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Speaker 1: Hey, jorgey, do you think science is good at predicting

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Speaker 1: the future. It doesn't do very well with predicting the weather,

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Speaker 1: does it well? Here in California just says sunny every day? Yeah?

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Speaker 1: I guess some states are easier to predict the better.

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Speaker 1: All right, but let me try my hand at it.

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Speaker 1: I have a prediction of the future. You're a psychic,

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Speaker 1: note and a physicist. Well, I predict that you cannot

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Speaker 1: go a whole episode without talking about bananas. What that's bananas? Boom,

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Speaker 1: there you go. I'm totally psychic. You know the difference

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Speaker 1: between a psychic and a physicist their salary where you

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Speaker 1: put the h That's the only difference. Hey, I'm RhE

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Speaker 1: and my cartoonist and the creator of PhD comments. Hi.

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Speaker 1: I'm Daniel. I'm a particle physicist, not a particle psychic,

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Speaker 1: and I'm a co author of our book We Have

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Speaker 1: No Idea, A Guide to the Unknown Universe. Welcome to

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Speaker 1: our podcast, Daniel and Jorge Explain the Universe, a production

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Speaker 1: of I Heart Radio, in which we talk about all

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Speaker 1: the amazing, the fascinating, the hot, the nasty, the wet,

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Speaker 1: the bright, the dirty, the soft, the quiet, the loud,

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Speaker 1: the hot, the cold, all the stuff in the universe

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Speaker 1: that's fascinating and beautiful and amazing, and explain it to

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Speaker 1: you in a way that we hope you actually understand

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Speaker 1: and hopefully even enjoy. Yeah, and sometimes on the podcast,

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Speaker 1: we like to talk about predicting the future. What's gonna happen,

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Speaker 1: what's gonna happen to the universe, what's going to happen

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Speaker 1: to the Earth, what's gonna happen to the solar system,

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Speaker 1: what's going to happen to this podcast? Where is this

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Speaker 1: podcast going anyway? Yeah, we like to talk about what

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Speaker 1: science does and doesn't know about the future, what we

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Speaker 1: can predict about what's going to happen, and where we

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Speaker 1: are totally clueless. Yeah, well, as I was we were

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Speaker 1: saying earlier, there's a there's a fine line between being

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Speaker 1: a psychic and being a physicist. I would say it's

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Speaker 1: a bright but fine line. It's right, Okay, it's an

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Speaker 1: impenetrable barrier, quantum barrier. It's difficult to tunnel between being

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Speaker 1: a physicist and being a psychic, but in some sense

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Speaker 1: we do have the same job. Physics also wants to

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Speaker 1: predict the future. Yeah, that's kind of. I mean, that's

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Speaker 1: kind of why, in a way, physics was invented, right,

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Speaker 1: Like we want to know where this catapult payload is

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Speaker 1: going to land. We want to know how far my

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Speaker 1: car is going to go? Were you there when physics

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Speaker 1: was invented? I didn't get invited to that meeting? Oh yeah,

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Speaker 1: and you didn't? Um? I think Einstein was there and

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Speaker 1: Newton was there, and damn I knew I should have

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Speaker 1: checked my email that day. He missed the calendar invite.

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Speaker 1: That's right, And all those exams, as you mentioned, are

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Speaker 1: totally valuable and our examples of why science has an

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Speaker 1: impact on everyday life. You know, is my catapult going

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Speaker 1: to get over those castle walls and this kind of stuff?

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Speaker 1: But also physics just wants to understand what's going to

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Speaker 1: happen to us, what's our fate? How can we plan

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Speaker 1: to live ahead? Um? And can we understand the mysteries

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Speaker 1: of everything around us so that we can know when

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Speaker 1: lightning is going to strike or when disease is going

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Speaker 1: to wipe out our cattle? Right? In a way, that's

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Speaker 1: kind of the the standard for physics, right. It's like

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Speaker 1: like we we we say we understand something in a

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Speaker 1: way we can sort of predict what's going to happen.

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Speaker 1: You want to verify that your theory of physics describes

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Speaker 1: the real universe out there and not just some idea

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Speaker 1: in your mind. You have to make a testable prediction. Einstein,

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Speaker 1: for example, predicted how light was going to be bent

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Speaker 1: during an eclipse, and people measured it and he was right.

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Speaker 1: And that's really when people started to believe his theory

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Speaker 1: of relativity. Because if your theory can't predict the future,

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Speaker 1: then what uses it, Right, That's what science does. It

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Speaker 1: predicts the outcome of future elements. Yeah, and you know,

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Speaker 1: I think people are comfortable with this idea that physics

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Speaker 1: is able to some degree predict the future. Like if

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Speaker 1: if you told somebody, hey, physics predict that the Earth

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Speaker 1: is going to be around for a very long time,

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Speaker 1: or that the universe will never end that those are comforting,

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Speaker 1: or if you eat that candy you will get bad. Yeah,

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Speaker 1: I think that's a that's more of a physical education. Um,

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Speaker 1: there's physics there. You're converting candy energy into squishy stomach energy. Yeah.

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Speaker 1: So we're comfortable I think with some physics predicting some

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Speaker 1: things about the future. But I think we're a little

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Speaker 1: bit uncomfortable about physics describing other things about the future, right. Yeah.

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Speaker 1: We like to use physics and science to explore the

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Speaker 1: universe around us and outside us. But then sometimes we

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Speaker 1: turn that science on ourselves and we seek to gain

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Speaker 1: insight into how we work. And then that makes you wonder. Yeah,

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Speaker 1: it makes you wonder if you are predictable in a

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Speaker 1: way you know, like could physics but actually one day,

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Speaker 1: you know, simulate the human mind, or simulate your mind

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Speaker 1: and predict what you're gonna think and do. It's a

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Speaker 1: fascinating question because so many things that humans have puzzled

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Speaker 1: over for so many years, how eclipse has happened, where

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Speaker 1: lightning strikes, all this stuff, how reproduction works. All of

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Speaker 1: these things have in the end been explained through science.

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Speaker 1: It turns out they are mechanistic. We can understand the

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Speaker 1: microscopically how it works and predict what's going to happen

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Speaker 1: in the future. And so then it's a natural question

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Speaker 1: to wonder how far you can extend that strategy. Can

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Speaker 1: you turn that around and extend it into your own

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Speaker 1: inner life? Right yeah, because you know, like if physics

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Speaker 1: can predict what, uh, you know a can of gas

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Speaker 1: particles is going to do. Why can't it predict what

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Speaker 1: a brain full of neurons is going to do? What's

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Speaker 1: the difference in the end between a can of gas

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Speaker 1: and a brain of neurons Really depends on the person probably,

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Speaker 1: but it depends on what that person eight recently. Yeah,

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Speaker 1: So it's a big question with I think some really

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Speaker 1: deep philosophical implications right about who we are and whether

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Speaker 1: or not we're predictable, or whether or not we have

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Speaker 1: this thing called free will. Yeah, that's right. Like many

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Speaker 1: of the topics we touch on in this podcast, there

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Speaker 1: are deep philosophical implications, and so I think today we

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Speaker 1: should walk carefully and focus on the science and then

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Speaker 1: think about what the philosophical implications are of what we

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Speaker 1: do and do not know. Yeah, and so today on

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Speaker 1: the podcast, we'll be tackling the question can't science predict

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Speaker 1: what you're going to do? And I predict that there

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Speaker 1: will be a lot of predictions in this episode, but

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Speaker 1: maybe not a lot of answers. Well that's sort of

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Speaker 1: our specialty, right, opening questions and not really answering that.

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Speaker 1: I think what you mean is getting people excited about

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Speaker 1: the questions, right, and that's right, sparking people's fundamental curiosity.

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Speaker 1: I think it's I think it's wonderful to talk about

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Speaker 1: things that we don't understand very well, because hopefully it's

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Speaker 1: a preview for what's going to happen in the future.

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Speaker 1: It's like a fantasy for future science. Maybe in five

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Speaker 1: years or in a thousand years, Signs will have figured

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Speaker 1: out the exact workings of the human brain. It can

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Speaker 1: tell you exactly what you're gonna do tomorrow. That would

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Speaker 1: be amazing. We totally change the way life operates, the

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Speaker 1: way what it's like to be a human being, right, Yeah,

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Speaker 1: I mean, we wrote a whole book about all the

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Speaker 1: things we don't know, Daniel, I'm sure we can pull

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Speaker 1: off a podcast also, I predict we will. So. Yeah.

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Speaker 1: So this is an interesting question, and it's kind of

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Speaker 1: goes back to a long time ago, when you know,

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Speaker 1: once Signs started seeing that the universe was what they

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Speaker 1: called deterministic, meaning like like just the giant machine that

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Speaker 1: follows the laws of physics like a clock. Then I

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Speaker 1: think that's when people started to think, like, hey, maybe

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Speaker 1: maybe our humanity is also predictable like a clock. Yeah.

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Speaker 1: I think that's sort of shocking. I think when people

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Speaker 1: first had that idea, it might have been a terrifying

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Speaker 1: moment to imagine that this experience they're having might actually

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Speaker 1: just be explainable, that things could be determined from the past. Yeah. Well,

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Speaker 1: I think if you told my eleven year old self

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Speaker 1: that I was a robot, I'd be like cool. Nowadays, though,

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Speaker 1: you know, it's more of an uncomfortable statement. You're a

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Speaker 1: robot and we gave the remote control to your sister. Sorry. Yeah, no.

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Speaker 1: I think also it's fun to think even more deeply

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Speaker 1: into sort of the origins of human thought on this question.

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Speaker 1: Is the sort of the hubrist that the universe is

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Speaker 1: explainable at any level? You know, I think a thousand

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Speaker 1: years ago or five thousand years ago, people might have

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Speaker 1: been comfortable with the idea that the universe doesn't follow laws,

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Speaker 1: it just sort of is, and maybe there are these

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Speaker 1: omniscient sentient beings out there that are in control of

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Speaker 1: stuff and they can do whatever they like. So the

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Speaker 1: idea that the universe that we could write down rules,

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Speaker 1: we could discover rules that the universe follows and use

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Speaker 1: those to predict what's going to happen. That's an incredible

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Speaker 1: step forward in human intellectual history. But also it's not

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Speaker 1: something we can necessarily explain, like why would the universe

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Speaker 1: be deterministic? Why would the universe even follow laws? Is

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Speaker 1: it true even today, given our amazing success in science,

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Speaker 1: is it true that everything we can discover, Um, every

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Speaker 1: natural phenomena we discover will eventually be explained by science

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Speaker 1: or can be explained by science. Those are open questions

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Speaker 1: in philosophy. Yeah, and so I guess the question then is,

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Speaker 1: you know how far can we push science? Like if

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Speaker 1: science can predict the future to some degree, like you know,

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Speaker 1: I can predict that the airplane is not going to

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Speaker 1: fall from the sky, or it's going to predict that, Um,

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Speaker 1: you know, if I shoot this laser, this is what's

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Speaker 1: gonna happen. You know, how far can we push the

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Speaker 1: science and maybe even predict what your brain is going

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Speaker 1: to do? Fascinating questions. And I think you'll see from

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Speaker 1: some of these reactions that there's a wide variety of

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Speaker 1: opinions out there. So, as usual, I walked around campus

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Speaker 1: at you see Irvine, and I asked folks this question,

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Speaker 1: can science predict what you're going to think or do?

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Speaker 1: So think about it for a second. Do you think

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Speaker 1: you're just a big, squeehy biological robot machine or do

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Speaker 1: you think you have some sort of free will or

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Speaker 1: some sort of free spirit that nobody can predict what

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Speaker 1: you're going to think or do. Here's what people have

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Speaker 1: to say, not precisely to an extent. There's just so

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Speaker 1: many variables. No, no, not um, because we're humans are unpredictable.

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Speaker 1: I'm a psychology aager. So yeah, I don't believe that

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Speaker 1: we can. We can try, but it's not likely. Yeah,

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Speaker 1: I think so, you think so? Yeah, So then is

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Speaker 1: their free will in that case? Yeah, because it's still

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Speaker 1: the person that'slf, that's stims, just the other person that's

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Speaker 1: from the predicting correctly, So it's not their choice theoretically.

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Speaker 1: I mean, if we did have these capabilities, then that

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Speaker 1: might be possible. We just need to advance. Science is

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Speaker 1: far enough to able to figure that out. No, I don't.

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Speaker 1: I don't think so. So do you think the brain

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Speaker 1: is like not described by physical laws or does something

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Speaker 1: else happening there? No? I think, UM, strong determinism I

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Speaker 1: think is a very uh optimistic Yeah you do. Why

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Speaker 1: is that? Um? I don't know. I just feel like

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Speaker 1: it could, and if it does, does that mean that

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Speaker 1: you have free will or don't have free will? Or um?

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Speaker 1: If you can predict what people are going to think,

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Speaker 1: then probably not. Yes, yes, Why is that? I don't know.

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Speaker 1: I think I saw like a video where they're like

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Speaker 1: trying to map out like a brain or something, and

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Speaker 1: they were talking about like how to recreate it, and

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Speaker 1: that everything we think is just like a series of decisions,

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Speaker 1: and that you can put it in like binary or something,

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Speaker 1: so like zero for yes or one for no, and

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Speaker 1: it all leads to what choices you make. I think

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Speaker 1: that if there were a method for it, it wouldn't

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Speaker 1: be super exact, just because there were so many Does

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Speaker 1: that play into it. I don't think it's possible to

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Speaker 1: be able to predict every single one of them. Yes, yes, um,

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Speaker 1: oh no, no No. So you don't think the brain

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Speaker 1: follows physical laws. I think it does, but I think

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Speaker 1: they're chaotic, chaotic or random. I've given enough information. Are

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Speaker 1: you just a complicated mechanical watch? Uh? No. I think

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Speaker 1: I may or may not subscribe to the view that

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Speaker 1: there's some quantum mechanics at play. So maybe you're not

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Speaker 1: seating quantum mechanics because it's an opening for free will.

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Speaker 1: M M. Now, I don't know if that's true. I'm

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Speaker 1: I'm a pessimist. I feel like eventually, yes, but I

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Speaker 1: feel like we're not there yet. So if so, does

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Speaker 1: that mean that your brain is deterministic but you're just

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Speaker 1: just a product of what's happened in the past and

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Speaker 1: the stimulus it's getting. Obviously there's like some varying factories,

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Speaker 1: but I think there are some things that are like patternistic,

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Speaker 1: like if you're gonna wake up in like drink a coffee,

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Speaker 1: or if you're gonna wake up and like go for

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Speaker 1: a walk, Like those things are patterns that like are habitual.

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Speaker 1: But then there's things that aren't. I feel like you

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Speaker 1: could predict it to an extent, but not like every

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Speaker 1: single action by action, like there might be like faults

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Speaker 1: in the prediction. But yeah, it's hard to do because

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Speaker 1: it's impossible. Just I feel like that's probably impossible because

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Speaker 1: your things can change, you know, very complicated robot. Does

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Speaker 1: that mean that there's no free will? I currently thinking

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Speaker 1: that there's no free will. Yes, Yeah, So maybe that's

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Speaker 1: where it becomes a bit complicated to answer this question,

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Speaker 1: because I do believe that the laws of physics govern

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Speaker 1: everything in the universe, so that would include us, all right.

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Speaker 1: I feel like these answers were all very yes and no.

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Speaker 1: You know, some people were like no, some people are

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Speaker 1: like yes. Nobody said like maybe, I don't know, you know,

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Speaker 1: like people had very opinions. They certainly did, and I

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Speaker 1: should have taken some data to see if these were

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Speaker 1: like all science majors who had confidence as science would

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Speaker 1: eventually figure it out or not. But the last two

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Speaker 1: were maybe the most fun because they turned out to

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Speaker 1: be a husband and wife and he said, yes, he's

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Speaker 1: a complicated robot and she says, no, we're not robots.

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Speaker 1: And then after I left, I heard them arguing about

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Speaker 1: it in a good natured way. In a good natured way, Oh,

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Speaker 1: I see one of them. One of them thought that

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Speaker 1: the other one was predictable and the other one did

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Speaker 1: not like to be predicted. Yeah. I thought that was fascinating.

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Speaker 1: Maybe sparked some dinner table conversation. But you're right, and

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Speaker 1: and in contrast to some other questions, this is definitely

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Speaker 1: a topic everybody felt comfortable giving an answer to. Sometimes

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Speaker 1: I'll ask people a question and they'll be like, what,

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Speaker 1: I never heard of that before or I don't know,

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Speaker 1: but here everybody had something thoughtful to say. Yeah, because

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Speaker 1: I think it touches something very deep within us, you know,

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Speaker 1: just this idea that there's something more to me than

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Speaker 1: just like a big biological clock or a big biological

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Speaker 1: you know, clump of cells doing what there would do

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Speaker 1: without thinking about it. Yeah, I think most people feel

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Speaker 1: like they are steering, even if your body is a

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Speaker 1: big biological robot. They feel like they're in charge. They're

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Speaker 1: making choices. They decide to eat that cookie, or they

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Speaker 1: decide to step on that crack. They feel like they're

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Speaker 1: making these decisions and so so and so. It doesn't

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Speaker 1: sort of jibe with that experience to imagine that those

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Speaker 1: decisions are just the product of the situation you're in

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Speaker 1: an instant before. It's hard to imagine how you could

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Speaker 1: have such a visceral experience of free will if you

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Speaker 1: don't actually have it. All right, so let's stick into

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Speaker 1: the question. Here is the question here, which is a

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Speaker 1: cook science predict what you're going to do. And so

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Speaker 1: let's maybe paint the picture to our listeners about what

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Speaker 1: that might look like. You know, like, how could science,

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Speaker 1: physics or you know, a combination of biology and computer

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Speaker 1: science possibly predict what a human brain might think or do. YEA. So,

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Speaker 1: the typical raggy for understanding something is to think about

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Speaker 1: it in terms of its microscopic bits, like what's going

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Speaker 1: on inside of it? Can we understand those bits and

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Speaker 1: from that build up some sort of understanding, you know,

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Speaker 1: like if you wanted to say understand how a watch worked,

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Speaker 1: you would take it apart and you would say, oh,

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Speaker 1: there's a gear here, and there's a lever there, and

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Speaker 1: this lever touches that gear which turns this thing, and

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Speaker 1: that's how this thing works. And if you can make

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Speaker 1: a model of all the things inside of it, and

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Speaker 1: each one of those things is following the laws of physics,

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Speaker 1: then together the whole thing has to follow the laws

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Speaker 1: of physics. Right. If something is made up of pieces

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Speaker 1: which are predictable, then putting them together it should also

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Speaker 1: be predictable, right you mean like a so science would

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Speaker 1: might be maybe break down your brain and maybe build

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Speaker 1: like a computer model of each one of your neurons

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Speaker 1: and that somehow, you know, acts exactly the same way

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Speaker 1: that is put together the exact same way that your

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Speaker 1: brain is. And so maybe like if you capture your

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Speaker 1: brain in a computer, could that maybe predict what you're thinking,

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Speaker 1: what you'll think and do. Yeah, And it doesn't have

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Speaker 1: to be a computer model in the end, it just

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Speaker 1: has to follow the mathematical laws of physics, and you

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Speaker 1: can express those as a computer model. You could also

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Speaker 1: build a mechanical model. You can imagine building a basically

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Speaker 1: a physical copy of your brain. So that's I think, uh,

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Speaker 1: that detail is not critical the concept. The critical concept

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Speaker 1: is understanding what's going on inside the little bits and

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Speaker 1: then build putting those together to basically replicate your brain.

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Speaker 1: But replicating is not enough. Like if I had a

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Speaker 1: perfect copy of your brain, Like if I created another Hooge,

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Speaker 1: that wouldn't necessarily help me understand what you're going to do.

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Speaker 1: In order to in order to predict what you're gonna do,

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Speaker 1: I need to be able to run experiments. And so

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Speaker 1: you're having a simulation of your brain. I could like say, well,

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Speaker 1: what would Hooge do if I offered him a cookie?

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Speaker 1: Would he say yes or no? So if I had

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Speaker 1: a perfect simulation of your brain, I could run those experiments, right, Yeah,

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Speaker 1: I think it goes to the idea that you know

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Speaker 1: we're really complicated as human beings, as thinking beings. But

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Speaker 1: you know, if you break down our brain, it's made

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Speaker 1: out of you know, lobes and chunks of brain tissue,

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Speaker 1: and those are made out of neurons connected to each other,

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Speaker 1: and neurons are made out of molecules, and so all

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Speaker 1: of these things down to the molecule level kind of

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Speaker 1: follow the laws of physics. You know. It is sort

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Speaker 1: of at the end, just a big and very very complicated,

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Speaker 1: but still a big clock. Yes. And that's a really

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Speaker 1: deeply powerful implication of this discovery that we made a

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Speaker 1: long long time ago, that everything is made out of

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Speaker 1: the same bits. Right, I'm made out of atoms. You're

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Speaker 1: made out of atoms. This chair I'm sitting on is

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Speaker 1: made out of atoms. Things are not made out of

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Speaker 1: their own kind of stuff, which means that they in

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Speaker 1: the end, they all follow the same rules. The rules

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Speaker 1: that hold a chair together are the same rules that

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Speaker 1: hold your cat together, and your hamster together and you together.

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Speaker 1: So if we can figure out what the rules are

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Speaker 1: that describe how molecules and atoms work, that improve instaple.

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Speaker 1: And that's an important distinction and principle we should be

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Speaker 1: able to extrapolate it up and understand how you work. Right,

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Speaker 1: It's kind of like saying, like, you know, we are

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Speaker 1: made out of inanimate bids. You know, I think we're

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Speaker 1: made out of things that are just plain things which

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Speaker 1: you can maybe predict what they're going to do. And

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Speaker 1: so does that mean that we are also inanimate in

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Speaker 1: a way unpredictable. Imagine you came across a robot, for example,

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Speaker 1: and it was doing weird stuff and you want to

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Speaker 1: understand it. How would you understand it? What? You would

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Speaker 1: take it apart and say, oh, it's made out of

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Speaker 1: these pieces, and can I understand each of those pieces?

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Speaker 1: And if so, you could put that together to an

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Speaker 1: understanding of the whole robot. And so the idea is

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Speaker 1: apply that to a person. Yeah, and you could do

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Speaker 1: things like, you know, if I, you know, if I

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Speaker 1: poked this little bit here in this engine, you know,

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Speaker 1: I predicted the and the car is gonna move forward

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Speaker 1: or backwards exactly. And all of this happening, of course,

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Speaker 1: assumes a few things. It assumes that you can get

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Speaker 1: a picture of what's what's happening inside your brain. The

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Speaker 1: idea you presented for choirs that we know each neuron,

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Speaker 1: we know the situation that neuron is in, right, It's

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Speaker 1: like for the watch, it's like that we know where

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Speaker 1: the levers are and where the gears are, and that

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Speaker 1: we can extrapolate up from those levers and gears to

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Speaker 1: the operation of a whole brain. That's not trivial. And

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Speaker 1: then you know, there's questions about like is it actually deterministic,

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Speaker 1: or is there like some funky quantum magic going on,

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Speaker 1: or is there something in there that like science can describe.

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Speaker 1: So it's not a trivial thing to say just just

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Speaker 1: because your brain is made of atoms that we could

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Speaker 1: therefore predict what you're gonna do. Right, Yeah, I think

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Speaker 1: that's the at the core question here, And so let's

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Speaker 1: get into it and um, just to say, some time, Daniel,

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Speaker 1: I will always take the cookie. You don't need a

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Speaker 1: fancy computer simulation to predict that I will take the cookie.

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Speaker 1: All right, I'm gonna cross that off my deep questions

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Speaker 1: of the universal list. Yeah, so let's get into it

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Speaker 1: a little bit more deeply and figure out how you

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Speaker 1: might even do this, or whether we can or if

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Speaker 1: there is some kind of quantum magic that might give

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Speaker 1: a little bit of a loophole to get free will.

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Speaker 1: But first let's take a quick break. All right, we're

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Speaker 1: talking about whether science can predict what you're gonna think

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Speaker 1: and do, and we talked about, um, yeah, that maybe

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Speaker 1: your your brain is made out of little bits and

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Speaker 1: pieces which which are sort of little biological machines. And

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Speaker 1: so does that mean that your whole brain is just

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Speaker 1: a machine or like a robot, which anyone could predict

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Speaker 1: what they're going to do? So let's get into it.

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Speaker 1: What are some of the things Daniel, that physicists know

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Speaker 1: or think that might make that picture really difficult or

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Speaker 1: maybe impossible to predict what you're going to do. The

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Speaker 1: first thing that comes to my mind is just knowing

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Speaker 1: the current status of your brain. Like if I wanted

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Speaker 1: to model the flight of a of a baseball, I

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Speaker 1: wanted to know exactly where baseball went. I would need

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Speaker 1: to know it's current position and it's current direction. If

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Speaker 1: you wanted to know if you wanted to predict where

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Speaker 1: what's gonna land, you would sort of need to know

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Speaker 1: you know where it is and where it's going at

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Speaker 1: any given time. Yeah, and and at any moment, just

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Speaker 1: one moment in time would determine where it's going to be.

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Speaker 1: So if I knew where that baseball was now and

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Speaker 1: where it was in which direction it was going in,

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Speaker 1: I could just apply the law of physics and propagate

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Speaker 1: that information forward. I would say, Oh, it's going to

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Speaker 1: move in a certain path under the under gravity, and

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Speaker 1: I can tell you exactly where it's going to land.

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Speaker 1: That's physics predicting the future, and that works for one

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Speaker 1: little tiny particle or baseball or whatever. But in order

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Speaker 1: to do that for your brain, I would need to

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Speaker 1: know the current situation of your brain, Like, what is

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Speaker 1: the situation of every neuron? Is it about to fire

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Speaker 1: a little pulse? Is it not about to fire pulse?

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Speaker 1: How strong is this connection between it and the next neuron?

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Speaker 1: And you know there's billions and billions of neurons in

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Speaker 1: your brains. We're talking about an enormous amount of information

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Speaker 1: you'd need to know. I think what you mean is

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Speaker 1: that even if I had a giant computers similiation of

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Speaker 1: your brain, I would need to give each of the

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Speaker 1: neurons kind of a starting value, right, or like I

428
00:23:05,720 --> 00:23:09,280
Speaker 1: would need to know where each neuron was in order

429
00:23:09,320 --> 00:23:12,439
Speaker 1: to predict what the whole brain was going to do. Precisely.

430
00:23:12,760 --> 00:23:14,840
Speaker 1: If I had a computer program that could simulate an

431
00:23:14,920 --> 00:23:17,320
Speaker 1: arbitrary brain, I would somehow need to configure it to

432
00:23:17,440 --> 00:23:20,040
Speaker 1: your brain. And that would mean knowing where all the

433
00:23:20,080 --> 00:23:22,200
Speaker 1: neurons were and how they were connected to each other

434
00:23:22,800 --> 00:23:24,800
Speaker 1: and all that kind of stuff. Just like if you

435
00:23:24,840 --> 00:23:26,679
Speaker 1: want to calculate where the baseball is going to go,

436
00:23:26,920 --> 00:23:28,800
Speaker 1: you need to know the initial conditions. You need to

437
00:23:28,840 --> 00:23:31,320
Speaker 1: know where it is now and which direction is going in.

438
00:23:31,760 --> 00:23:34,359
Speaker 1: So like, even if I had that computer program, and

439
00:23:34,359 --> 00:23:37,240
Speaker 1: even if it was possible um to use that computer

440
00:23:37,240 --> 00:23:39,600
Speaker 1: program to predict the future, how do I get that

441
00:23:39,680 --> 00:23:42,639
Speaker 1: information from your brain? Do I have to like scan

442
00:23:42,760 --> 00:23:45,080
Speaker 1: your brain somehow? You have to take your head off

443
00:23:45,119 --> 00:23:48,560
Speaker 1: and slice it into hyperfine little bits? Like how do

444
00:23:48,600 --> 00:23:52,239
Speaker 1: you even physically do that? Right? Because each neuron might

445
00:23:52,280 --> 00:23:54,480
Speaker 1: be in a different state, you know, like one win

446
00:23:54,600 --> 00:23:57,240
Speaker 1: might be more excited than others, or you might be

447
00:23:57,840 --> 00:23:59,240
Speaker 1: you know, you might be in a bad mood. And

448
00:23:59,280 --> 00:24:02,040
Speaker 1: so there's a general I don't know dopamine levels that

449
00:24:02,080 --> 00:24:05,439
Speaker 1: are you know, suppressing some of your neurons right now.

450
00:24:05,480 --> 00:24:07,320
Speaker 1: You need to know that in order to predict what

451
00:24:07,359 --> 00:24:08,920
Speaker 1: you're going to think and do. Yeah, And you need

452
00:24:08,960 --> 00:24:10,879
Speaker 1: to know it all at the same moment. Right, I

453
00:24:10,920 --> 00:24:12,600
Speaker 1: don't want to know what the left half of your

454
00:24:12,600 --> 00:24:14,280
Speaker 1: brain is doing right now and the right half of

455
00:24:14,280 --> 00:24:16,359
Speaker 1: your brain is doing two seconds ago. I need a

456
00:24:16,400 --> 00:24:19,919
Speaker 1: complete picture of your brain at one moment, so that

457
00:24:20,000 --> 00:24:23,600
Speaker 1: I know how what direction everything is moving in. I'm

458
00:24:23,640 --> 00:24:25,119
Speaker 1: just thinking of your brain is like a lot of

459
00:24:25,160 --> 00:24:28,000
Speaker 1: tiny little baseballs, and so I need to know where

460
00:24:28,040 --> 00:24:30,280
Speaker 1: all those baseballs are at the same time. So even

461
00:24:30,520 --> 00:24:33,399
Speaker 1: slicing your brain, you know, like a ham sandwich or whatever,

462
00:24:33,640 --> 00:24:36,960
Speaker 1: wouldn't work. I need to somehow instantly scan everything in

463
00:24:37,000 --> 00:24:43,840
Speaker 1: your brain. And that just seems almost impossible, right, It

464
00:24:43,920 --> 00:24:45,920
Speaker 1: seems almost impossible. I mean I read a lot of

465
00:24:45,960 --> 00:24:49,160
Speaker 1: science fiction, and there's some good stuff where the people

466
00:24:49,160 --> 00:24:52,160
Speaker 1: are uploading brains into the cloud, and sometimes they talk

467
00:24:52,200 --> 00:24:54,840
Speaker 1: about how scanning the brain is a destructive process, but

468
00:24:54,880 --> 00:24:56,959
Speaker 1: they never talked about how fast it has to be. Like,

469
00:24:57,000 --> 00:24:58,680
Speaker 1: if you want to scan the brain, it's got to

470
00:24:58,720 --> 00:25:01,359
Speaker 1: be a snapshot. You gotta know where everything is in

471
00:25:01,440 --> 00:25:05,480
Speaker 1: an instant or it's all averaged like over the last

472
00:25:05,600 --> 00:25:08,119
Speaker 1: five minutes or ten minutes or twenty minutes, or however

473
00:25:08,119 --> 00:25:10,639
Speaker 1: long it takes to scan the brain. And that's going

474
00:25:10,680 --> 00:25:13,280
Speaker 1: to be a disaster. So this is a technological issue,

475
00:25:13,320 --> 00:25:16,080
Speaker 1: not philosophical. But I don't know if that's even possible.

476
00:25:16,240 --> 00:25:18,399
Speaker 1: Oh I see, Okay, so that's kind of the first

477
00:25:18,880 --> 00:25:22,480
Speaker 1: um barrier that might prevent you from predicting somebody's brain

478
00:25:22,800 --> 00:25:25,960
Speaker 1: is getting a snapshot of it. But uh, and it

479
00:25:26,080 --> 00:25:28,720
Speaker 1: sounds impossible, but I think technically you can't rule it

480
00:25:28,760 --> 00:25:33,159
Speaker 1: out right, Like, it's not technically or theoretically impossible that

481
00:25:33,600 --> 00:25:36,040
Speaker 1: maybe one day people will come up with a brain

482
00:25:36,080 --> 00:25:38,639
Speaker 1: scan that can somehow capture all of your brain in

483
00:25:38,680 --> 00:25:41,280
Speaker 1: one instant. That's right, unless you need to know it's

484
00:25:41,320 --> 00:25:43,840
Speaker 1: sort of at the level of quantum mechanical objects, like

485
00:25:43,920 --> 00:25:46,679
Speaker 1: you need to know the exact location of every electron.

486
00:25:47,040 --> 00:25:50,520
Speaker 1: Then it's theoretically impossible because you can't measure the perfect

487
00:25:50,560 --> 00:25:53,440
Speaker 1: quantum state of the entire brain all at the same time.

488
00:25:54,200 --> 00:25:56,520
Speaker 1: I think that's theoretically impossible. But as long as it's

489
00:25:56,520 --> 00:25:59,600
Speaker 1: you know, not necessarily sensitive to quantum effects in theory,

490
00:25:59,680 --> 00:26:03,680
Speaker 1: it's possible, but technologically way out of our grasp today today. Yeah,

491
00:26:03,720 --> 00:26:06,280
Speaker 1: let's assume that that's possible and then think about what

492
00:26:06,320 --> 00:26:09,560
Speaker 1: the other problems would be. Yeah, yeah, because that's that's

493
00:26:09,600 --> 00:26:12,160
Speaker 1: not that's not the only problem is scanning your brain.

494
00:26:13,040 --> 00:26:16,560
Speaker 1: There are first we have to achieve this almost impossible

495
00:26:16,560 --> 00:26:20,320
Speaker 1: sounding technological feat. Then we got the real problems. Yeah, well,

496
00:26:20,359 --> 00:26:22,200
Speaker 1: you know that's what they said about the iPhone. And

497
00:26:22,560 --> 00:26:24,840
Speaker 1: look where we are now? Is that? Is that what

498
00:26:24,880 --> 00:26:27,679
Speaker 1: they said about the iPhone? Was it that? This was

499
00:26:27,720 --> 00:26:29,520
Speaker 1: that at the physics meeting you had with Einstein and

500
00:26:29,560 --> 00:26:31,679
Speaker 1: you know all those guys, Well it was science pitching

501
00:26:31,800 --> 00:26:34,840
Speaker 1: like fifty years ago, right, like this device that fit

502
00:26:34,880 --> 00:26:37,600
Speaker 1: in your pocket and you can talk video with people

503
00:26:37,840 --> 00:26:40,800
Speaker 1: and play addictive video games on for hours. I mean

504
00:26:40,800 --> 00:26:43,399
Speaker 1: that was like a Star trek. You know that's true.

505
00:26:43,800 --> 00:26:46,960
Speaker 1: And it'd be folly to say this kind of technology

506
00:26:46,960 --> 00:26:49,600
Speaker 1: will never be developed or would take years or centuries

507
00:26:49,680 --> 00:26:52,840
Speaker 1: or whatever, because those kind of predictions are always people

508
00:26:52,880 --> 00:26:55,720
Speaker 1: always look silly five years later after making those predictions.

509
00:26:56,119 --> 00:26:58,760
Speaker 1: So we should avoid that. And maybe technology will progress

510
00:26:58,880 --> 00:27:01,200
Speaker 1: rapidly and they'll invent the brain scan next week, and

511
00:27:01,240 --> 00:27:03,520
Speaker 1: they'll have a brain scan app that you can put

512
00:27:03,600 --> 00:27:06,639
Speaker 1: on your phone. Maybe, But then there are other things

513
00:27:06,640 --> 00:27:09,320
Speaker 1: that will would make this really difficult or that kind

514
00:27:09,320 --> 00:27:13,520
Speaker 1: of make your brain almost pretty much unpredictable. Right, Yeah,

515
00:27:13,520 --> 00:27:16,520
Speaker 1: there are a lot of practical issues and actually accomplishing

516
00:27:16,680 --> 00:27:18,879
Speaker 1: predicting what your brain is going to do. Say, we

517
00:27:18,920 --> 00:27:21,200
Speaker 1: had a snapshot at your brain, we knew the current

518
00:27:21,240 --> 00:27:23,880
Speaker 1: status of every neuron. We could load that into the computer,

519
00:27:24,320 --> 00:27:26,480
Speaker 1: and we wanted to run that forward. We wanted to say,

520
00:27:26,640 --> 00:27:29,320
Speaker 1: all right, well, what's this person going to do in

521
00:27:29,359 --> 00:27:33,760
Speaker 1: five minutes. That's not always easy. Some systems, even if

522
00:27:33,760 --> 00:27:36,720
Speaker 1: they're made of atoms which follow physical laws, and even

523
00:27:36,760 --> 00:27:39,760
Speaker 1: if you knew where all those atoms were, are hard

524
00:27:39,840 --> 00:27:44,280
Speaker 1: to describe. Yeah, because there um you're telling me earlier.

525
00:27:44,560 --> 00:27:48,840
Speaker 1: They're not easy systems to kind of simulate, or they're

526
00:27:48,840 --> 00:27:53,280
Speaker 1: not easy systems to um to kind of predict what

527
00:27:53,320 --> 00:27:55,159
Speaker 1: they're going to do. Yeah, and this is again a

528
00:27:55,200 --> 00:27:58,760
Speaker 1: technological problem, but it's a real problem, Like why can't

529
00:27:58,760 --> 00:28:02,480
Speaker 1: we predict the weather? In theory, weather follows rules that

530
00:28:02,520 --> 00:28:06,480
Speaker 1: we understand water droplets and air resistance and wind and

531
00:28:06,520 --> 00:28:09,560
Speaker 1: all that stuff. That's not complicated physics. They're just atoms. Yeah,

532
00:28:09,600 --> 00:28:11,800
Speaker 1: they're just atoms, And we don't even need to worry

533
00:28:11,800 --> 00:28:13,840
Speaker 1: about the atoms. We can think about the water droplets

534
00:28:13,840 --> 00:28:16,720
Speaker 1: and the temperature and stuff. So why is it so

535
00:28:16,760 --> 00:28:18,960
Speaker 1: hard to predict when it's going to rain or when

536
00:28:18,960 --> 00:28:20,840
Speaker 1: a hurricane is going to come. If it's following the

537
00:28:20,880 --> 00:28:23,679
Speaker 1: laws of physics, and we have amazing satellites that are

538
00:28:23,720 --> 00:28:26,840
Speaker 1: like gathering all this data about what the temperature is everywhere,

539
00:28:26,960 --> 00:28:30,359
Speaker 1: it's a very similar problem. The reason that weather it

540
00:28:30,400 --> 00:28:32,680
Speaker 1: is hard to predict is not because it doesn't follow

541
00:28:32,680 --> 00:28:35,920
Speaker 1: the laws of physics. It's because it's very, very sensitive

542
00:28:36,160 --> 00:28:40,120
Speaker 1: to the exact tiny details of the situation. A small

543
00:28:40,280 --> 00:28:43,320
Speaker 1: change in temperature over here leads to a big change

544
00:28:43,360 --> 00:28:46,320
Speaker 1: over there. That's something we call chaos. Right, It's this

545
00:28:46,360 --> 00:28:48,600
Speaker 1: idea that the kind of goes back to that whole

546
00:28:48,600 --> 00:28:52,600
Speaker 1: butterfly idea, right, Like like they say that if a

547
00:28:52,680 --> 00:28:55,360
Speaker 1: butterfly flaps its wing in one part of the world,

548
00:28:55,480 --> 00:28:58,720
Speaker 1: it can actually affect the weather in another part of

549
00:28:58,760 --> 00:29:02,080
Speaker 1: the world, just because it's so sensitive to even small

550
00:29:02,160 --> 00:29:05,240
Speaker 1: things like a butterfly flapping its wing. That's right, and

551
00:29:05,320 --> 00:29:08,520
Speaker 1: not every system is chaotic. Some things are not right

552
00:29:08,560 --> 00:29:10,760
Speaker 1: some things. For example, when you throw a ball, you

553
00:29:10,800 --> 00:29:13,640
Speaker 1: throw a ball, if you change the angle you're throwing

554
00:29:13,640 --> 00:29:16,520
Speaker 1: it at by a tiny bit, then the outcome is

555
00:29:16,640 --> 00:29:18,960
Speaker 1: changed by a tiny bit. Right, you throw it a

556
00:29:19,000 --> 00:29:21,640
Speaker 1: tiny bit harder, it lands, it goes a tin a

557
00:29:21,640 --> 00:29:24,480
Speaker 1: bit further. But other things, if you change how you

558
00:29:24,480 --> 00:29:25,959
Speaker 1: do them by a tiny bit, you get a very

559
00:29:25,960 --> 00:29:29,040
Speaker 1: different outcome, Like rolling a die. If you roll a

560
00:29:29,080 --> 00:29:31,480
Speaker 1: dice slightly differently, you spin your hand to tying a

561
00:29:31,480 --> 00:29:33,760
Speaker 1: bit differently, you get a four instead of a two,

562
00:29:33,880 --> 00:29:36,040
Speaker 1: or a five instead of a one. So the outcome

563
00:29:36,080 --> 00:29:39,560
Speaker 1: depends very very sensitive and exactly how you did it.

564
00:29:39,560 --> 00:29:43,200
Speaker 1: It's not random, it's following the laws of physics. In theory,

565
00:29:43,360 --> 00:29:47,080
Speaker 1: it's predictable, but in practice it's very difficult because the

566
00:29:47,120 --> 00:29:51,080
Speaker 1: outcome depends very sensitively on how you flap those butterfly wings, yeah,

567
00:29:51,200 --> 00:29:53,360
Speaker 1: or how you throw the die. Like to predict a

568
00:29:53,440 --> 00:29:56,120
Speaker 1: die roll, you would need to really kind of like

569
00:29:56,160 --> 00:30:00,560
Speaker 1: pay attention to the exact angle that each I is

570
00:30:01,320 --> 00:30:03,800
Speaker 1: at when it leaves your hand, and you have to

571
00:30:03,840 --> 00:30:07,480
Speaker 1: predict also or simulate how like when the corners hit

572
00:30:07,560 --> 00:30:09,720
Speaker 1: the ground, how that's going to affect the spin of

573
00:30:09,800 --> 00:30:12,720
Speaker 1: the die. And so it's really it's just a much

574
00:30:12,760 --> 00:30:16,800
Speaker 1: more complicated system to simulate and predict than like just

575
00:30:16,840 --> 00:30:19,120
Speaker 1: throwing a baseball. So then the question is, is your

576
00:30:19,120 --> 00:30:22,040
Speaker 1: brain like a big bag of dice with very each

577
00:30:22,040 --> 00:30:24,520
Speaker 1: one very difficult to predict and bouncing off the other one.

578
00:30:24,800 --> 00:30:27,920
Speaker 1: It's a very complex thing, or is it made out

579
00:30:27,920 --> 00:30:30,600
Speaker 1: of things which are easy to predict? And if you

580
00:30:30,680 --> 00:30:34,360
Speaker 1: knew pretty much the current situation that you could predict

581
00:30:34,360 --> 00:30:36,000
Speaker 1: how it's going to come about? You know, is your

582
00:30:36,000 --> 00:30:38,960
Speaker 1: brain a hurricane or is it just a baseball right?

583
00:30:39,440 --> 00:30:41,480
Speaker 1: Or you know, if I have butterflies in my stomach

584
00:30:41,520 --> 00:30:43,520
Speaker 1: and those they flap, what's how is it going to

585
00:30:44,400 --> 00:30:47,320
Speaker 1: affect my decision to eat a cookie or not exactly?

586
00:30:47,360 --> 00:30:49,720
Speaker 1: So the point is that even if you knew exactly

587
00:30:49,760 --> 00:30:52,320
Speaker 1: the current situation of the brain, could you have a

588
00:30:52,400 --> 00:30:55,120
Speaker 1: powerful enough computer to predict what it's going to happen

589
00:30:55,120 --> 00:30:57,680
Speaker 1: going forward? And in the end, that's really the limitation.

590
00:30:58,080 --> 00:31:01,200
Speaker 1: For example, for hurricanes, if we the location of every

591
00:31:01,280 --> 00:31:04,200
Speaker 1: drop of water on Earth and its current position and velocity,

592
00:31:04,400 --> 00:31:07,320
Speaker 1: and we had a super duper powerful computer, then yeah,

593
00:31:07,360 --> 00:31:11,400
Speaker 1: we could probably predict the weather very accurately. But we

594
00:31:11,480 --> 00:31:14,560
Speaker 1: don't have those computers right well, were I feel like

595
00:31:14,560 --> 00:31:16,720
Speaker 1: we're getting better though, you know, like sometimes I'm really

596
00:31:16,760 --> 00:31:19,400
Speaker 1: impressed by how far ahead we can predict the weather

597
00:31:19,480 --> 00:31:22,360
Speaker 1: and how somewhat accurately, we can. This is just a

598
00:31:22,440 --> 00:31:26,840
Speaker 1: hurdle of technology. Something of the fastest computers in the world,

599
00:31:26,840 --> 00:31:30,160
Speaker 1: like the supercomputers, are all devoted to this problem predicting

600
00:31:30,200 --> 00:31:32,840
Speaker 1: the future of the weather, understanding the atmosphere and all

601
00:31:32,920 --> 00:31:35,880
Speaker 1: of its chaos, and so it's really just like throwing

602
00:31:35,880 --> 00:31:39,080
Speaker 1: more computational power at the problem. Well, and that's because

603
00:31:39,200 --> 00:31:42,920
Speaker 1: weather is a chaotic system, right, Definitely, weather is very chaotic.

604
00:31:42,960 --> 00:31:45,480
Speaker 1: It's very difficult to predict the outcome, even if you

605
00:31:45,560 --> 00:31:47,960
Speaker 1: know the current conditions. But do we know if the

606
00:31:48,040 --> 00:31:52,200
Speaker 1: brain is chaotic or humans or chaotic? Humans seem chaoic

607
00:31:52,240 --> 00:31:53,760
Speaker 1: to me. I mean some of them I've known for

608
00:31:53,800 --> 00:31:56,280
Speaker 1: decades and I still don't understand why. Then good decisions

609
00:31:56,320 --> 00:32:01,240
Speaker 1: they do, and not just their children, not just of children. No,

610
00:32:01,440 --> 00:32:03,280
Speaker 1: we don't know for sure, but it seems to me

611
00:32:03,600 --> 00:32:07,400
Speaker 1: very likely. I mean, it's a hyper connected, very sensitive

612
00:32:07,600 --> 00:32:10,560
Speaker 1: set of neurons. It seems to me very unlikely that

613
00:32:10,640 --> 00:32:12,440
Speaker 1: it wouldn't be a chaotic, But we don't know. It

614
00:32:12,560 --> 00:32:16,080
Speaker 1: might be that there are sort of emergent phenomenon that

615
00:32:16,360 --> 00:32:19,160
Speaker 1: you're not really sensitive to all the little details, and

616
00:32:19,200 --> 00:32:22,760
Speaker 1: that you could build a model that predicts roughly where

617
00:32:22,800 --> 00:32:25,280
Speaker 1: things are going. If you don't care about the details,

618
00:32:25,360 --> 00:32:27,960
Speaker 1: you can tell whether somebody's gonna have a cookie and

619
00:32:28,000 --> 00:32:29,960
Speaker 1: who they're going to vote for the next election. It's

620
00:32:30,000 --> 00:32:32,720
Speaker 1: possible that you could build those models, but that requires

621
00:32:32,720 --> 00:32:36,400
Speaker 1: a sort of another layer of insight. Right. Imagine you

622
00:32:36,800 --> 00:32:39,840
Speaker 1: only knew the baseball in terms of little particles inside

623
00:32:39,840 --> 00:32:41,200
Speaker 1: of it. You're like, oh, there's no way I could

624
00:32:41,200 --> 00:32:43,240
Speaker 1: predict the way this baseball is gonna move. There's ten

625
00:32:43,280 --> 00:32:47,080
Speaker 1: to the twenty three particles. It's impossible. But if you understand,

626
00:32:47,080 --> 00:32:49,280
Speaker 1: if you took a step back and saw the flight

627
00:32:49,320 --> 00:32:51,280
Speaker 1: of it, you can say, oh, actually, I can describe

628
00:32:51,320 --> 00:32:53,760
Speaker 1: this and ignore all the particles. I can ignore all

629
00:32:53,760 --> 00:32:56,800
Speaker 1: those details they're not relevant, and I can just describe

630
00:32:56,840 --> 00:32:59,520
Speaker 1: this in terms of simple motion. So it's possible that

631
00:32:59,600 --> 00:33:03,640
Speaker 1: there's an emergent theory of psychology mathematical psychology that could

632
00:33:03,920 --> 00:33:05,960
Speaker 1: describe the motion of the brain. We just don't know,

633
00:33:06,760 --> 00:33:09,600
Speaker 1: or I wonder if it might vary with people. You know,

634
00:33:09,680 --> 00:33:12,960
Speaker 1: some people might be more predictable than others. Yeah, I

635
00:33:13,000 --> 00:33:17,000
Speaker 1: certainly know some people who seem pretty chaotic. All right, Well,

636
00:33:17,280 --> 00:33:19,600
Speaker 1: those are two pretty big hurdles, and but then there's

637
00:33:19,760 --> 00:33:23,719
Speaker 1: um another hurdle coming up and and or possibly a

638
00:33:23,720 --> 00:33:27,000
Speaker 1: loophole that might still let us have some free will

639
00:33:27,040 --> 00:33:31,760
Speaker 1: in this deterministic machine like universe. So let's get into that.

640
00:33:31,800 --> 00:33:47,240
Speaker 1: But first let's take a quick break, all right, Daniel.

641
00:33:47,280 --> 00:33:53,040
Speaker 1: The last topic here is about randomness and whether randomness

642
00:33:53,040 --> 00:33:57,480
Speaker 1: at the quantum level can maybe effect what we see

643
00:33:57,520 --> 00:34:00,000
Speaker 1: as free will, or whether it can affect with or

644
00:34:00,080 --> 00:34:02,400
Speaker 1: not we can predict what people will think or do.

645
00:34:02,600 --> 00:34:04,760
Speaker 1: The whole premise here, The assumption we're making is that

646
00:34:04,840 --> 00:34:08,560
Speaker 1: the brain should be predictable if it's various bits are predictable,

647
00:34:08,719 --> 00:34:10,600
Speaker 1: if it's made out of predictable bits, then you should

648
00:34:10,600 --> 00:34:13,279
Speaker 1: be able to put those predictable bits together into a

649
00:34:13,320 --> 00:34:17,240
Speaker 1: predictable brain. But listeners of the podcast are probably wondering,

650
00:34:17,600 --> 00:34:20,520
Speaker 1: are those bits predictable? The brain is made of atoms,

651
00:34:20,560 --> 00:34:22,719
Speaker 1: and atoms are made of protons and electrons and all

652
00:34:22,800 --> 00:34:25,680
Speaker 1: this stuff, and we know that those things are quantum mechanical,

653
00:34:25,719 --> 00:34:28,880
Speaker 1: and we talked on the podcast recently about the crazy

654
00:34:28,920 --> 00:34:33,120
Speaker 1: probabilistic nature or quantum mechanics, that things are not determined

655
00:34:33,160 --> 00:34:36,200
Speaker 1: until their measures, that there is really true randomness at

656
00:34:36,200 --> 00:34:39,080
Speaker 1: the quantum scale. So you might be wondering, how can

657
00:34:39,120 --> 00:34:43,399
Speaker 1: you build determinism on top of this fuzzy quantum randomness. Yeah,

658
00:34:43,440 --> 00:34:45,520
Speaker 1: because we talked about some of the challenges, right, We

659
00:34:45,600 --> 00:34:48,680
Speaker 1: talked about scanning your brain and about chaos, and but

660
00:34:48,760 --> 00:34:52,239
Speaker 1: those are technical problems. You're saying that maybe just in

661
00:34:52,280 --> 00:34:55,400
Speaker 1: the bits themselves of the brain, there is some inherent

662
00:34:55,920 --> 00:35:00,319
Speaker 1: randomness that might make it impossible to predict. Absolutely, we

663
00:35:00,440 --> 00:35:03,239
Speaker 1: know that there's inherent randomness. Everything, as we say, is

664
00:35:03,320 --> 00:35:06,440
Speaker 1: made of atoms, and those things are governed by fundamentally

665
00:35:06,480 --> 00:35:11,000
Speaker 1: quantum mechanical properties. What we don't know is if that matters, right,

666
00:35:11,040 --> 00:35:14,520
Speaker 1: It certainly doesn't matter for predicting the motion of a

667
00:35:14,560 --> 00:35:18,080
Speaker 1: mechanical watch. People can build mechanical watches that are super

668
00:35:18,120 --> 00:35:20,640
Speaker 1: accurate for years at a time. We can predict the

669
00:35:20,680 --> 00:35:23,800
Speaker 1: flight of a baseball without even knowing that quantum mechanics

670
00:35:23,840 --> 00:35:26,799
Speaker 1: was the thing. I remember. Quantum mechanics affects things only

671
00:35:26,800 --> 00:35:31,799
Speaker 1: on super duper tiny scales. The uncertainty principle delta x

672
00:35:31,840 --> 00:35:36,320
Speaker 1: delta P the relationship between the uncertainty and motion and position.

673
00:35:36,800 --> 00:35:39,880
Speaker 1: The uncertainty there is is related to this. Planks constant

674
00:35:39,960 --> 00:35:42,520
Speaker 1: each bar, which is like the fundamental unit of the universe.

675
00:35:42,600 --> 00:35:45,120
Speaker 1: But this is a super tiny number. It's ten to

676
00:35:45,160 --> 00:35:49,120
Speaker 1: the minus thirty four jewels. And so it might be

677
00:35:49,520 --> 00:35:52,120
Speaker 1: that on top of the quantum randomness, we do have

678
00:35:52,360 --> 00:35:55,640
Speaker 1: a layer of physics which is deterministic. Or it could

679
00:35:55,680 --> 00:35:57,840
Speaker 1: be that you know that the quantum randomness sort of

680
00:35:57,880 --> 00:36:00,279
Speaker 1: seeps up from below and affects the world working of

681
00:36:00,360 --> 00:36:03,120
Speaker 1: the brain. Okay, so you're saying that there is a

682
00:36:03,200 --> 00:36:08,759
Speaker 1: fundamental randomness in the universe and in my brain cells,

683
00:36:08,800 --> 00:36:13,520
Speaker 1: Like at the to the smallest level, I can't possibly

684
00:36:13,520 --> 00:36:16,880
Speaker 1: predict my brain, but maybe if I go up a

685
00:36:16,920 --> 00:36:20,120
Speaker 1: few levels, then the brain starts to be more predictable.

686
00:36:20,200 --> 00:36:22,040
Speaker 1: We see this in physics. We see at the very

687
00:36:22,080 --> 00:36:24,960
Speaker 1: smallest levels you cannot predict what's going to happen. You

688
00:36:25,000 --> 00:36:27,800
Speaker 1: shoot the same photon into the same experiment twice, you

689
00:36:27,880 --> 00:36:31,719
Speaker 1: get two different outcomes. There's really true randomness there, and

690
00:36:31,800 --> 00:36:36,680
Speaker 1: that breaks determinism. So photons not deterministic, electrons not deterministic.

691
00:36:36,920 --> 00:36:41,840
Speaker 1: Protons not deterministic. But somehow, when you put these things together,

692
00:36:42,080 --> 00:36:45,719
Speaker 1: you put enough of them together, all those random fluctuations

693
00:36:45,760 --> 00:36:48,560
Speaker 1: average out that basically cancel each other. This is a

694
00:36:48,680 --> 00:36:51,440
Speaker 1: deep theorem in physics. It's called the air infest theorem,

695
00:36:51,480 --> 00:36:53,680
Speaker 1: that you have enough of these things and it doesn't

696
00:36:53,719 --> 00:36:55,759
Speaker 1: matter anymore as long as you're measuring things on the

697
00:36:55,840 --> 00:36:59,960
Speaker 1: sort of classical scale and sizes that we care about centimeters, millimeters.

698
00:37:00,040 --> 00:37:03,200
Speaker 1: Even then the quantum mechanic effects average out, which is

699
00:37:03,320 --> 00:37:06,239
Speaker 1: why we didn't notice quantum mechanics for thousands of years.

700
00:37:06,400 --> 00:37:09,560
Speaker 1: It's hidden inside the summation of all of these quantum

701
00:37:09,600 --> 00:37:12,399
Speaker 1: little events. Yeah, which is why it was so hard

702
00:37:12,440 --> 00:37:15,600
Speaker 1: to accept. Right, we had just accepted the mind boggling

703
00:37:15,600 --> 00:37:19,120
Speaker 1: consequences of a deterministic universe, like, wow, the universe seems

704
00:37:19,120 --> 00:37:21,040
Speaker 1: to follow rules and we can predict it. And then

705
00:37:21,080 --> 00:37:23,880
Speaker 1: we discovered, oh, actually no, at its deepest level, it

706
00:37:23,920 --> 00:37:27,000
Speaker 1: seems weirdly random. And that was totally in contradiction with

707
00:37:27,040 --> 00:37:29,760
Speaker 1: everything we thought we understood, which is why quantum mechanics

708
00:37:29,800 --> 00:37:33,360
Speaker 1: are so counterintuitive and so fuzzy. But still, it didn't

709
00:37:33,400 --> 00:37:36,400
Speaker 1: mean that all those things we learned were wrong. It

710
00:37:36,480 --> 00:37:39,280
Speaker 1: just meant that they applied to sort of the larger scales,

711
00:37:39,320 --> 00:37:43,240
Speaker 1: that those same rules can't be applied to electrons and protons.

712
00:37:43,280 --> 00:37:46,040
Speaker 1: But they can still be applied to baseballs and watches.

713
00:37:46,600 --> 00:37:49,800
Speaker 1: So then the question is is your brain a baseball

714
00:37:49,800 --> 00:37:52,319
Speaker 1: and watch or is it an electron. Yeah, it's kind

715
00:37:52,320 --> 00:37:55,080
Speaker 1: of like if I said, um, hey, Dana, I'm gonna

716
00:37:55,080 --> 00:37:57,279
Speaker 1: flip this coin, and if it's head, i'm gonna take

717
00:37:57,320 --> 00:37:59,279
Speaker 1: your cookie, and if its tails, I'm not going to

718
00:37:59,360 --> 00:38:01,799
Speaker 1: take your cookie. Then it then it's kind of like

719
00:38:02,200 --> 00:38:04,440
Speaker 1: then you might say it's unpredictable what am I gonna do? Right,

720
00:38:04,680 --> 00:38:07,680
Speaker 1: because you don't know except that a coin is deterministic.

721
00:38:07,800 --> 00:38:10,279
Speaker 1: A coin is a classical object. If I knew exactly

722
00:38:10,320 --> 00:38:12,839
Speaker 1: how you're gonna flip it, I could predict exactly how

723
00:38:12,880 --> 00:38:14,960
Speaker 1: that coin was gonna land, and I would know that

724
00:38:15,000 --> 00:38:16,480
Speaker 1: you were going to take the cookie no matter how

725
00:38:16,480 --> 00:38:19,000
Speaker 1: the coin flipped, actually, because I know you as a person,

726
00:38:19,680 --> 00:38:22,640
Speaker 1: but but yeah, exactly the coin flip is not written.

727
00:38:22,680 --> 00:38:25,200
Speaker 1: But if you, for example, how a radioactive particle and

728
00:38:25,239 --> 00:38:27,920
Speaker 1: you said, I'm gonna wait one minute. If the particle

729
00:38:28,040 --> 00:38:30,440
Speaker 1: decays in within this minute, I'm eating the cookie. And

730
00:38:30,440 --> 00:38:32,960
Speaker 1: if it doesn't decay within this minute, I'm not eating

731
00:38:33,000 --> 00:38:35,920
Speaker 1: the cookie. Then I can't predict whether or not you're

732
00:38:35,920 --> 00:38:38,440
Speaker 1: gonna eat the cookie. That's because you linked a macroscopic

733
00:38:38,480 --> 00:38:42,600
Speaker 1: action eating the cookie to a quantum mechanical thing. That's rare. Right,

734
00:38:42,640 --> 00:38:45,960
Speaker 1: that's a whole Shrowdinger's box argument. It's very difficult to

735
00:38:46,000 --> 00:38:48,840
Speaker 1: find quantum mechanic effects that you can see on the

736
00:38:48,880 --> 00:38:52,480
Speaker 1: macroscopic scale. Oh, I see, like, if if I made

737
00:38:52,560 --> 00:38:59,319
Speaker 1: my cookie eating dependent on whether this particle decays or not,

738
00:38:59,760 --> 00:39:02,960
Speaker 1: then it's unpredictable. But if I make my eating the

739
00:39:03,000 --> 00:39:07,240
Speaker 1: cookie depending on whether the particle will decay over a minute,

740
00:39:07,760 --> 00:39:10,960
Speaker 1: then we know a lot more. Right, it's less unpredictable

741
00:39:10,960 --> 00:39:14,040
Speaker 1: because you know that on average, most of these particles,

742
00:39:14,080 --> 00:39:17,680
Speaker 1: let's say, like these particles decay within a minute. Yeah,

743
00:39:17,840 --> 00:39:20,960
Speaker 1: that's true. And if you want to make statements about averages,

744
00:39:21,239 --> 00:39:23,799
Speaker 1: then you're a rock solid footing even quantum mechanically, because

745
00:39:23,840 --> 00:39:26,319
Speaker 1: quantum mechanics doesn't mean things don't follow laws. It just

746
00:39:26,360 --> 00:39:29,200
Speaker 1: means those laws are probabilistic. And so you can say,

747
00:39:29,200 --> 00:39:31,120
Speaker 1: on average, this is going to happen. On average, that's

748
00:39:31,160 --> 00:39:34,520
Speaker 1: gonna happen for one particular particle. You can't make any

749
00:39:34,600 --> 00:39:37,799
Speaker 1: predictions on a quantum mechanical scale, but you know what

750
00:39:37,920 --> 00:39:41,040
Speaker 1: quantum mechanical effects do you observe as a person, Like

751
00:39:41,520 --> 00:39:45,160
Speaker 1: for quantum, for something to affect your life that's really random,

752
00:39:45,400 --> 00:39:48,120
Speaker 1: it has to have an impact like that somebody's measuring

753
00:39:48,160 --> 00:39:51,200
Speaker 1: this quantum mechanical thing and making a decision based on it.

754
00:39:51,200 --> 00:39:54,840
Speaker 1: It's really pretty rare for quantum mechanical randomness to affect

755
00:39:54,960 --> 00:39:58,920
Speaker 1: the macroscopic world. People do really complicated experiments to try

756
00:39:58,920 --> 00:40:01,799
Speaker 1: to set this kind of thing up. Bose Einstein condensate.

757
00:40:02,200 --> 00:40:05,400
Speaker 1: It's like a macroscopic quantum state that you can see

758
00:40:05,719 --> 00:40:08,960
Speaker 1: that actually behaves quantum mechanically. It's really weird and amazing,

759
00:40:08,960 --> 00:40:12,400
Speaker 1: and people want the Nobel Prize for that. So two,

760
00:40:12,440 --> 00:40:15,800
Speaker 1: for the brain to be dependent on quantum mechanical randomness,

761
00:40:15,840 --> 00:40:18,480
Speaker 1: you'd have to show somehow that like the motion of

762
00:40:18,560 --> 00:40:23,040
Speaker 1: these electrons and this weird quantum mechanical effect was triggering neurons,

763
00:40:23,040 --> 00:40:26,759
Speaker 1: and neurons were somehow sensitive to these things. Yeah, So

764
00:40:26,920 --> 00:40:30,000
Speaker 1: it's so it's it's it's fundamentally random. But the question,

765
00:40:30,120 --> 00:40:32,279
Speaker 1: it seems like the core and the key question here

766
00:40:32,360 --> 00:40:36,360
Speaker 1: is whether that randomness at the quantum level really affects

767
00:40:36,360 --> 00:40:38,400
Speaker 1: whether I'm going to eat my cookie or not, or

768
00:40:38,400 --> 00:40:41,960
Speaker 1: whether that all gets drowned out by the Brazilian electrons

769
00:40:41,960 --> 00:40:43,719
Speaker 1: that I have in my brain. And there are some

770
00:40:43,760 --> 00:40:46,239
Speaker 1: folks who have made that argument, and I think that

771
00:40:46,239 --> 00:40:50,320
Speaker 1: that argument is largely in response to fear of determinism.

772
00:40:50,360 --> 00:40:52,479
Speaker 1: They don't want to think that the that the brain

773
00:40:52,600 --> 00:40:54,920
Speaker 1: is just a mechanical watch that can be predicted. So

774
00:40:54,920 --> 00:40:58,400
Speaker 1: there's sort of striving for some way to leave a

775
00:40:58,440 --> 00:41:00,600
Speaker 1: window open for free will. And they, oh, well, if

776
00:41:00,640 --> 00:41:03,279
Speaker 1: we can connect it to quantum randomness, then you know

777
00:41:03,320 --> 00:41:05,640
Speaker 1: you can't be predicted and therefore there might be room

778
00:41:05,680 --> 00:41:08,640
Speaker 1: for free will. And famous people like Roger Penrose make

779
00:41:08,680 --> 00:41:11,680
Speaker 1: this argument, but it's just a it's more like a

780
00:41:11,680 --> 00:41:14,560
Speaker 1: an outline of an argument. There's no evidence that the

781
00:41:14,600 --> 00:41:17,600
Speaker 1: brain is dependent on quantum mechanic. It's just like, can

782
00:41:17,680 --> 00:41:20,880
Speaker 1: we find some path maybe go down that leads us

783
00:41:20,920 --> 00:41:24,400
Speaker 1: to a nondeterministic brain. There's no real evidence or argument there.

784
00:41:24,400 --> 00:41:27,600
Speaker 1: It's just like a suggestion. Well, the I think the

785
00:41:27,640 --> 00:41:30,000
Speaker 1: thing is that it's it's a it's a yes or

786
00:41:30,040 --> 00:41:32,719
Speaker 1: no decision, right, whether I eat the cookie, it's either

787
00:41:32,840 --> 00:41:35,440
Speaker 1: yes or no. So I'm kind of like sitting on

788
00:41:35,520 --> 00:41:39,759
Speaker 1: the edge of a really thin knife, right, and you

789
00:41:39,800 --> 00:41:42,279
Speaker 1: know who knows. Are you can you really rule out

790
00:41:42,280 --> 00:41:46,600
Speaker 1: that you know how one particular electron behaved it was

791
00:41:46,840 --> 00:41:49,120
Speaker 1: resulted in pushing me one way or the other, Or

792
00:41:49,160 --> 00:41:54,040
Speaker 1: are you saying that pretty much that's unlikely. No, I'm

793
00:41:54,040 --> 00:41:55,560
Speaker 1: not saying that we can rule it out at all.

794
00:41:55,600 --> 00:41:57,520
Speaker 1: You're totally right, and it could be that there are

795
00:41:57,600 --> 00:42:01,040
Speaker 1: quantum mechanic effects that determine whether you make that decision.

796
00:42:01,080 --> 00:42:03,920
Speaker 1: It's possible, but I'm saying we have no evidence for that.

797
00:42:04,080 --> 00:42:06,800
Speaker 1: Nobody has shown that we don't even understand the mechanism

798
00:42:06,880 --> 00:42:08,799
Speaker 1: of it. That doesn't mean it's not happening. It just

799
00:42:08,880 --> 00:42:12,160
Speaker 1: means that it's more of a suggestion, an open door,

800
00:42:12,400 --> 00:42:15,400
Speaker 1: than an actual idea. All right, well, I feel I

801
00:42:15,440 --> 00:42:17,799
Speaker 1: feel pretty good. I feel like we um we're right

802
00:42:17,840 --> 00:42:20,960
Speaker 1: where we predicted we would be. I think you deserved

803
00:42:20,960 --> 00:42:25,279
Speaker 1: a cookie or a banana at the very list. Oh no, wait,

804
00:42:25,320 --> 00:42:28,319
Speaker 1: do you say? I would say, there you go? But

805
00:42:28,440 --> 00:42:31,000
Speaker 1: I think that there's some fascinating questions there, like even

806
00:42:31,040 --> 00:42:33,000
Speaker 1: if you knew the answer to this question, even if

807
00:42:33,000 --> 00:42:36,759
Speaker 1: you showed that the brain was deterministic or wasn't that

808
00:42:36,840 --> 00:42:40,000
Speaker 1: the brain was quantum mechanically random, what would that mean

809
00:42:40,280 --> 00:42:43,400
Speaker 1: for this experience of free will. Let me see if

810
00:42:43,440 --> 00:42:46,280
Speaker 1: I can readat what we learned. We learned that it's

811
00:42:46,280 --> 00:42:50,200
Speaker 1: predicting what people are going to do is super technically

812
00:42:50,280 --> 00:42:53,040
Speaker 1: hard with the scanning all of the neurons in your

813
00:42:53,040 --> 00:42:58,000
Speaker 1: brain and chaos maybe playing a large party making it unpredictable.

814
00:42:58,120 --> 00:43:00,480
Speaker 1: But let's say like we invented technology to take care

815
00:43:00,520 --> 00:43:02,879
Speaker 1: of that, there's still sort of the question of whether

816
00:43:03,000 --> 00:43:09,040
Speaker 1: randomness trickles up to influence decisions, you know, randomness at

817
00:43:09,080 --> 00:43:12,440
Speaker 1: the quantum level, whether that trickles up to influenced decisions,

818
00:43:12,520 --> 00:43:14,680
Speaker 1: And it sounds like we we we don't know. It

819
00:43:14,719 --> 00:43:16,960
Speaker 1: sounds like we can't say either way. That's right. Quantum

820
00:43:16,960 --> 00:43:20,919
Speaker 1: mechanics might make it theoretically impossible to predict the brain.

821
00:43:21,000 --> 00:43:23,680
Speaker 1: We don't know, And if it doesn't, if it doesn't

822
00:43:23,680 --> 00:43:26,400
Speaker 1: make it impossible, and we know, it's still super duper

823
00:43:26,480 --> 00:43:29,319
Speaker 1: hard because you need to know the exact state of

824
00:43:29,320 --> 00:43:32,800
Speaker 1: the brain and you need to overcome the potential overwhelming

825
00:43:32,960 --> 00:43:36,919
Speaker 1: chaos of your billions and billions of neurons. So even

826
00:43:36,960 --> 00:43:40,239
Speaker 1: if it's not impossible, it's definitely very very tricky, right,

827
00:43:40,320 --> 00:43:42,000
Speaker 1: And then we could probably have a whole podcast just

828
00:43:42,080 --> 00:43:45,279
Speaker 1: on the implications on how we feel about free will

829
00:43:45,360 --> 00:43:48,640
Speaker 1: and whether it would still exist even if it was

830
00:43:48,960 --> 00:43:51,879
Speaker 1: governed by quantum randomness. That's right, And this is an

831
00:43:51,920 --> 00:43:55,480
Speaker 1: area of philosophy, And neither you nor I have formal

832
00:43:55,480 --> 00:43:57,400
Speaker 1: training in philosophy. What do you mean have a doctorate

833
00:43:57,400 --> 00:44:03,520
Speaker 1: in philosophy in engineerings. So then let me ask you, Jorge,

834
00:44:03,800 --> 00:44:06,560
Speaker 1: if I could prove that you were deterministic, does that

835
00:44:06,640 --> 00:44:08,960
Speaker 1: mean you don't have free will? This being a big

836
00:44:09,000 --> 00:44:11,759
Speaker 1: mechanical robot mean you're not making choices? Or is that

837
00:44:11,840 --> 00:44:15,640
Speaker 1: just describe the choices you are you are making? I

838
00:44:15,680 --> 00:44:18,759
Speaker 1: think that would be bananas. No, I think for me

839
00:44:18,880 --> 00:44:20,839
Speaker 1: it sort of doesn't matter. I feel like it doesn't matter.

840
00:44:20,840 --> 00:44:23,160
Speaker 1: I'm not I'm not someone who sweats free will too much.

841
00:44:23,640 --> 00:44:25,680
Speaker 1: To be honest, Like, I feel like it might be

842
00:44:25,719 --> 00:44:29,239
Speaker 1: a robot. That's fine, And um, you know, currently it's

843
00:44:29,239 --> 00:44:31,120
Speaker 1: almost like who would want to predict what I'm going

844
00:44:31,160 --> 00:44:33,160
Speaker 1: to do? Do you know what I mean? Like, it's

845
00:44:33,239 --> 00:44:37,160
Speaker 1: such like, why is this problem even interesting? Who would

846
00:44:37,160 --> 00:44:39,200
Speaker 1: take the time to care about what I'm going to

847
00:44:39,320 --> 00:44:42,279
Speaker 1: think and do? Um? So, as long as nobody else

848
00:44:42,320 --> 00:44:44,640
Speaker 1: can think or would want to know, what I think

849
00:44:44,680 --> 00:44:46,759
Speaker 1: and do. Then to me like, okay, I could be

850
00:44:46,800 --> 00:44:48,520
Speaker 1: a robot or I could not be a robot. Well,

851
00:44:48,520 --> 00:44:50,960
Speaker 1: I think there's an implication of moral responsibility. We've been

852
00:44:51,000 --> 00:44:53,400
Speaker 1: talking about you eating a cookie. What if that was

853
00:44:53,480 --> 00:44:56,920
Speaker 1: somebody else's cookie, right, and you ate that person's cookie,

854
00:44:57,160 --> 00:44:59,600
Speaker 1: Then could you say, Hey, I didn't make that choice.

855
00:44:59,640 --> 00:45:02,000
Speaker 1: I have no free will, and therefore I can't be

856
00:45:02,040 --> 00:45:05,640
Speaker 1: more morally culpable. If everybody is deterministic and people aren't

857
00:45:05,719 --> 00:45:08,680
Speaker 1: making choices, than our sort of whole theory of morality

858
00:45:08,760 --> 00:45:12,000
Speaker 1: kind of falls apart and we can't really punish anybody

859
00:45:12,000 --> 00:45:14,920
Speaker 1: for anything. All right, we'll say that. For our other podcast,

860
00:45:15,000 --> 00:45:18,839
Speaker 1: Daniel and Jorge explain the Moral Universe. Daniel and Jorge

861
00:45:19,160 --> 00:45:21,400
Speaker 1: um blather on about philosophy. They don't really know what

862
00:45:21,440 --> 00:45:24,680
Speaker 1: they're talking about. I would listen to that, and I

863
00:45:24,760 --> 00:45:27,799
Speaker 1: predict that a lot of people will probably not. But

864
00:45:27,840 --> 00:45:29,680
Speaker 1: I think these are, like many of the things that

865
00:45:29,680 --> 00:45:31,879
Speaker 1: we talked about on the show, there are deep implications

866
00:45:31,920 --> 00:45:34,240
Speaker 1: for just what it means to be human being. Often

867
00:45:34,239 --> 00:45:37,319
Speaker 1: we talk about how the universe was created and how

868
00:45:37,360 --> 00:45:39,200
Speaker 1: it came to be in his future, and that has

869
00:45:39,560 --> 00:45:43,000
Speaker 1: deep importance for people, how what people think about their

870
00:45:43,040 --> 00:45:45,279
Speaker 1: place in the cosmos and how they should live their lives.

871
00:45:45,360 --> 00:45:47,840
Speaker 1: And this is similar. It's a question, you know, is

872
00:45:47,840 --> 00:45:50,239
Speaker 1: this the threshold that science will ever cross? And if so,

873
00:45:50,320 --> 00:45:52,600
Speaker 1: what does it mean? And so I love the fact

874
00:45:52,640 --> 00:45:55,719
Speaker 1: that science is so relevant sometimes that everything touches the

875
00:45:55,800 --> 00:45:57,560
Speaker 1: deep core of how you're gonna live your life and

876
00:45:57,600 --> 00:45:59,480
Speaker 1: what it means to be human. Yeah, it's amazing to

877
00:45:59,560 --> 00:46:02,359
Speaker 1: think that physics can have such an impact in who

878
00:46:02,400 --> 00:46:06,520
Speaker 1: we are as a in our souls, in our conception

879
00:46:06,600 --> 00:46:08,640
Speaker 1: of who we are. Well, physics is deep in my

880
00:46:08,680 --> 00:46:11,640
Speaker 1: soul and now maybe you're discovering it's actually deep in

881
00:46:11,719 --> 00:46:16,080
Speaker 1: your soul as well. We got you, We infected your soul,

882
00:46:16,880 --> 00:46:19,880
Speaker 1: dear audience, physics. All right, Well, thanks for joining us.

883
00:46:19,920 --> 00:46:22,279
Speaker 1: We hope you enjoyed that, and we hope that meant

884
00:46:22,320 --> 00:46:25,680
Speaker 1: all of your expectations. But what this podcast was going

885
00:46:25,719 --> 00:46:27,920
Speaker 1: to be, that's right. Thanks for tuning in. And for

886
00:46:27,960 --> 00:46:31,400
Speaker 1: those of you who wonder whether science can actually explain

887
00:46:31,400 --> 00:46:34,239
Speaker 1: the universe, remember that we don't know. Science has worked

888
00:46:34,239 --> 00:46:36,120
Speaker 1: pretty well so far and been able to explain a

889
00:46:36,200 --> 00:46:38,279
Speaker 1: lot of what we've seen, but there might be some

890
00:46:38,360 --> 00:46:40,719
Speaker 1: day in the future where we find some phenomenon that

891
00:46:40,840 --> 00:46:43,800
Speaker 1: can't be explained by science, or by our current visioning

892
00:46:43,840 --> 00:46:47,000
Speaker 1: of science or our mathematical rules. So we are continuing

893
00:46:47,040 --> 00:46:49,600
Speaker 1: on this journey of trying to explore and explain the

894
00:46:49,680 --> 00:46:52,399
Speaker 1: universe we find around us. Thanks for joining us, see

895
00:46:52,400 --> 00:47:02,360
Speaker 1: you next time. Before you still have a question after

896
00:47:02,400 --> 00:47:05,520
Speaker 1: listening to all these explanations, please drop us the line.

897
00:47:05,560 --> 00:47:07,719
Speaker 1: We'd love to hear from you. You can find us

898
00:47:07,719 --> 00:47:11,520
Speaker 1: on Facebook, Twitter, and Instagram at Daniel and Jorge That's

899
00:47:11,560 --> 00:47:14,920
Speaker 1: one Word, or email us at Feedback at Daniel and

900
00:47:15,040 --> 00:47:18,480
Speaker 1: Jorge dot com. Thanks for listening and remember that Daniel

901
00:47:18,520 --> 00:47:21,040
Speaker 1: and Jorge Explain the Universe is a production of I

902
00:47:21,280 --> 00:47:24,719
Speaker 1: Heart Radio. For more podcast from my heart Radio, visit

903
00:47:24,760 --> 00:47:28,239
Speaker 1: the i heart Radio app, Apple Podcasts, or wherever you

904
00:47:28,320 --> 00:47:29,840
Speaker 1: listen to your favorite shows.