 3: the you know, the way you can do things is

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Speaker 3: set things up objectively in the real world where you

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Speaker 3: can verify. Look, I have, you know, three circles that

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Speaker 3: are the color red, you know, projecting this wavelength on

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Speaker 3: the screen and you know, what are people seeing. That's

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Speaker 3: still example, But the point is we can set things

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Speaker 3: up in the world and understand what people are individually experiencing.

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Speaker 3: I'll give you an example. One of the things I

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Speaker 3: study is called synesthesia, and that's where people have a

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Speaker 3: blending of the senses. So they might look at letters

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Speaker 3: on the page and it triggers a color experience for them,

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Speaker 3: so they'll see Jay is purple, and why is blue?

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Speaker 3: And m is red and so on, and you know,

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Speaker 3: it's just an internal experience that they're having. We can

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Speaker 3: verify what's going on in the real world. We can

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Speaker 3: compare people to each other. About three percent of the

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Speaker 3: population has synesthesia. But there are lots of things like

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Speaker 3: this that we do where we study across people to

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Speaker 3: understand how perception differs. You know, there are other things

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Speaker 3: like if I ask you Craig to imagine a you know,

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Speaker 3: an ant crawling our red and white table cloth towards

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Speaker 3: jar of purple jelly. How do you perceive that in

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Speaker 3: your head? Is it clear like a movie or is

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Speaker 3: it you don't really see anything at all, it's just conceptual.

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Speaker 1: Does it involve you then? And like, for example, you

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Speaker 1: just gave me the the ant on the If you say,

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Speaker 1: is it clear like a movie, it's such a weirdly Uh,

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Speaker 1: it's semantics because I mean, if I do I imagine

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Speaker 1: a clear iPhone film?

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Speaker 3: Is it show on? Is a sixteen millimeters or print?

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Speaker 3: Is it? Do you know what I mean? Is it

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Speaker 3: black and white? Right? So, if you had to have

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Speaker 3: if there was a spectrum from no picture at all

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Speaker 3: in your head to a movie at you know, at

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Speaker 3: the other end of the extreme, where would where would

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Speaker 3: you be with the ant on the paper? Yeah, the

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Speaker 3: on on the table cloth.

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Speaker 1: I think I could get myself right up to imax

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Speaker 1: with the end on the paper.

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Speaker 3: Okay, that's that's amazing. So it turns out that there

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Speaker 3: is a spectrum across the population. Everyone's spread pretty evenly

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Speaker 3: across this in terms of how how visually you imagine

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Speaker 3: things on the inside. And again, this is something that

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Speaker 3: we can test across the population, and we can also

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Speaker 3: test it objectively using grain imaging to see how much

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Speaker 3: activity there is in the visual part of the brain.

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Speaker 3: And we see that across anything we measure people exist

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Speaker 3: on a spectrum. For example, if I ask you how

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Speaker 3: loud or intrusive is your internal voice? You know, everyone

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Speaker 3: has a dialogue with themselves, right right? Are you aware

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Speaker 3: of your internal voice all the time or hardly? Ever?

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Speaker 1: I would say that that is very much situationally dependent.

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Speaker 1: When I'm you know, when I'm calm, not at all.

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Speaker 1: When I'm angry, probably not at all. And when i'm

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Speaker 1: you know, when I'm trying to make a difficult or

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Speaker 1: political decision a lot, you know so, or or am

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Speaker 1: I thinking about the wrong thing?

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Speaker 3: No? No, that's that's right. That's a good observation that

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Speaker 3: it differs moment to moment. But across the population, we

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Speaker 3: also find, you know, some people are really overwhelmed by

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Speaker 3: their internal radio. Other people have what's called an endophasia,

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Speaker 3: which means no internal voice. They just know it's totally

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Speaker 3: silent in there. Essentially, across anything we measure, we find

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Speaker 3: that people have very different results. Or how about your memory?

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Speaker 3: Are you do you have a great autobiographical memory? Can

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Speaker 3: you remember exactly what you were doing at this time

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Speaker 3: last year or five years ago?

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Speaker 1: And I think it's deteriorating as well. Actually as I age,

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Speaker 1: I really am beginning to think there may be something

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Speaker 1: in that.

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Speaker 3: Yeah, yeah, you just said that three minutes ago. No,

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Speaker 3: I'm kidding her. Yeah, that's the thing. But you know,

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Speaker 3: some people like Mary Lou Henner the actress, and you

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Speaker 3: know somebody I have this, you know, untaxable autobiographical memory

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Speaker 3: and everywhere in between.

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Speaker 1: I talked to Mary Lou Henna rctly and asked her

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Speaker 1: about that, and she I tested her because I had

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Speaker 1: worked with her years before on a different show. This

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Speaker 1: was and I talked to her on late night and

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Speaker 1: she had been on the drink, you know why. I

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Speaker 1: got even remember why I was talking to her about it.

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Speaker 1: But she really she really could do that. It's kind

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Speaker 1: of it's like a weird trick. It's very it's impressive.

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Speaker 1: I guess is a genetic I guess it's genetics.

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Speaker 3: Right, yeah, yeah, and so and actually so are all

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Speaker 3: these things, at least as far as we can tell,

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Speaker 3: you know, all this. But what it goes to illustrate

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Speaker 3: is that people are very different from one another on

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Speaker 3: the inside. And one of the this has been one

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Speaker 3: of my eras of interest in neuroscience is figuring out

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Speaker 3: why what are the genes or what are the experiences

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Speaker 3: or you know, what is the thing that has led

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Speaker 3: to different circuitry in Mary Leeu's brain in your brain,

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Speaker 3: that would lead you to have different experiences of what

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Speaker 3: memory is.

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Speaker 1: What would happen or have you ever encountered anithon divid

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Speaker 1: I can imagine that it could be potentially very explosive

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Speaker 1: if you say you know, well you know, because it

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Speaker 1: could lead you into horrible areas of racism. Like you say,

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Speaker 1: Medisranean people tend their brains stand to be like this,

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Speaker 1: or Nordic people their brains stand to.

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Speaker 3: Be like this. Is that a real thing or is

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Speaker 3: that made up by Nazis? The general story is, you know,

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Speaker 3: Homo sapiens have only spread around the earth very recently.

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Speaker 3: So you know, we originated in Africa about two hudred

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Speaker 3: fift thousand years ago. We came out the top and

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Speaker 3: half the people turned left and half turned right and

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Speaker 3: became you know, Europeans or Asians. But on the inside,

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Speaker 3: the organ that we have, that three pound mission control

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Speaker 3: center hasn't changed. That's the same same thing. Why because

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Speaker 3: two hundred fift thousand years just isn't enough time. In

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Speaker 3: the same way that people's hearts and lungs and kidneys

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Speaker 3: are the same as you go around the world. So

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Speaker 3: while there's an enormous amount of difference between people, there

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Speaker 3: aren't between groups of people. On average. You find this

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Speaker 3: giant distribution everywhere.

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Speaker 1: Well about the idea, I mean, I presume this study.

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Speaker 1: Is it driven, I mean it's knowledge driven. I guess

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Speaker 1: it's science. But is it a medical Is that what.

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Speaker 3: We're looking for?

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Speaker 1: Is it to try and solve problem? Like one of

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Speaker 1: this brings to mind is demanchia obviously in Alzheimer's, which

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Speaker 1: is a real kind of cognitive problem.

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Speaker 3: Yes, yeah, exactly right. So you know, the field of

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Speaker 3: neuroscience traditionally studies diseases and disorders and what happens with

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Speaker 3: the brain to make it change, for example, in cases

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Speaker 3: of dementia. I also study that. A lot of the

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Speaker 3: things I do have to do with those areas, but

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Speaker 3: just personally, I got very interested in the topic of

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Speaker 3: you know, how does the brain run in everyone under

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Speaker 3: normal circumstances, and again, what are the differences between people?

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Speaker 3: And by the way, how does it matter for society.

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Speaker 3: So one of the things I do I run this

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Speaker 3: Center for Neuroscience and Law, which is all the things

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Speaker 3: that we're learning in neuroscience. How does this affect the

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Speaker 3: legal system and how we think about things there.

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Speaker 1: I mean, so if it there's a behavioral problem, for example,

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Speaker 1: excuse me, if you find out that someone reacts a

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Speaker 1: certain way being triggered by a certain stimulus. Like off

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Speaker 1: the top of my head, I'm not a doctor and

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Speaker 1: I don't know what I'm talking about, but say that

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Speaker 1: I have a brain that if you touch me, I

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Speaker 1: get very very upset. Is that something that you could

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Speaker 1: bring into the legal world where you say, well, this

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Speaker 1: person behaved very badly when they were being arrested, but

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Speaker 1: now we found out they've got the type of brain

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Speaker 1: if you touch them, they get very upset.

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Speaker 3: So here's the thing, great question. It turns out none

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Speaker 3: of this lets people off the hook. So if you

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Speaker 3: break the law, if you cross a sideal line, you

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Speaker 3: still have to confront the legal system for it. But

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Speaker 3: one of the things that tells us a lot about

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Speaker 3: is new methods for rehabilitation. So what we do right

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Speaker 3: now is a society and it is true around the

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Speaker 3: world we treat incarceration as a one size fits all solution,

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Speaker 3: but in fact, we know so much about the brain

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Speaker 3: now that if you come in with this particular disorder

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Speaker 3: where touching you on your shoulder, makes you react badly.

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Speaker 3: You know, maybe there's something we can do to help

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Speaker 3: you out, at least such that you know at least

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Speaker 3: exactly what we're not gonna do. And then it turns

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Speaker 3: out that you know, we might be able to help

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Speaker 3: you for the next time. Now, again, it doesn't let

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Speaker 3: people off the hook. It's not that you go without punishment,

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Speaker 3: but that's that's the idea, and there are lots of

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Speaker 3: ways we can do this. Just one example. I've been

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Speaker 3: a strong advocate for having specialized mental health courts. So

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Speaker 3: what we do right now as everyone goes to the

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Speaker 3: same court system, but if somebody has mental illness, which

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Speaker 3: is a you know, quite a high number of people

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Speaker 3: with mental illness end up on the wrong side of

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Speaker 3: legal system. You know, you have judges and juries that

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Speaker 3: maybe don't know anything about let's say schizophrenia or take

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Speaker 3: drug rehabilitation. Yeah, most judges and juries don't know a

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Speaker 3: great deal about what options are available. So having specialized

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Speaker 3: mental health courts, specialized drug courts, things like this are

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Speaker 3: really helpful where you have people that expertise, they know

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Speaker 3: the strategy is available.

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Speaker 1: It's an interesting thing that you mentioned excuse me schizophrenia

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Speaker 1: and drug rehabilitation, because schizophrenia. Remember I know nothing about this.

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Speaker 1: You know, you're the brain. I'm pinky, right, So that

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Speaker 1: my understanding of is or the tinium and I know

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Speaker 1: about it is that schizophrenia is a condition which you

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Speaker 1: I develop.

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Speaker 3: From a genetic position. Right. It's it's an illness that

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Speaker 3: is born within you. Right. It has a strong generic

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Speaker 3: component to it. It's not entirely can it be brought

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Speaker 3: on by by outside stimulus. It certainly can be exacerbated

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Speaker 3: and brought on early by things like drugs, for example.

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Speaker 3: So for sure, example, this is a real problem with

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Speaker 3: young people using marijuana, which has a much higher percentage

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Speaker 3: of THHC now than it used to in earlier strains.

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Speaker 3: A lot of young people are getting psychotic breaks as

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Speaker 3: a result of that much higher percentage than used to.

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Speaker 1: That happened to me when I took marijuana when I

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Speaker 1: was when I was young, I stopped take it.

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Speaker 3: I started.

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Speaker 1: I took marimana when it was about eighteen through until

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Speaker 1: I was about twenty, which is all terrible thing to do.

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Speaker 1: And I didn't do tons of it, but there was

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Speaker 1: at one point I took some and it it was

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Speaker 1: one of the most horrendous experiences of my life from marijuana,

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Speaker 1: and it's very hard to explain that to people who

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Speaker 1: don't get affected.

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Speaker 3: By it that way, right, right, exactly, And there's probably

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Speaker 3: a genetic component to that in terms of who gets

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Speaker 3: affected and who doesn't. But yeah, So back to your

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Speaker 3: question about schizophrenia though, right, So, what were you going

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Speaker 3: to So it's mostly genetic, but there are environmental things

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Speaker 3: that exacerbate it.

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Speaker 1: Well, I was going to ask you about drug addiction,

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Speaker 1: which I think I don't know. Is that the same

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Speaker 1: is it percent more percentage genetic for schizophrenia is for

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Speaker 1: drug addiction? Is it more environmental and land behavior for

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Speaker 1: drug and alcohol addiction? I can't imagine there is peer

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Speaker 1: pressure to become schizophrenic, you know. It seems like it's

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Speaker 1: almost accidental. Whereas I speak, is a sober alcoholic? I mean,

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Speaker 1: I didn't say out for that to happen, you know,

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Speaker 1: I say for the sober thing to happen, it basically,

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Speaker 1: but it kind of crept up on me. Is there

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Speaker 1: a genetic predisposition to both of these things? Is what

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Speaker 1: I'm saying.

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Speaker 3: There is, although completely separate genetics on the Sudie. But yes,

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Speaker 3: there is a genetic predisposition for addiction, for having an

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Speaker 3: addictive personality. That is clearly a thing. But there are

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Speaker 3: very few things really that can be separated cleanly into

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Speaker 3: nature versus nurture, because there are influences on both. I'll

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Speaker 3: just give you an example. It turns out that with

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Speaker 3: back to schizophrenia, one of the things that influences whether

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Speaker 3: someone has a psychotic break in part has to do

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Speaker 3: with whether they are living in a place where they

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Speaker 3: are in their culture, in their language, or whether they

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Speaker 3: have immigrated somewhere else. And when you're living somewhere else,

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Speaker 3: there are things like you know, you can't for example,

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Speaker 3: you can't make jokes in your new language as well,

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Speaker 3: or you can't fit in exactly as well. And it

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Speaker 3: turns out that more people have psychotic breaks. In my

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Speaker 3: book in Cognito, I talked about this as you know,

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Speaker 3: one of the risks of getting schatphrenia is the color

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Speaker 3: of your passport. So you know that's that's a surprising

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Speaker 3: social aspect of it that people have discovered.

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Speaker 1: Well, that's that's kind of fascinating to me. Then does

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Speaker 1: that does that lead you to study more men aloneness,

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Speaker 1: because clearly there are things like it's not a man

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Speaker 1: in aloneness, but clearly if someone is dyslexic, they're bre dyslexic. Right,

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Speaker 1: it's not something you learn as a little baby, that's right.

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Speaker 1: But if someone's left handed or right handed? I was,

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Speaker 1: was that do you learn?

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Speaker 3: That? Is it?

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Speaker 1: I mean, how much information you get right in the beginning,

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Speaker 1: I think, is what I'm saying.

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Speaker 3: Yeah, yeah, these are great questions. The fact is, when

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Speaker 3: it comes to nature versus nurture, the answer is almost

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Speaker 3: always both. There are a very tiny number of things

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Speaker 3: that are one or the other. Four example, the first

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Speaker 3: gene that was pulled for a disease was Huntington's disease,

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Speaker 3: and everyone thought, great, if you have this gene, you're

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Speaker 3: gonna get Huntington's that's it. And never thought this is

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Speaker 3: going to be easy. But it turns out it's one

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Speaker 3: of the few monogenetic diseases that exist, meaning you know,

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Speaker 3: if you have this gene, blah blah, because everything turns

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Speaker 3: out to be more complicated. Other diseases involve genetics. They

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Speaker 3: have all lots of different genes, whole families of genes.

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Speaker 3: We're still trying to get to the bottom of them.

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Speaker 3: But also most of everything involves what's going on societally too.

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Speaker 3: Let me give you an example of this. This came

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Speaker 3: out some years ago. The question is are there genes

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Speaker 3: for depression? Well, it turns out if you're a carrier

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Speaker 3: of particular genes, the question is, okay, are you more

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Speaker 3: likely to get depression? And the answer is that totally

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Speaker 3: depends on the number of really traumatic life events you have.

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Speaker 3: So let's say, you know, a terrible car accident or

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Speaker 3: the death of a loved one, things like that. If

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Speaker 3: you've had a lot of traumatic life experiences and you

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Speaker 3: carry these genes, then your chance of getting depression is

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Speaker 3: much higher than someone who's had the same number of

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Speaker 3: traumatic life experiences but don't carry the genes. But if

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Speaker 3: you don't have let's say any or just a few

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Speaker 3: life experiences that are bad, your chances are no different

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Speaker 3: than anyone else. So this is now we refer to

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Speaker 3: this as gene times environment you know, gene x environment interactions.

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Speaker 3: So it depends on both things.

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Speaker 1: So it's kind of like a recipe then, right, yeah, yeah,

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Speaker 1: Like so I want to stay about like some some

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Speaker 1: bit of this and some bit of that.

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Speaker 3: You know, you get a little bit of sugar and

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Speaker 3: a little bit of salt and a little.

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Speaker 1: Bit of trauma, and you get you know, you get

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Speaker 1: a spatial thing, exactly.

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Speaker 3: And what this points to is the complexity of both

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Speaker 3: biology and life, right you know, yeah, born, Yeah, things

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Speaker 3: can happen to you that we're unexpected, and you can

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Speaker 3: have genes that interact in unexpected ways.

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Speaker 1: Yes, And that's so I imagine those probably an almost

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Speaker 1: infinite amount of variables and all these different things. So

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Speaker 1: to depend on how someone is ever going to be,

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Speaker 1: it just remains as elusive as ever then, right, that

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Speaker 1: is exactly right.

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Speaker 3: So you take a movie like Minority Report, where the

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Speaker 3: shtick was that you could predict who's going to commit

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Speaker 3: a crime in the future. It's total fantasy and it'll

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Speaker 3: never happen. In other words, people think, hey, as we

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Speaker 3: get better with brain imaging or with AI, won't we

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Speaker 3: get to that point someday? But the answer is never happened.

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Speaker 3: Why Because your brain is changing and rewiring every second

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Speaker 3: of your life depending on your interactions. So, for example,

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Speaker 3: your brain and my brain are different than they were

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Speaker 3: five minutes ago, just from conversing with each other. Right, So,

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Speaker 3: and this is the notion of brain plasticity, which is

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Speaker 3: that fundamentally, what mother nature has done is built a

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Speaker 3: system that absorbs the world and is constantly reconfiguring itself.

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Speaker 1: So I kind of you mentioned the AI there, so

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Speaker 1: I kind of find that fascinating because the idea I

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Speaker 1: suppose of AI. Again, I know not of AI either,

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Speaker 1: but the idea is that it mimics the landing pattern

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Speaker 1: of a human brain, right, because that's all it can do,

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Speaker 1: given the fact that's all we have to build it with.

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Speaker 3: Sort of, So this is the really interesting thing. So

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Speaker 3: AI launched many decades ago, and the idea was, okay, look,

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Speaker 3: the brain is super complicated, but fundamentally you've got these units,

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Speaker 3: and you've got these connections between the units in the brain.

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Speaker 3: These are neurons, and these are all the connections between

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Speaker 3: the urts. So people said, look, what if we just

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Speaker 3: make a cartoon version of this where you just have

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Speaker 3: these you know, little units that we've got these connections

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Speaker 3: that you are just changing the strength of those connections

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Speaker 3: across the big network. So that's where artificial neural networks

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Speaker 3: took off and went in that direction, and it turns

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Speaker 3: out that's become incredibly successful. We've got this great renaissance

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Speaker 3: going on of AI. But it's actually not that much

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Speaker 3: like the human brain. It's it's quite different. So there

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Speaker 3: are many many things that the human brain does that

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Speaker 3: AI simply can't, and at least in its current architecture,

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Speaker 3: you won't do anytime soon. I'll give you an example

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Speaker 3: of that. But I'll also say really quickly that it's

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Speaker 3: not to say that we can't build artificial neural networks

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Speaker 3: that are just like the brain and someday, maybe five

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Speaker 3: years now, maybe fifty years from now, do everything in

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Speaker 3: brain does. But our current stuff like chat GPT, for example,

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Speaker 3: does not have an internal model of the world. So

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Speaker 3: if I ask GPT, hey, when Craig Ferguson walks into

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Speaker 3: a room, does his nose come with him? It won't

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Speaker 3: know the answer to that because it has no model

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Speaker 3: of the world. You know, does does his spleen come

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Speaker 3: with him?

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Speaker 2: Well?

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Speaker 3: How does it know? It doesn't? It why? Because the

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Speaker 3: way chat GPT is trained, it's read everything in the

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Speaker 3: world and it's just doing statistical games on what word

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Speaker 3: is likely to come next. That's all GPT does. It's

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Speaker 3: an enormous, enormous network yeah, that's just why I did ask.

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Speaker 1: I asked chat GPT to write me a short Craig

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Speaker 1: ferguson stand up comedy routine. And you know, I feel

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Speaker 1: like either I'm a terrible writer but my delivery is great,

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Speaker 1: or just a a terrible comedian, or chat GPT has

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Speaker 1: got a way to go yet, and it should maybe,

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Speaker 1: you know, work on his material in some clubs.

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Speaker 3: So so, okay, this is a really good point. And

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Speaker 3: chat GPT is terrible at humor, at making up new jokes, Okay.

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Speaker 3: Why it's because it's just a statistical parent. And what

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Speaker 3: it realizes is that humor is all about the violation

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Speaker 3: of expectation, but it doesn't know how to violate it. Well,

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Speaker 3: so if you ask it, tell me a joke about

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Speaker 3: you know, three guys who walk into a bar and say,

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Speaker 3: you know, and do blah blah blah. It'll say the

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Speaker 3: first guy does this, the second guy does this, and

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Speaker 3: the third guy does this, and it'll say something that

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Speaker 3: doesn't make any sense because it knows the third thing

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Speaker 3: is supposed to break the pattern, but it doesn't know

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Speaker 3: how to do it in a funny way.

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Speaker 5: I feel in Spain, I I think there's an argument

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Speaker 5: to be made for having a comedy night in a

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Speaker 5: club where comedians have to tell jokes written by computers.

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Speaker 1: And in fact, I am going to put that together

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Speaker 1: as soon as possible.

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Speaker 3: So this is funny that you mentioned this because I'm

434
00:23:27,040 --> 00:23:31,360
Speaker 3: actually working on on on a television documentary now. I'm

435
00:23:31,400 --> 00:23:34,440
Speaker 3: writing this up with my colleagues. It's called Bits and Giggles,

436
00:23:34,800 --> 00:23:37,640
Speaker 3: and it's exactly about this. It's about a comedian who

437
00:23:37,680 --> 00:23:41,399
Speaker 3: goes on a road trip with no Yeah, We've actually

438
00:23:41,440 --> 00:23:45,560
Speaker 3: built a little bot that does you know speech to text?

439
00:23:45,560 --> 00:23:47,600
Speaker 3: It goes off to chat GPT and then does you

440
00:23:47,640 --> 00:23:50,600
Speaker 3: know text to speech? So you can have a dialogue

441
00:23:50,680 --> 00:23:53,359
Speaker 3: back and forth with this little bot. And the question

442
00:23:53,600 --> 00:23:56,159
Speaker 3: is what does AI mean for us? Will it be

443
00:23:56,280 --> 00:23:59,119
Speaker 3: funny it, can it take the place of community? Can

444
00:23:59,200 --> 00:24:02,960
Speaker 3: it perform on stage with a comedian? Yeah?

445
00:24:03,119 --> 00:24:06,320
Speaker 1: I think I think it's quite interesting because I because

446
00:24:06,359 --> 00:24:09,639
Speaker 1: of my own history with komedy, I love it and

447
00:24:09,720 --> 00:24:13,640
Speaker 1: I feel that it's a very human connectivity thing. It's

448
00:24:13,680 --> 00:24:16,320
Speaker 1: a very and it's odd way, it's very intimate thing,

449
00:24:17,160 --> 00:24:19,880
Speaker 1: even although you know it's one person then an audience

450
00:24:20,000 --> 00:24:22,040
Speaker 1: in the way that I do it anyway, and I

451
00:24:22,119 --> 00:24:27,240
Speaker 1: wonder if that happens, then do you have your robot lover,

452
00:24:27,440 --> 00:24:31,520
Speaker 1: do you have your robot husband, your robot wife, your

453
00:24:31,640 --> 00:24:34,520
Speaker 1: robot spouse, your robot children?

454
00:24:34,720 --> 00:24:38,760
Speaker 3: I mean, is it? Is it possible? Yeah? So okay,

455
00:24:38,840 --> 00:24:40,760
Speaker 3: so this is funny mite. So my wife has been

456
00:24:40,840 --> 00:24:42,760
Speaker 3: joking about this for a long time. She's been joking

457
00:24:42,760 --> 00:24:45,800
Speaker 3: about the five percent better David, by which she means,

458
00:24:46,400 --> 00:24:48,720
Speaker 3: what does she have AI David that had all my

459
00:24:48,760 --> 00:24:52,080
Speaker 3: good qualities but it never got distracted or angry or

460
00:24:52,119 --> 00:24:55,879
Speaker 3: you know, we looked in my phone beeps or whatever. So, uh,

461
00:24:56,400 --> 00:24:59,600
Speaker 3: we've talked about this a lot and what this means.

462
00:24:59,680 --> 00:25:02,359
Speaker 3: And you know, the issue now is that lots of

463
00:25:02,400 --> 00:25:04,879
Speaker 3: young people are getting AI girlfriends and to some lesser

464
00:25:04,920 --> 00:25:09,639
Speaker 3: extent AI boyfriends girls getting that. In Japan, apparently this

465
00:25:09,680 --> 00:25:13,840
Speaker 3: is becoming a bigger thing where people have these AI relationships.

466
00:25:14,640 --> 00:25:17,760
Speaker 3: We can imagine perhaps the downsides of this, but I

467
00:25:17,800 --> 00:25:20,520
Speaker 3: do want to note I think an upside for young

468
00:25:20,600 --> 00:25:24,159
Speaker 3: people is you might be able to learn how to

469
00:25:24,240 --> 00:25:27,520
Speaker 3: navigate relationships a little bit better, and you know, you

470
00:25:27,600 --> 00:25:31,359
Speaker 3: kind of get your sandbox, your practice relationship, and if

471
00:25:31,400 --> 00:25:34,480
Speaker 3: the AI it gives you good feedback, you might actually

472
00:25:34,560 --> 00:25:36,400
Speaker 3: be a better person in relationships.

473
00:25:36,840 --> 00:25:39,600
Speaker 1: Yeah, but then you don't get the requisite amount of

474
00:25:39,640 --> 00:25:42,520
Speaker 1: trauma to make you human. I mean, no one wants

475
00:25:42,560 --> 00:25:45,840
Speaker 1: to wish trauma and anyone but junior high school may

476
00:25:45,920 --> 00:25:49,520
Speaker 1: be an essential component of making you a better persons.

477
00:25:50,560 --> 00:25:54,200
Speaker 3: It's an interesting conundrum. So I agree with you, and

478
00:25:54,880 --> 00:25:56,680
Speaker 3: it turns out the way to do this, I think,

479
00:25:56,760 --> 00:26:00,320
Speaker 3: is to make the AI bought be traumatic in the

480
00:26:00,400 --> 00:26:03,080
Speaker 3: sense of, you know, if you say something wrong to it,

481
00:26:03,080 --> 00:26:05,320
Speaker 3: it's not kind or something. You know, it gets its

482
00:26:05,320 --> 00:26:09,359
Speaker 3: feelings hurt. Obviously it's just statistically impersonating this, but the

483
00:26:09,440 --> 00:26:12,480
Speaker 3: point is instead of having an AI that just says, oh,

484
00:26:12,520 --> 00:26:14,399
Speaker 3: that was so good, that was so funny and nice,

485
00:26:14,760 --> 00:26:17,000
Speaker 3: instead it gives you real feedback, tough love.

486
00:26:17,160 --> 00:26:20,520
Speaker 1: And that that might actually work better than the parenting

487
00:26:20,560 --> 00:26:24,359
Speaker 1: that my generation inflicted on the next generation, which I

488
00:26:24,359 --> 00:26:27,399
Speaker 1: think was a little too positive. I don't know, something

489
00:26:27,440 --> 00:26:30,119
Speaker 1: went wrong, So let me try it. Let me steer

490
00:26:30,160 --> 00:26:32,600
Speaker 1: you around back to the brain and perception a little bit,

491
00:26:32,640 --> 00:26:36,320
Speaker 1: because I'm fascinated by the idea in my own life,

492
00:26:36,320 --> 00:26:39,480
Speaker 1: I'm fascinated by the idea of I think most people

493
00:26:39,520 --> 00:26:42,200
Speaker 1: are What is all about was the meaning of life

494
00:26:42,520 --> 00:26:43,960
Speaker 1: was the is there a god?

495
00:26:44,480 --> 00:26:44,719
Speaker 3: You know?

496
00:26:45,200 --> 00:26:49,080
Speaker 1: And I wonder if in the study of the brain,

497
00:26:49,280 --> 00:26:53,159
Speaker 1: which is you know, it's information central, it's information and

498
00:26:53,200 --> 00:26:57,280
Speaker 1: control everything's passing through there, does it lead you in

499
00:26:57,400 --> 00:27:01,560
Speaker 1: any direction personally for yourself? Does it lead you in

500
00:27:01,600 --> 00:27:02,920
Speaker 1: an atheistic direction?

501
00:27:03,040 --> 00:27:06,639
Speaker 3: Does it lead you in a faith based direction? But

502
00:27:06,800 --> 00:27:09,600
Speaker 3: does it do anything to you personally? Sure? I mean,

503
00:27:09,640 --> 00:27:12,359
Speaker 3: I've spent my life in science, and I feel like

504
00:27:12,560 --> 00:27:17,359
Speaker 3: the main lesson that one can derive is to really

505
00:27:17,440 --> 00:27:22,879
Speaker 3: understand the vastness of our ignorance. And so the more

506
00:27:22,960 --> 00:27:26,800
Speaker 3: you reach down into science in the world and the cosmos,

507
00:27:26,920 --> 00:27:29,399
Speaker 3: you find that there's so much that we don't know,

508
00:27:29,520 --> 00:27:31,679
Speaker 3: we don't understand. So what does that meant for me?

509
00:27:32,119 --> 00:27:37,520
Speaker 3: I am neither an atheist nor religious, because atheism, at

510
00:27:37,600 --> 00:27:40,879
Speaker 3: least in its harshest form, in its strictest form, kind

511
00:27:40,880 --> 00:27:44,000
Speaker 3: of often pretends, Hey, we've got this all figured out,

512
00:27:44,000 --> 00:27:46,240
Speaker 3: we know what's going on here, but it's clear that

513
00:27:46,240 --> 00:27:49,119
Speaker 3: we don't know what's going on here. On the flip side,

514
00:27:49,880 --> 00:27:54,320
Speaker 3: all the traditional religions also pretend to have certainty about stuff,

515
00:27:54,359 --> 00:27:58,080
Speaker 3: and they're all making it up. And so that puts

516
00:27:58,119 --> 00:28:00,879
Speaker 3: me in the middle. I don't call my self agnostic,

517
00:28:00,960 --> 00:28:05,439
Speaker 3: because agnostic often means I don't know if there's a

518
00:28:05,480 --> 00:28:08,159
Speaker 3: guy with a beard on a cloud or not. But

519
00:28:08,480 --> 00:28:11,040
Speaker 3: I call myself something else. I call myself a possibilion.

520
00:28:11,359 --> 00:28:15,760
Speaker 3: And the idea with possibilianism is an active exploration of

521
00:28:15,800 --> 00:28:19,320
Speaker 3: the possibility space, trying to figure out what is going

522
00:28:19,359 --> 00:28:22,560
Speaker 3: on in this great, big cosmos that we're in. And

523
00:28:22,640 --> 00:28:27,080
Speaker 3: so the idea is, you know, to take a scientific

524
00:28:27,200 --> 00:28:30,719
Speaker 3: mindset to this question, which is to say, you know,

525
00:28:30,800 --> 00:28:34,200
Speaker 3: science always has a broad table and allows lots of

526
00:28:34,280 --> 00:28:37,920
Speaker 3: hypotheses on and says, okay, maybe this, maybe that cool.

527
00:28:37,920 --> 00:28:41,120
Speaker 3: I'll let anything on the table. But you know, we

528
00:28:41,280 --> 00:28:44,040
Speaker 3: use the tools of science to rule out parts of

529
00:28:44,040 --> 00:28:47,280
Speaker 3: the possibility space. So if you come and say, hey, look,

530
00:28:47,360 --> 00:28:49,000
Speaker 3: I think you know this thing is going on with

531
00:28:49,120 --> 00:28:51,959
Speaker 3: crystals or this or yesp or whatever, we can actually

532
00:28:52,000 --> 00:28:54,080
Speaker 3: test that and rule things out. And we and we

533
00:28:54,280 --> 00:28:55,880
Speaker 3: that's what we do all the time. There's lots of

534
00:28:55,920 --> 00:28:59,040
Speaker 3: stuff that's sort of off the table at this point.

535
00:28:59,600 --> 00:29:01,920
Speaker 3: For example, you know, if you were to say, like

536
00:29:02,040 --> 00:29:04,480
Speaker 3: you know, traditional religious books, hey the earth is six

537
00:29:04,520 --> 00:29:08,640
Speaker 3: thousand years old. You know that's a problem because you know,

538
00:29:09,040 --> 00:29:12,800
Speaker 3: the Japanese were, you know, making pottery six thousand years

539
00:29:12,840 --> 00:29:15,520
Speaker 3: before that, and so that can't be true. So we

540
00:29:16,040 --> 00:29:18,480
Speaker 3: can use the tools of science to open up new

541
00:29:18,520 --> 00:29:22,400
Speaker 3: folds in the possibility space and to rule things out.

542
00:29:22,720 --> 00:29:25,040
Speaker 3: But what it allows is a big space where we

543
00:29:25,080 --> 00:29:27,080
Speaker 3: can shine a flashlight around and say, all right, look,

544
00:29:27,160 --> 00:29:29,440
Speaker 3: we're not going to pretend that we know for sure

545
00:29:29,520 --> 00:29:33,560
Speaker 3: that nothing exists, or that this particular made up story exists. Instead,

546
00:29:33,600 --> 00:29:35,840
Speaker 3: we're going to explore. It's fascinating to me.

547
00:29:35,880 --> 00:29:37,920
Speaker 1: I imagine at some point in your life you run

548
00:29:37,960 --> 00:29:40,720
Speaker 1: across the varieties of religious experience.

549
00:29:41,080 --> 00:29:44,240
Speaker 3: The William James lechos, did you run under them? I

550
00:29:44,360 --> 00:29:45,880
Speaker 3: have not read that. I've heard of it.

551
00:29:46,520 --> 00:29:50,200
Speaker 1: Yeah, essentist because I'm kind of like claiming through it

552
00:29:50,320 --> 00:29:52,520
Speaker 1: right now for I don't know. I guess that's what

553
00:29:52,640 --> 00:29:56,160
Speaker 1: I do for entertainment. There was one of the lectures

554
00:29:56,160 --> 00:30:00,600
Speaker 1: he gave when he talks about that when people believe

555
00:30:00,640 --> 00:30:03,440
Speaker 1: something and it makes them feel good, then they are

556
00:30:03,520 --> 00:30:08,160
Speaker 1: convinced it's true. He's talking and I thought, that's fascinating

557
00:30:08,200 --> 00:30:09,800
Speaker 1: to me. I knew I was going to be talking

558
00:30:09,800 --> 00:30:12,120
Speaker 1: to you today as well, and I thought that that's

559
00:30:12,160 --> 00:30:16,920
Speaker 1: an interesting position to be in that the religious experience.

560
00:30:17,360 --> 00:30:23,000
Speaker 1: If something a ceremony, or a story, or a particular

561
00:30:23,200 --> 00:30:26,479
Speaker 1: piece of dogma gives you a sense of euphoria, is

562
00:30:26,520 --> 00:30:31,880
Speaker 1: euphoria something that breeds very similitude? Is it something that

563
00:30:31,920 --> 00:30:35,840
Speaker 1: you say, I feel good, therefore this must be true.

564
00:30:36,080 --> 00:30:38,680
Speaker 3: Yeah. I think there are lots of reasons why people

565
00:30:39,280 --> 00:30:43,800
Speaker 3: believe things about any religious story. One of them, of course,

566
00:30:43,920 --> 00:30:47,640
Speaker 3: is that often people don't apply real rigor in what

567
00:30:47,680 --> 00:30:50,120
Speaker 3: they call true or not true in the first place.

568
00:30:50,160 --> 00:30:52,760
Speaker 3: But secondly, there's a huge social component to this. If

569
00:30:52,760 --> 00:30:55,960
Speaker 3: your friends, your family, or loved ones go and they

570
00:30:56,000 --> 00:30:59,640
Speaker 3: pray to this deity at this situation, then people feel like, hey,

571
00:30:59,680 --> 00:31:03,800
Speaker 3: you know, that's something that is meaningful to me too.

572
00:31:04,360 --> 00:31:06,360
Speaker 3: So I think there are a lot of reasons why

573
00:31:06,400 --> 00:31:08,960
Speaker 3: people believe in things. One of them is that people,

574
00:31:09,240 --> 00:31:12,280
Speaker 3: you know, don't necessarily apply rigorous tools when they're deciding

575
00:31:12,280 --> 00:31:15,640
Speaker 3: what to believe or not. But more than that, there's

576
00:31:15,680 --> 00:31:19,680
Speaker 3: a huge social component to religion or faith of any sort,

577
00:31:19,680 --> 00:31:22,040
Speaker 3: which is to say, if your friends and loved ones

578
00:31:22,680 --> 00:31:25,200
Speaker 3: believe in a particular thing, we tend to be compelled

579
00:31:25,200 --> 00:31:27,440
Speaker 3: that way. And if you live in a place where

580
00:31:27,480 --> 00:31:31,520
Speaker 3: everyone around you believes whatever deity and whatever crazy thing.

581
00:31:31,840 --> 00:31:33,800
Speaker 3: Then you grow up that way and you think, of,

582
00:31:33,800 --> 00:31:35,480
Speaker 3: of course I must be true because these people that

583
00:31:35,520 --> 00:31:39,160
Speaker 3: I love and respect they believe that. So there are

584
00:31:39,200 --> 00:31:42,880
Speaker 3: many different things that compel people. And you know, maybe

585
00:31:42,920 --> 00:31:44,800
Speaker 3: someone says, Okay, I'm going to finally break from my

586
00:31:44,840 --> 00:31:48,720
Speaker 3: religion and they go to some other religion and whatever

587
00:31:48,760 --> 00:31:53,920
Speaker 3: they're you know, attractive people there, or a compelling narrator

588
00:31:53,920 --> 00:31:56,160
Speaker 3: who tells them something, and so they feel like, hey,

589
00:31:56,200 --> 00:31:58,440
Speaker 3: that fits with what I need in my life. That's

590
00:31:58,480 --> 00:32:01,600
Speaker 3: the message I need right now. But none of this, Yeah,

591
00:32:02,120 --> 00:32:05,320
Speaker 3: none of this qualifies as good reasons to believe. It's

592
00:32:05,360 --> 00:32:06,400
Speaker 3: just why people believe.

593
00:32:07,160 --> 00:32:10,480
Speaker 1: It's interesting though, because the only the ultimate measuring tool

594
00:32:10,520 --> 00:32:12,520
Speaker 1: that you have in front of you, or that you

595
00:32:12,600 --> 00:32:16,320
Speaker 1: have to use, is in fact your own perception and

596
00:32:16,360 --> 00:32:19,480
Speaker 1: the perception of your contemporaries. Right, So if you set

597
00:32:19,560 --> 00:32:23,760
Speaker 1: up even the most rigorous academic test, you're still looking

598
00:32:23,800 --> 00:32:26,040
Speaker 1: at it with your eyes and thinking about it with

599
00:32:26,200 --> 00:32:26,920
Speaker 1: your brain.

600
00:32:27,440 --> 00:32:29,280
Speaker 3: Don't I don't think so. I think that we can

601
00:32:29,320 --> 00:32:32,640
Speaker 3: actually use the tools of science really. So yeah, So,

602
00:32:33,680 --> 00:32:37,080
Speaker 3: for example, I mentioned the way that science opens up

603
00:32:37,120 --> 00:32:40,880
Speaker 3: new folds in the possibility space as we discover things,

604
00:32:41,240 --> 00:32:43,360
Speaker 3: for example, about the size of the I mean, look,

605
00:32:43,400 --> 00:32:46,280
Speaker 3: you know, poor you know, Galileo had to spend the

606
00:32:46,320 --> 00:32:49,800
Speaker 3: last part of his life imprisoned because he suggested that

607
00:32:49,880 --> 00:32:52,320
Speaker 3: maybe the Earth is going around the Sun and not

608
00:32:52,440 --> 00:32:54,920
Speaker 3: vice versa. But as we discover more and more about

609
00:32:54,920 --> 00:32:58,720
Speaker 3: the cosmos and understand the absolute enormity of it, and

610
00:32:59,160 --> 00:33:02,960
Speaker 3: that our galaxy has one hundred billion stars, any number

611
00:33:03,040 --> 00:33:05,320
Speaker 3: you know, any one of which has number of planets

612
00:33:05,360 --> 00:33:07,960
Speaker 3: rolling around it, and and our galaxy is one of

613
00:33:08,080 --> 00:33:11,840
Speaker 3: one hundred billion galaxies in the cosmos. And as we

614
00:33:11,960 --> 00:33:14,479
Speaker 3: as we understand these things, I think that opens us

615
00:33:14,560 --> 00:33:17,720
Speaker 3: up to a very different kind of faith, so that

616
00:33:17,720 --> 00:33:20,360
Speaker 3: we don't have to think about, Okay, my little local

617
00:33:20,400 --> 00:33:23,320
Speaker 3: deity can beat your local deity and so on. First

618
00:33:23,360 --> 00:33:25,560
Speaker 3: of all, science opens up these things. But then the

619
00:33:25,600 --> 00:33:28,240
Speaker 3: other thing I mention is that science rules things out,

620
00:33:29,760 --> 00:33:32,960
Speaker 3: you know, whether that's the age of the Earth or

621
00:33:33,000 --> 00:33:36,239
Speaker 3: the idea that you know, your deity, you know, did

622
00:33:36,680 --> 00:33:39,160
Speaker 3: some little things, some little magic trick, and you can

623
00:33:39,600 --> 00:33:43,280
Speaker 3: rule that stuff in or out. I think we probably

624
00:33:43,320 --> 00:33:46,600
Speaker 3: have a very different perspective on the world than we

625
00:33:46,680 --> 00:33:50,280
Speaker 3: did even three hundred years ago. When people consider it, Hey,

626
00:33:50,320 --> 00:33:53,880
Speaker 3: do I think this deity represents the truth? And and

627
00:33:53,880 --> 00:33:57,480
Speaker 3: and you know, for example, we're so global now that

628
00:33:57,560 --> 00:34:01,480
Speaker 3: we see there are two thousand religions on the planet,

629
00:34:01,920 --> 00:34:05,520
Speaker 3: and so it becomes harder to believe, Oh, the thing

630
00:34:05,520 --> 00:34:07,760
Speaker 3: that I grew up with has to be the right one,

631
00:34:07,760 --> 00:34:10,719
Speaker 3: because you now see that there are two thousand other

632
00:34:10,960 --> 00:34:14,320
Speaker 3: versions of this stuff. So anyway, all these things point

633
00:34:14,360 --> 00:34:17,560
Speaker 3: to as we become smarter as a society, I think

634
00:34:17,600 --> 00:34:22,480
Speaker 3: we can develop notions that maybe are more appropriate to

635
00:34:22,560 --> 00:34:31,879
Speaker 3: a deeper view along the lines of what you were saying.

636
00:34:31,920 --> 00:34:34,480
Speaker 1: I remember before my first kid was born, I said

637
00:34:35,000 --> 00:34:39,840
Speaker 1: to the obstetrician, how much do you actually know about

638
00:34:39,920 --> 00:34:43,760
Speaker 1: what pregnancy was going on in pregnancy? And she said,

639
00:34:44,160 --> 00:34:47,239
Speaker 1: if you'd ask me that question ten years ago, i'd

640
00:34:47,239 --> 00:34:51,880
Speaker 1: have said about fifty percent. But we've learned so much

641
00:34:52,480 --> 00:34:55,160
Speaker 1: that now I would say about twenty five percent.

642
00:34:55,920 --> 00:34:57,759
Speaker 3: Excellent, very good.

643
00:34:58,160 --> 00:35:01,720
Speaker 1: And I think that that that's a fascinating though, because

644
00:35:01,719 --> 00:35:07,040
Speaker 1: if you follow the logical, mathematical root of that, literally,

645
00:35:07,120 --> 00:35:08,960
Speaker 1: the more you know, the less you know.

646
00:35:09,560 --> 00:35:13,280
Speaker 3: Yeah, that's exact. I mean, there used to be people

647
00:35:13,360 --> 00:35:17,560
Speaker 3: called pansophists, which meant, you know, someone who knows everything

648
00:35:17,640 --> 00:35:20,280
Speaker 3: to be known. And you know, back in ancient Greece

649
00:35:21,200 --> 00:35:23,680
Speaker 3: it was plausible to have somebody who was a Panzifist,

650
00:35:23,719 --> 00:35:27,239
Speaker 3: and now it's totally impossible. It has been for centuries.

651
00:35:29,200 --> 00:35:32,160
Speaker 3: So you know, that's lovely. And what I love, by

652
00:35:32,200 --> 00:35:34,040
Speaker 3: the way, about this moment in time right now, is

653
00:35:34,080 --> 00:35:39,640
Speaker 3: we've got AI that has consumed you know, every single

654
00:35:39,680 --> 00:35:43,600
Speaker 3: thing ever written by humans, and so that provides a

655
00:35:43,640 --> 00:35:47,400
Speaker 3: whole new way of interacting and learning human kind's knowledge,

656
00:35:47,400 --> 00:35:49,880
Speaker 3: which is a sphere that is now much too large

657
00:35:49,880 --> 00:35:52,440
Speaker 3: for any of us to ever hope to even get into.

658
00:35:52,840 --> 00:35:55,480
Speaker 3: But what we can do is find some doorway that

659
00:35:55,560 --> 00:35:58,239
Speaker 3: interests us and enter the sphere that way, and by

660
00:35:58,320 --> 00:36:02,440
Speaker 3: talking to the AI just you know, learn all about

661
00:36:02,480 --> 00:36:04,879
Speaker 3: the world by asking questions that are relevant to us.

662
00:36:04,880 --> 00:36:06,560
Speaker 3: And I think this is going to really change our

663
00:36:06,680 --> 00:36:11,359
Speaker 3: educational systems for schooling, because right now, you know, kids

664
00:36:11,480 --> 00:36:13,919
Speaker 3: in classrooms, it's too fast for half the kids, too

665
00:36:13,920 --> 00:36:18,400
Speaker 3: slow for half the kids. But we can finally achieve

666
00:36:18,520 --> 00:36:24,600
Speaker 3: this dream of real individualized education where everyone you know

667
00:36:24,680 --> 00:36:27,000
Speaker 3: has an AI tutor, which is, by the way, how

668
00:36:27,000 --> 00:36:28,920
Speaker 3: it used to go. You know, Alexander the Great was

669
00:36:28,960 --> 00:36:31,960
Speaker 3: tutored by Aristotle, and you know you'd sit there and

670
00:36:32,120 --> 00:36:35,520
Speaker 3: have conversations. And I think we'll return to that. But

671
00:36:35,560 --> 00:36:38,160
Speaker 3: what that's I mean, that's fantastic for learning.

672
00:36:38,200 --> 00:36:40,919
Speaker 1: But I mean what we what we were, you're talking

673
00:36:40,960 --> 00:36:43,560
Speaker 1: about as well, even we were talking about religion. Is

674
00:36:43,600 --> 00:36:49,080
Speaker 1: that your religion or your propensity to certain depressions or

675
00:36:49,320 --> 00:36:50,040
Speaker 1: or or.

676
00:36:51,880 --> 00:36:53,040
Speaker 3: Different traumas.

677
00:36:53,080 --> 00:36:58,239
Speaker 1: All of that's to do with socialization and to have

678
00:36:58,400 --> 00:37:02,960
Speaker 1: an AI a certain point, I have to ask myself.

679
00:37:02,960 --> 00:37:04,680
Speaker 1: I mean, I'm just speaking.

680
00:37:04,719 --> 00:37:07,240
Speaker 3: I love that. What's the point if it just mimics

681
00:37:07,280 --> 00:37:09,480
Speaker 3: everything that we've already go. We've ready to go all that,

682
00:37:10,560 --> 00:37:12,880
Speaker 3: So okay, great. Those are two types of questions. So

683
00:37:12,920 --> 00:37:15,680
Speaker 3: as far as socialization, I think that's what school will become.

684
00:37:15,719 --> 00:37:20,120
Speaker 3: I think you know, you're exactly right that that's such

685
00:37:20,160 --> 00:37:22,920
Speaker 3: an important part of growing up. And this was the

686
00:37:23,800 --> 00:37:26,960
Speaker 3: terrible thing for parents about COVID is seeing your young

687
00:37:27,080 --> 00:37:30,200
Speaker 3: children having to stay home and not wrestling and rolling

688
00:37:30,200 --> 00:37:33,239
Speaker 3: around and jumping on trampolines with other kids. So we'll

689
00:37:33,239 --> 00:37:35,480
Speaker 3: always have that, but school will become more about that

690
00:37:35,800 --> 00:37:38,480
Speaker 3: and instead of having the teacher drone on to the kids.

691
00:37:38,480 --> 00:37:41,319
Speaker 3: It'll be you know, the kids put on headphones. Do that,

692
00:37:43,440 --> 00:37:47,360
Speaker 3: at least as it stands. Now, what humans are really

693
00:37:47,400 --> 00:37:55,160
Speaker 3: great at doing is creativity and also understanding which creative

694
00:37:55,239 --> 00:37:59,640
Speaker 3: moves matter. So, for example, I can say to the AI,

695
00:37:59,719 --> 00:38:03,840
Speaker 3: hate generate one hundred pictures of you know, Craig sitting

696
00:38:03,840 --> 00:38:07,040
Speaker 3: in an avocado chair holding a poodle, and it'll do that.

697
00:38:07,440 --> 00:38:10,840
Speaker 3: But it doesn't know which of those pictures are better

698
00:38:11,360 --> 00:38:13,680
Speaker 3: than another. But a human looks at and says, oh, Craig,

699
00:38:13,680 --> 00:38:15,359
Speaker 3: that's a really good one, and that one over these

700
00:38:15,600 --> 00:38:20,840
Speaker 3: staying over here or whatever. And so humans are actually necessary,

701
00:38:20,840 --> 00:38:23,560
Speaker 3: at least at the moment for doing this next step

702
00:38:23,560 --> 00:38:26,800
Speaker 3: for figuring out Okay, I can ask, I can query

703
00:38:26,840 --> 00:38:28,799
Speaker 3: the AI, but what do I do with that? What's

704
00:38:28,840 --> 00:38:32,719
Speaker 3: the next step. I'll give you a specific example science.

705
00:38:33,080 --> 00:38:38,239
Speaker 3: So AI can tell me incredible things like, hey, I

706
00:38:38,280 --> 00:38:40,840
Speaker 3: need to understand you know, these facts that are scattered

707
00:38:40,840 --> 00:38:44,080
Speaker 3: around all these different journal papers across fifty years. Give

708
00:38:44,080 --> 00:38:46,719
Speaker 3: me a summary of this. It's trivial for it to

709
00:38:46,760 --> 00:38:48,960
Speaker 3: do that, and that's super useful. But what it can't

710
00:38:49,040 --> 00:38:54,120
Speaker 3: do is generate new sorts of science in the way that.

711
00:38:54,200 --> 00:38:57,479
Speaker 3: Let's say Albert Einstein says, Okay, what if I were

712
00:38:57,880 --> 00:39:00,600
Speaker 3: writing on a photon of lightweight? What would that be

713
00:39:00,719 --> 00:39:02,360
Speaker 3: like if we were moving into speed of light? And

714
00:39:02,520 --> 00:39:04,520
Speaker 3: he thinks through that, he says, oh, and he comes

715
00:39:04,600 --> 00:39:07,840
Speaker 3: up with the special theory of relativity. That's progress. He

716
00:39:07,880 --> 00:39:09,680
Speaker 3: wants to know about prize for this sort of stuff.

717
00:39:10,000 --> 00:39:12,400
Speaker 3: That's the kind of things that at least at the moment,

718
00:39:12,800 --> 00:39:16,880
Speaker 3: AI does not do. So in answer your question, the

719
00:39:18,040 --> 00:39:21,680
Speaker 3: ultimate perfect thing is if we have AI co pilots

720
00:39:21,719 --> 00:39:24,960
Speaker 3: with us who can tell us lots of information, and

721
00:39:25,000 --> 00:39:29,880
Speaker 3: then we use our creativity and our extrapolation and simulation

722
00:39:29,960 --> 00:39:34,520
Speaker 3: of possible futures to put that together to make to

723
00:39:34,560 --> 00:39:37,000
Speaker 3: make something that's the next step for our civilization.

724
00:39:37,360 --> 00:39:41,480
Speaker 1: All right, So if that can happen, and let's imagine

725
00:39:41,480 --> 00:39:46,680
Speaker 1: that it can, is there a possibility the certain point,

726
00:39:46,840 --> 00:39:52,440
Speaker 1: if we can find the genetic and chemical recipe for

727
00:39:52,560 --> 00:39:58,840
Speaker 1: any individual's personality, that that can be I'm asking the

728
00:39:58,880 --> 00:40:02,680
Speaker 1: singularity question. Can you put the mind and the soul

729
00:40:02,800 --> 00:40:10,240
Speaker 1: of a cognizant, coherent santient being inside something which is digital?

730
00:40:10,719 --> 00:40:13,520
Speaker 3: Okay, so that's the question of can you upload your brain?

731
00:40:13,680 --> 00:40:16,719
Speaker 3: So you don't have to die. Here's how it would work.

732
00:40:16,800 --> 00:40:20,760
Speaker 3: It would work by taking a scan of your brain

733
00:40:21,239 --> 00:40:23,640
Speaker 3: at the kind of resolution that we can't even dream

734
00:40:23,760 --> 00:40:27,160
Speaker 3: of now. Right now with our very fancy brain imaging

735
00:40:27,200 --> 00:40:31,640
Speaker 3: what we call fMRI functional magnetic residence imaging is very crude. Okay,

736
00:40:31,960 --> 00:40:36,120
Speaker 3: but cut to one hundred years from now, our great

737
00:40:36,160 --> 00:40:39,160
Speaker 3: grand children are sitting around having a podcast with each other,

738
00:40:39,440 --> 00:40:42,399
Speaker 3: and the question is, could you scan a brain at

739
00:40:42,400 --> 00:40:44,879
Speaker 3: the resolution where you know every single neuron and all

740
00:40:44,880 --> 00:40:47,720
Speaker 3: the connections and perhaps everything going on inside the neuron

741
00:40:48,000 --> 00:40:51,560
Speaker 3: and reproduce that algorithm on a computer? The answer is

742
00:40:51,640 --> 00:40:54,560
Speaker 3: probably probably you could do that, and therefore you could

743
00:40:54,600 --> 00:40:59,759
Speaker 3: download it and run Craig or Craig's great grandchild such

744
00:40:59,840 --> 00:41:02,839
Speaker 3: that you really couldn't tell a difference. So I say

745
00:41:02,960 --> 00:41:06,120
Speaker 3: to the computer, Hey, Craig's great grandchild, are you in there?

746
00:41:06,440 --> 00:41:09,000
Speaker 3: And she says, yeah, I'm here, what's up? And you know,

747
00:41:09,040 --> 00:41:12,640
Speaker 3: we have a conversation that's fascinating to me.

748
00:41:12,800 --> 00:41:16,359
Speaker 1: So the idea that is, I mean, I wouldn't hold

749
00:41:16,400 --> 00:41:20,920
Speaker 1: you to it, but sort of theoretically, sort of kind

750
00:41:20,960 --> 00:41:22,120
Speaker 1: of maybe.

751
00:41:22,719 --> 00:41:27,279
Speaker 3: Oh, theoretically yes. And it's because as best we can

752
00:41:27,320 --> 00:41:30,959
Speaker 3: tell this is just a machine in here. It's the

753
00:41:31,000 --> 00:41:34,440
Speaker 3: most complex sophisticated thing that we have ever come across

754
00:41:34,480 --> 00:41:38,160
Speaker 3: in our universe, the human brain. But it's just a machine.

755
00:41:38,200 --> 00:41:41,360
Speaker 3: It's just built out of eighty six billion neurons and

756
00:41:41,400 --> 00:41:44,080
Speaker 3: about the same number of glial cells, and it's you know,

757
00:41:44,239 --> 00:41:46,520
Speaker 3: every neuron in your head is popping off the little

758
00:41:46,600 --> 00:41:51,760
Speaker 3: signals tends to hundreds of times per second, So it's

759
00:41:52,280 --> 00:41:55,799
Speaker 3: unbelievably complex. You've got something like two hundred trillion connections

760
00:41:55,840 --> 00:41:58,440
Speaker 3: between these neurons, and as I said, it's it's like

761
00:41:58,480 --> 00:42:02,000
Speaker 3: a forest that's re configuring with every experience that you have.

762
00:42:02,040 --> 00:42:05,080
Speaker 3: So it's unbelievably complex. But it's a machine. And so

763
00:42:05,160 --> 00:42:07,160
Speaker 3: there's no reason that we should not be able to

764
00:42:07,280 --> 00:42:11,000
Speaker 3: reproduce that on silicon or whatever I mean. In theory,

765
00:42:11,080 --> 00:42:13,920
Speaker 3: I could reproduce your brain out of beer cans and

766
00:42:13,960 --> 00:42:14,680
Speaker 3: tennis balls.

767
00:42:14,960 --> 00:42:18,839
Speaker 1: And if it's definitely yeah, I don't think you need

768
00:42:18,880 --> 00:42:19,560
Speaker 1: the tennis ball.

769
00:42:21,560 --> 00:42:25,560
Speaker 3: And if it's doing the same algorithm, then then it's you.

770
00:42:25,600 --> 00:42:27,560
Speaker 3: And if I say, hey, Craig, how you doing, you say, ah,

771
00:42:27,600 --> 00:42:31,560
Speaker 3: I'm a little hungry, whatever, But it's it's you. Because

772
00:42:31,600 --> 00:42:33,759
Speaker 3: all we are is you know, these vast machines. And

773
00:42:33,840 --> 00:42:35,200
Speaker 3: by the way, the reason we know that, I'm not

774
00:42:35,239 --> 00:42:36,920
Speaker 3: just saying this as an assertion. The reason we know

775
00:42:37,040 --> 00:42:41,239
Speaker 3: that is because of centuries of studying brain damage. If

776
00:42:41,239 --> 00:42:43,560
Speaker 3: you study even a very tiny bit of your brain

777
00:42:44,800 --> 00:42:47,879
Speaker 3: that completely changes that can change your personality or decision making,

778
00:42:47,920 --> 00:42:52,560
Speaker 3: your ability to recognize animals, or see colors, or hear music,

779
00:42:52,840 --> 00:42:55,160
Speaker 3: or you know a thousand other things that we see

780
00:42:55,200 --> 00:42:57,360
Speaker 3: in the clinics every day. And that's how we know

781
00:42:58,120 --> 00:43:00,759
Speaker 3: that you are the operation of your brain and when

782
00:43:00,800 --> 00:43:03,080
Speaker 3: little things change, that changes you. And by the way,

783
00:43:03,160 --> 00:43:06,560
Speaker 3: drugs and alcohol are just invisibly small molecules that get

784
00:43:06,600 --> 00:43:08,560
Speaker 3: in your blood stream and change the functioning of your

785
00:43:08,600 --> 00:43:13,719
Speaker 3: brain changes you. You know, when you sleep each night,

786
00:43:13,719 --> 00:43:15,640
Speaker 3: you go into deep sleep and then you're not even

787
00:43:15,640 --> 00:43:17,880
Speaker 3: there anymore, and then you know, when you wake up,

788
00:43:17,920 --> 00:43:20,080
Speaker 3: it sort of reboots the whole system and so on.

789
00:43:20,320 --> 00:43:22,719
Speaker 3: But the point is it's all happening in these three

790
00:43:22,800 --> 00:43:25,680
Speaker 3: pounds here. That is you. That is fascinating.

791
00:43:25,920 --> 00:43:30,760
Speaker 1: So I have to ask you personally, what does anything

792
00:43:30,920 --> 00:43:32,120
Speaker 1: frighten you about this?

793
00:43:33,520 --> 00:43:37,840
Speaker 6: I don't think so, I mean, just because what you're saying,

794
00:43:37,840 --> 00:43:39,759
Speaker 6: would I think what you're saying would frighten a lot

795
00:43:39,800 --> 00:43:45,760
Speaker 6: of people who are committed to different theological or psychological

796
00:43:45,960 --> 00:43:50,760
Speaker 6: or philosophical ideas, and you're and you're saying some stuff

797
00:43:50,800 --> 00:43:51,839
Speaker 6: that would challenge that.

798
00:43:51,920 --> 00:43:55,560
Speaker 3: I think from a scientific point of view, Yeah, I mean,

799
00:43:55,640 --> 00:43:58,160
Speaker 3: I guess I can't say that people have all kinds

800
00:43:58,160 --> 00:44:00,520
Speaker 3: of you know, with eight point three billion people on

801
00:44:00,560 --> 00:44:02,960
Speaker 3: the earth, there are that many views on the world.

802
00:44:03,040 --> 00:44:09,799
Speaker 3: So but this view, I would assert, is the only

803
00:44:09,840 --> 00:44:13,280
Speaker 3: one that's defensible. I mean, you could have whatever faith

804
00:44:13,360 --> 00:44:15,439
Speaker 3: you have, whatever deity you have, But if you walk

805
00:44:15,480 --> 00:44:18,240
Speaker 3: into a neurology ward and you see patients with different

806
00:44:18,280 --> 00:44:20,640
Speaker 3: brain damage and they have different things going on, I

807
00:44:20,640 --> 00:44:25,319
Speaker 3: don't know how one would explain that otherwise except to say, yeah,

808
00:44:25,680 --> 00:44:29,520
Speaker 3: you are your brain. I guess the part that frightens me,

809
00:44:29,880 --> 00:44:33,560
Speaker 3: But it's sort of a calm, mellow fright is just

810
00:44:33,920 --> 00:44:37,920
Speaker 3: how fragile we are as creatures. But everybody knows that anyway.

811
00:44:37,960 --> 00:44:41,080
Speaker 3: All it takes is a stroke, you know, a little

812
00:44:41,320 --> 00:44:44,480
Speaker 3: clot that gets in there, or traumatic brain injury or

813
00:44:44,520 --> 00:44:47,000
Speaker 3: a brain tumor or whatever, and then you're not even

814
00:44:47,040 --> 00:44:50,239
Speaker 3: you anymore. So I guess that part is frightening, but

815
00:44:50,320 --> 00:44:54,520
Speaker 3: I'm so used to thinking about that. Yeah, it's a

816
00:44:54,680 --> 00:44:56,440
Speaker 3: fascinating endlessly.

817
00:44:56,719 --> 00:44:58,719
Speaker 1: I think that must be one of the attractions of it,

818
00:44:58,800 --> 00:45:02,840
Speaker 1: surely is the fact that it it's endless. It's endless,

819
00:45:02,880 --> 00:45:06,080
Speaker 1: there's no there's no endpoint where you go, well, that's

820
00:45:06,120 --> 00:45:08,480
Speaker 1: the brain done, let's move on to the kidneys. It's

821
00:45:08,640 --> 00:45:12,640
Speaker 1: there's just not it's a long way to go.

822
00:45:13,960 --> 00:45:18,520
Speaker 3: Yeah, that's exactly right. And you know what's so cool

823
00:45:18,719 --> 00:45:21,600
Speaker 3: is so I've been in the field now, I wow,

824
00:45:21,920 --> 00:45:25,240
Speaker 3: well over a quarter century and the progress that I've seen.

825
00:45:25,600 --> 00:45:28,920
Speaker 3: But I would say exactly what the you know, what

826
00:45:28,960 --> 00:45:31,759
Speaker 3: the obstetricians said about pregnancy, I would say the same

827
00:45:31,800 --> 00:45:34,600
Speaker 3: thing about the brain, which is we we have so

828
00:45:34,760 --> 00:45:37,799
Speaker 3: much knowledge now we know less and less as a percentage.

829
00:45:38,719 --> 00:45:40,399
Speaker 3: You know, we have this book in the field called

830
00:45:40,440 --> 00:45:43,720
Speaker 3: Principles of Neuroscience, and it's enormous. It's about a thousand

831
00:45:43,800 --> 00:45:45,760
Speaker 3: pages long at this point, you know, it's the umpteenth

832
00:45:45,920 --> 00:45:48,760
Speaker 3: edition of this of this book. But what's very funny

833
00:45:48,760 --> 00:45:51,160
Speaker 3: about it is it keeps growing longer with each edition.

834
00:45:51,680 --> 00:45:54,520
Speaker 3: And it's not principles, because if it were principles, it

835
00:45:54,520 --> 00:45:58,160
Speaker 3: would be like a pamphlet, But instead, as we get

836
00:45:58,239 --> 00:46:00,919
Speaker 3: more and more data, we just keeping stuff in there.

837
00:46:01,000 --> 00:46:02,640
Speaker 3: We say, oh, well, but there's also this, and there's

838
00:46:02,680 --> 00:46:04,360
Speaker 3: that in these kind of cells and that kind of genes.

839
00:46:04,719 --> 00:46:07,400
Speaker 3: And what it demonstrates is we don't have the principles

840
00:46:07,480 --> 00:46:11,200
Speaker 3: yet that allow us to have some sort of compression

841
00:46:11,320 --> 00:46:11,680
Speaker 3: of this.

842
00:46:12,560 --> 00:46:14,640
Speaker 1: Does it have an effect on you and your personal level?

843
00:46:14,719 --> 00:46:18,120
Speaker 1: Do you drink alcohol? Do you? Do you take drugs?

844
00:46:18,160 --> 00:46:20,880
Speaker 3: Do you? I mean you don't have to in a

845
00:46:20,960 --> 00:46:23,520
Speaker 3: vague way? Do you know? No, I don't do any

846
00:46:23,560 --> 00:46:29,120
Speaker 3: of that. Actually. Is that because of brain damage? Yeah? Yeah, no,

847
00:46:29,200 --> 00:46:32,719
Speaker 3: I think right. I think it's because I'm sort of

848
00:46:32,719 --> 00:46:34,840
Speaker 3: a control freak about my brain. I just want to

849
00:46:34,920 --> 00:46:37,200
Speaker 3: keep this as healthy as I can. Yeah, so I

850
00:46:37,200 --> 00:46:39,400
Speaker 3: don't do any of that. I'm the last guy in

851
00:46:39,440 --> 00:46:42,680
Speaker 3: Silicon Valley that hasn't done psychedelics and had interesting trips

852
00:46:42,680 --> 00:46:45,480
Speaker 3: and souf and everyone asks me about that around here,

853
00:46:46,600 --> 00:46:48,960
Speaker 3: but I, yeah, I just I haven't taken it. It's

854
00:46:49,000 --> 00:46:51,600
Speaker 3: probably it's probably so low risk to do that, but

855
00:46:51,680 --> 00:46:58,239
Speaker 3: I just maybe that's a fear. Is the my consciousness

856
00:46:58,280 --> 00:47:00,640
Speaker 3: is a very particular thing, and I know that if

857
00:47:00,680 --> 00:47:04,440
Speaker 3: I stick in these invisibly small molecules. It'll change the

858
00:47:05,719 --> 00:47:08,840
Speaker 3: you know, the receptors or whatever. It'll change the activity

859
00:47:09,120 --> 00:47:12,480
Speaker 3: just a few percentage, and I'll be talking to silver leprechauns.

860
00:47:13,120 --> 00:47:15,200
Speaker 3: But I don't. I don't want to change that. I

861
00:47:15,200 --> 00:47:18,319
Speaker 3: don't want to mess up the system because this is

862
00:47:18,360 --> 00:47:22,279
Speaker 3: all I've got. And what about physical health do you?

863
00:47:22,520 --> 00:47:24,959
Speaker 1: I mean it kind of obviously your body feeds your brain,

864
00:47:25,080 --> 00:47:28,680
Speaker 1: I mean everything. So I mean do you find yourself

865
00:47:29,640 --> 00:47:34,720
Speaker 1: avoiding certain foods or or avoid in certain activities.

866
00:47:34,320 --> 00:47:37,799
Speaker 3: Or or yeah? We basically that I keep in really

867
00:47:37,800 --> 00:47:42,680
Speaker 3: good shape and I I eat healthfully. Yeah, I just

868
00:47:42,760 --> 00:47:45,400
Speaker 3: I try to make sure that I'm optimizing everything I

869
00:47:45,440 --> 00:47:46,360
Speaker 3: can on that front.

870
00:47:47,040 --> 00:47:48,759
Speaker 1: You are you hyper aware of it? Like if you

871
00:47:48,760 --> 00:47:51,680
Speaker 1: eat if you eat some sugar, do you do you

872
00:47:51,719 --> 00:47:52,080
Speaker 1: feel it?

873
00:47:52,120 --> 00:47:54,400
Speaker 3: Do you know what it's doing? Yeah? I know what

874
00:47:54,440 --> 00:47:58,359
Speaker 3: it's doing. I we let's see. I don't think I'm

875
00:47:58,400 --> 00:48:01,239
Speaker 3: hyper aware of it. But I I'm not even attracted

876
00:48:01,280 --> 00:48:04,840
Speaker 3: to sugary things. I don't even like that. But I

877
00:48:04,920 --> 00:48:07,160
Speaker 3: think I would say anymore. Obviously when I was a child,

878
00:48:07,200 --> 00:48:10,280
Speaker 3: I did. But the more the more I care about

879
00:48:10,280 --> 00:48:12,920
Speaker 3: optimizing the whole system, the less I'm even interested in

880
00:48:12,920 --> 00:48:14,600
Speaker 3: those sorts of things.

881
00:48:14,800 --> 00:48:18,400
Speaker 1: Let's very quickly, because I've been taken up an enormous

882
00:48:18,520 --> 00:48:19,000
Speaker 1: of your time.

883
00:48:19,040 --> 00:48:20,080
Speaker 3: But I'm fascinated by this.

884
00:48:20,480 --> 00:48:23,719
Speaker 1: What does because sugar is a thing for me, What

885
00:48:23,800 --> 00:48:26,360
Speaker 1: does sugar do in your brain?

886
00:48:27,440 --> 00:48:31,360
Speaker 3: Well, you know, so you increase blood sugar in your body,

887
00:48:31,400 --> 00:48:33,880
Speaker 3: and there are all kinds of bad effects that that

888
00:48:34,000 --> 00:48:38,239
Speaker 3: can have just physically in the brain. It's actually not

889
00:48:38,320 --> 00:48:40,920
Speaker 3: a bad thing because it's it's an energy source. It's

890
00:48:40,920 --> 00:48:43,279
Speaker 3: a quick energy source. So you know, if you're if

891
00:48:43,280 --> 00:48:45,239
Speaker 3: you're really tired and you need to do something, it's

892
00:48:45,239 --> 00:48:48,800
Speaker 3: probably it's probably not a bad idea. But the rest

893
00:48:48,840 --> 00:48:51,040
Speaker 3: of the body it reeks happy with time.

894
00:48:51,280 --> 00:48:55,240
Speaker 1: Yeah, it's well, it's a it's a fascinating thing, David.

895
00:48:55,360 --> 00:48:58,160
Speaker 1: And and thank you for being so patient with me,

896
00:48:58,160 --> 00:49:01,560
Speaker 1: because I really do know nothing about this, but I

897
00:49:01,560 --> 00:49:03,480
Speaker 1: feel like I know a little more another And now

898
00:49:03,520 --> 00:49:05,560
Speaker 1: that I know a little more, I really know how

899
00:49:05,640 --> 00:49:06,160
Speaker 1: little I.

900
00:49:06,160 --> 00:49:10,520
Speaker 3: Know about what I was talking about. But it's a

901
00:49:10,560 --> 00:49:11,360
Speaker 3: fascinating subject.

902
00:49:11,560 --> 00:49:13,000
Speaker 1: And I hope you'll come back and talk to us

903
00:49:13,040 --> 00:49:18,720
Speaker 1: again because it's it really is an endlessly interesting piece

904
00:49:18,760 --> 00:49:22,040
Speaker 1: of the world that you're involved in. Great, probably the

905
00:49:22,040 --> 00:49:25,839
Speaker 1: most important piece, I guess, I kind of think so.

906
00:49:25,920 --> 00:49:27,680
Speaker 3: I mean, it is the center of who we are.

907
00:49:27,760 --> 00:49:31,320
Speaker 3: There's really if you want to understand something about the self,

908
00:49:31,400 --> 00:49:34,080
Speaker 3: one can take you know, spiritual classes, psychology class and

909
00:49:34,080 --> 00:49:37,040
Speaker 3: stuff like that, and those are probably good inroads, but fundamentally,

910
00:49:37,560 --> 00:49:40,840
Speaker 3: this is the perceptual machinery by which you view the

911
00:49:40,880 --> 00:49:44,680
Speaker 3: whole world. So this is probably the best inroad there

912
00:49:44,719 --> 00:49:47,080
Speaker 3: is to understand what the what the heck we're doing here,

913
00:49:47,200 --> 00:49:49,319
Speaker 3: what your perception of the world is, and why you

914
00:49:49,360 --> 00:49:51,360
Speaker 3: react the way you do, why you have the feelings

915
00:49:51,440 --> 00:49:53,319
Speaker 3: and emotions you do, while you think the way you do,

916
00:49:53,440 --> 00:49:57,200
Speaker 3: and so on, and by the way, you know, you know,

917
00:49:57,280 --> 00:50:00,120
Speaker 3: I think. I've got this podcast called Inner Cosmos, and

918
00:50:00,200 --> 00:50:02,359
Speaker 3: what I do is every week I talk about this

919
00:50:02,440 --> 00:50:07,680
Speaker 3: intersection between the brain and daily life and why we

920
00:50:07,920 --> 00:50:09,319
Speaker 3: experience the world the way we do.

921
00:50:10,120 --> 00:50:13,439
Speaker 1: It is a fascinating idea, and I will watch your

922
00:50:13,480 --> 00:50:17,359
Speaker 1: Inner Cosmos and listen to your inner cosmos and investigate

923
00:50:17,400 --> 00:50:19,120
Speaker 1: your inner cosmos.

924
00:50:19,560 --> 00:50:21,239
Speaker 3: And see if it can help me. By I am

925
00:50:21,239 --> 00:50:23,279
Speaker 3: fascinated by it, and it really is great. David, Thank

926
00:50:23,280 --> 00:50:25,520
Speaker 3: you so much for being around great. Thanks Greig it's

927
00:50:25,520 --> 00:50:28,880
Speaker 3: such a pleasure to be here. Thanks buddy,