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Speaker 1: Hollywood tells us what it's like to make a scientific discovery. Okay,

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Speaker 1: set the scene. A lone scientist wearing a lab coat

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Speaker 1: because they're always wearing a lab coat for some reason,

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Speaker 1: has a flash of inspiration, sometimes during a musical montage,

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Speaker 1: and that's when the ideas come together. He and it's

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Speaker 1: almost always a he rushes out to tell the world

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Speaker 1: and everyone greets the news with enthusiasm. That's a fun

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Speaker 1: bit of storytelling. But what is it really like? Does

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Speaker 1: that scenario ever happen? Or are scientists working slowly for

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Speaker 1: decades pushing the fuzzy bits of the puzzle together until

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Speaker 1: people are finally convinced. And yes, I have to admit

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Speaker 1: that wouldn't make quite as good of a movie. But anyway,

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Speaker 1: today we're going to pull back the curtain on the

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Speaker 1: process of scientific discovery and tell you stories of dramatic

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Speaker 1: as well as frustratingly slow discoveries. You'll hear the actual

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Speaker 1: historical audio of scientists being shocked at a discovery that

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Speaker 1: they were making in real time, a conversation with a

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Speaker 1: historian of science, and an interview with a man who

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Speaker 1: has spoken to more Nobel prize winners than maybe anyone

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Speaker 1: else on the planet, and we'll try to learn what

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Speaker 1: led to moments of understanding and discovery. Welcome to Daniel

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Speaker 1: and Kelly's Extraordinary Universe. Hello. I'm Kelly winder Smith. I

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Speaker 1: study parasites and space, and today we're going to talk

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Speaker 1: about how many times I have not discovered things.

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Speaker 2: Hello.

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Speaker 3: I'm Daniel Whitson. I'm a particle physicist, and I got

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Speaker 3: into particle physics to reveal the fundamental nature of the

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Speaker 3: universe and make earth shattering discoveries. But in thirty years

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Speaker 3: I've made exactly zero.

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Speaker 1: You've made exactly zero. Okay, Well that's a nice lead

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Speaker 1: into the question I have for you today. So you know,

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Speaker 1: at least in my field, and I assume this is

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Speaker 1: the same in your field. Before you start an experiment,

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Speaker 1: you have a prediction, you have an expectation for how

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Speaker 1: the results are going to go, and then you design

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Speaker 1: your experiment well so that if you're wrong, you can

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Speaker 1: be sure that you're wrong. That's a good experiment. So

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Speaker 1: what percent of the time roughly does the work that

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Speaker 1: you do match the predictions that you made initially?

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Speaker 3: Wow, way to put your finger on a source bot, Kelly,

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Speaker 3: So far every single experiment. We've done matches our expectations,

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Speaker 3: and we've even analyzed the statistics of that, Like you

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Speaker 3: don't expect when you flip a coin to get exactly

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Speaker 3: fifty percent heads and tails on a fair coin. You

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Speaker 3: expect some fluctuations, and we see exactly those kinds of fluctuations.

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Speaker 3: Sometimes the data is a little bit weird, rarely it's

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Speaker 3: very weird, and almost never is it super duper weird.

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Speaker 3: So we have a beautiful Gaussian curve of all of

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Speaker 3: our weirdness and really no surprises so far.

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Speaker 1: So every paper you've done, the prediction you were testing,

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Speaker 1: you found exactly what you expected.

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Speaker 3: I mean, I work in a field where if we

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Speaker 3: find something unexpected, it's a Nobel prize. Right. If you

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Speaker 3: find a new particle, if you find a new force,

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Speaker 3: that's a huge revelation. So we are constantly searching for stuff.

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Speaker 3: No we didn't find dark matter, No we didn't find this,

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Speaker 3: No we didn't find that. Ninety nine point ninety nine

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Speaker 3: percent of our papers are negative results. We looked for

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Speaker 3: X and we didn't see it. The standard model wins again.

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Speaker 1: Well, congratulations for being right on thousands of papers, Like

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Speaker 1: you told us the other day you have thousands of publications.

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Speaker 3: No, no, it's a great disappointment. I wish that we

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Speaker 3: were wrong. I got into this field to prove the

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Speaker 3: standard model wrong, to find situations where we see something

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Speaker 3: we don't expect, and not just to discover something new. Right,

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Speaker 3: some theorists could come up with a model of supersymmetry

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Speaker 3: and predict the selectron or whatever, and we could go

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Speaker 3: off and see that. That's sort of what happened with

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Speaker 3: the Higgs boson and with the top quark twenty years earlier.

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Speaker 3: But it's been a long time since we had a surprise,

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Speaker 3: a moment when the data told us something about the

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Speaker 3: universe we weren't expecting.

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Speaker 1: Well, Daniel, I'm excited that I can say to you

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Speaker 1: that I wish you failure.

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Speaker 3: There you go exactly. What about you? How about your

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Speaker 3: great moments of discovery where they unexpected or expected.

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Speaker 1: I think I'm at like fifty to fifty on my

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Speaker 1: predictions panning out, like I mean, so it's it's not

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Speaker 1: a like coin flip. I actually, you know, I do

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Speaker 1: serious literature searches, but you know, when you study animal behaviors,

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Speaker 1: so often it's like, oh, you know, we know that

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Speaker 1: the neurotransmitters are doing this, so we should predict that

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Speaker 1: the animal will do this, and then they don't do

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Speaker 1: what you expected. And that's pretty typical as we sort

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Speaker 1: of muddle through neuroscience and whatnot.

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Speaker 3: Well, when that happens, when they don't do what you expect,

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Speaker 3: have you learned something about the animal, something fundamental that

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Speaker 3: is scientific, or have you learned oops, I made a mistake,

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Speaker 3: or I don't know how to do neuroscience or something.

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Speaker 1: No, we always learn something like I do. I spend

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Speaker 1: a lot of time. I'm carefully designing my experiments so

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Speaker 1: that even if the answer is things didn't go the

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Speaker 1: way you thought they would, there's still something interesting to.

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Speaker 3: Say, Well, that's a well designed experiment. Congratulations, Oh thanks,

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Speaker 3: we published No matter what.

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Speaker 1: That's right. Well, I've gotten very comfortable with this form

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Speaker 1: of failure, and.

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Speaker 3: The success and failure of scientists is part of our

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Speaker 3: topic today. We are doing a deep dive into the

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Speaker 3: nature of the scientific process, pulling back the curtain on

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Speaker 3: how science actually works. What scientists do all day. We

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Speaker 3: don't just take naps and wake up with great moments

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Speaker 3: of inspiration, though I guess that does happen for some

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Speaker 3: of us. We work slowly and carefully through the process

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Speaker 3: of science, figuring out how the universe works and convincing

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Speaker 3: our peers of what we have learned. We have an

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Speaker 3: episode later this week on the scientific review process, but

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Speaker 3: today we're digging into the juiciest bit how scientific discoveries

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Speaker 3: actually happen.

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Speaker 1: And we are super lucky to have a bunch of

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Speaker 1: different input for this particular episode. We're going to start

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Speaker 1: with Daniel walking us through what discovery tends to look

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Speaker 1: like in physics. Then we're going to bring an expert

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Speaker 1: on to talk to us about the history of scientific discoveries,

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Speaker 1: and finally we're talking to someone who interviewed a bunch

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Speaker 1: of Nobel Prize winners and asked them about their discoveries

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Speaker 1: and how that went along. So Daniel on this path

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Speaker 1: of discovery. Maybe this should be a self help podcast

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Speaker 1: now it feels self healthy right now.

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Speaker 3: But how to win a Nobel Prize Steps one through ten.

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Speaker 3: You'll be shocked at step seven.

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Speaker 1: Well, let's start with your first discovery that you want

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Speaker 1: to tell us about today.

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Speaker 3: Yeah, I think it's important to walk through some examples

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Speaker 3: of discoveries because I think that the picture people have

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Speaker 3: in their minds of how scientific discovery happens is shaped

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Speaker 3: by a lot of these stories, most of which are

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Speaker 3: apocryphal and give people sort of a cartoonish view of

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Speaker 3: the process. And I want to get into the nitty gritty.

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Speaker 1: So I have to make a confession here, which is

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Speaker 1: that for a long time I didn't realize that apocryphal

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Speaker 1: means a story that isn't true. Oh no, So I'd

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Speaker 1: just like to clear that up for anyone who is

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Speaker 1: comparably bad at the English language.

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Speaker 3: These are great dinner party stories or popsy clickbait, but

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Speaker 3: they're not always real. And maybe one of the most

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Speaker 3: famous moments of discovery is Newton and the Apple. As

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Speaker 3: the story goes, Newton is sitting in his garden. He

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Speaker 3: sees an apple fall down, and he thinks about it

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Speaker 3: deep and he goes, hmmm, why do apples fall down

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Speaker 3: towards the center of the earth? And he comes up

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Speaker 3: with this theory of gravity. Is that the story you've heard, Kelly?

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Speaker 1: Absolutely?

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Speaker 3: And does that story make sense to you? Like, how

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Speaker 3: does looking at an apple tell anybody how gravity works?

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Speaker 1: I mean, I guess I didn't imagine that he looked

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Speaker 1: at the apple and immediately knew how gravity works. I

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Speaker 1: imagined that he saw the apple fall and thought to himself,

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Speaker 1: why did it go down and not up? And that

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Speaker 1: got him sort of thinking about the question more deeply.

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Speaker 3: Well, you know, that's a question that Aristotle worked on

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Speaker 3: thousands of years earlier, like why do things fall down?

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Speaker 3: It was a deep question, and you know, his answer

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Speaker 3: was like, well, there's some things it's in their nature

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Speaker 3: to fall down, and an apple and rocks and earth

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Speaker 3: are made of the falling down kind of stuff. And

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Speaker 3: that's not really an answer, you know, but this definitely

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Speaker 3: has been a question for a long long time. And

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Speaker 3: so it doesn't even really make sense to me, because

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Speaker 3: like seeing the apple inspires the question, but the question

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Speaker 3: is an ancient and outstanding one. Anyway, this whole story

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Speaker 3: doesn't make any sense because it's all made up. It

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Speaker 3: didn't really happen that way at all. The real story

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Speaker 3: is that Newton took years, decades to develop his theory

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Speaker 3: of gravity. He was writing letters back and forth with

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Speaker 3: another scientist, Hook for years, and he was thinking about gravity,

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Speaker 3: and he was wondering if you could come up with

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Speaker 3: a theory of gravity to explain why apples fall down,

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Speaker 3: and also why the moon doesn't fall down? Right, like

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Speaker 3: why is the moon in orbit around the Earth? This

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Speaker 3: kind of stuff, And so he was trying to develop that,

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Speaker 3: and he was trying to make it mathematical. He didn't

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Speaker 3: want just a story like Aristotle provided. He wanted a theory,

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Speaker 3: something that would let you calculate the force between two objects,

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Speaker 3: for example. And so it took him two decades to

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Speaker 3: put this theory together. And the you know, the fundamental

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Speaker 3: idea he came up with is that gravity gets weaker

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Speaker 3: with distance. And he showed that if you framed it

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Speaker 3: in this one over are squared or are as the

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Speaker 3: distance between objects, the force drops with a distance squared,

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Speaker 3: that you could actually calculate not just that an apple

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Speaker 3: should fall, but also that the moon should be in

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Speaker 3: its orbit. And he was able to reproduce the motion

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Speaker 3: of the moon. And this is the great triumph to

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Speaker 3: have a single theory of gravity that describes not just

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Speaker 3: what's happening on Earth, but also in the heavens.

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Speaker 1: All right, Well, so first I'm wondering with the Aristotle

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Speaker 1: and the birds. Did he think that the that birds

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Speaker 1: were like made of uppy stuff sometimes and downy stuff others,

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Speaker 1: and like what did this transmogrification look like? But let's

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Speaker 1: not get too far off topic.

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Speaker 3: I would love to have Aristotle on the podcast him

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Speaker 3: some of these questions, you know, also questions like why

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Speaker 3: didn't you ever do an experiment to try out some

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Speaker 3: of your ideas? Like in ten minutes, Galileo disproved a

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Speaker 3: lot of Aristontal's ideas just by doing experiments.

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Speaker 4: Well.

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Speaker 1: I was looking at the New York Times Bestseller's paperback

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Speaker 1: list the other day, and a book that beat mine

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Speaker 1: is one where a medium is giving you advice from

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Speaker 1: the dead. So maybe we can there's some people we

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Speaker 1: can reach out to you to make that happen.

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Speaker 3: But that's nonfiction.

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Speaker 1: That's in the nonfiction. Yeah, I know, so anyway, but

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Speaker 1: and it beat me fai But anyway.

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Speaker 3: So, but you guys are on the nonfiction bestseller list.

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Speaker 4: How we are.

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Speaker 3: Congrats?

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Speaker 1: Thanks, it'll be it. It won't be top secret by

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Speaker 1: the time the episode comes out, but we're on eleven.

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Speaker 1: And Ada will point out that we didn't break the

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Speaker 1: top ten, which is what she does every time I

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Speaker 1: mentioned that we're on the New York Times bestsellers list.

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Speaker 3: Oh my god, that's huge. Wow, wonderful.

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Speaker 5: Thanks.

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Speaker 1: Anyway, would be nice if I was above the medium person,

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Speaker 1: but I'm not.

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Speaker 3: But anyway, okay, So well, that gives you a very

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Speaker 3: nice cocktail story to tell when next time you go

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Speaker 3: to a fancy party. And this is what happened with Newton. Oh,

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Speaker 3: Newton developed his theory of gravity, and then he told

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Speaker 3: this story at like parties where it's like I saw

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Speaker 3: the apple and I had a moment of inspiration. And

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Speaker 3: so this is Newton basically writing clickbait. And then the

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Speaker 3: story got around and Voltaire heard about it. He's a

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Speaker 3: famous writer, and he wrote about it, and that's what

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Speaker 3: popularized it. And so Newton sort of like wrote a

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Speaker 3: pr pitch about his moment of inspiration that didn't really happen,

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Speaker 3: and then it got propagated by the mainstream media, which

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Speaker 3: was Voltaire at the time.

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Speaker 1: Amazing, How do we know that this didn't really happen

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Speaker 1: to Newton if he said it did?

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Speaker 3: Well, we have records of Newton's work, right, Like the

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Speaker 3: dude kept logbooks and we have his letters, and we

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Speaker 3: see him struggling with these concepts together with Hook over years.

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Speaker 3: And then it was twenty years later that his theory

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Speaker 3: was fully developed. So we see the development of it

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Speaker 3: in his notes and in his letters.

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Speaker 1: Huh, all right, fantastic. I didn't expect Voltaire to come

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Speaker 1: into our episode today, but there he is.

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Speaker 3: Yeah. Well, that's because this is the best of all

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Speaker 3: possible podcasts.

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Speaker 1: Oh my god, us you're so right, you're so right.

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Speaker 1: All right. So while people are discovering that this is

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Speaker 1: the best podcast ever, let's move on to another amazing

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Speaker 1: bombshell of a discovery about radioactivity.

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Speaker 3: So here's a moment of discovery that really is sort

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Speaker 3: of like the cartoon. There's an accident which leads to

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Speaker 3: a moment of inspiration and then like very rapidly, publication

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Speaker 3: and awards.

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Speaker 1: Just real quick to say, you usually don't want the

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Speaker 1: words accident and radioactivity in the same sentence. So I'm

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Speaker 1: hoping this accidental discovery didn't end anyone's life.

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Speaker 3: Pretty sure everybody involved in early radiation discovery's got cancer.

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Speaker 3: Oh sometimes several times.

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Speaker 1: All right, you're the downer today.

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Speaker 3: All right, speaking of X rays and cancer, some listener

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Speaker 3: wrote in recently and told me that until fairly recently,

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Speaker 3: you could go to a shoe store and get a

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Speaker 3: very intense X ray of your foot to make sure

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Speaker 3: your shoe is sized correctly.

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Speaker 1: Huh yeah, do not recommend.

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Speaker 3: Do not recommend, absolutely not. Anyway, Becherel is credited with

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Speaker 3: the discovery of radioactivity, specifically in uranium, and this comes

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Speaker 3: quick on the heels of Runken's discovery of X rays,

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Speaker 3: which was also an accident. We can dig into that

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Speaker 3: another time. But X rays with a new thing. Everybody

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Speaker 3: was excited about X rays and becherrel knew that uranium,

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Speaker 3: if you left it near photographic plates, would leave an

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Speaker 3: imprint on the plate. So, for example, uranium crystal and

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Speaker 3: you put it on top of the plate, that it

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Speaker 3: would leave the shape of the crystal onto the plate.

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Speaker 3: And he was wondering how this worked, and he actually

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Speaker 3: had the totally wrong theory. He thought that uranium was

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Speaker 3: absorbing sunlight and emitting X rays because X rays with

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Speaker 3: this new exciting thing, and so he thought, maybe that's

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Speaker 3: what's happening, and so he wanted to do this experiment

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Speaker 3: where he wrapped photographic plates in paper so that visible

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Speaker 3: light didn't hit them, and then he would put a

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Speaker 3: block of uranium on top of that, and they put

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Speaker 3: the whole thing out in the sunlight. And the idea

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Speaker 3: was the uranium would absorb sunlight amid X rays which

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Speaker 3: would go through the paper and leave an imprint on

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Speaker 3: the plate. That was his big experiment. Okay, but it

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Speaker 3: was cloudy in Paris, right, Paris did not cooperate with

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Speaker 3: his plans. His experiment needed sunlight, so he put the

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Speaker 3: whole thing in a drawer over the weekend, and he

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Speaker 3: came back after the weekend and he decided to develop

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Speaker 3: the photographic plate, even though he hadn't put it out

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Speaker 3: in the sunlight. And what he saw was a perfect

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Speaker 3: picture of the uranium crystal, even though there hadn't been

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Speaker 3: any sunlight. And that's when he realized, Oh, the uranium

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Speaker 3: is actually just generating radiation on its own. It doesn't

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Speaker 3: require sunlight, and it wasn't X rays, and so this

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Speaker 3: is like his moment of discovery. He realized, Wow, this

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Speaker 3: uranium is generating something on its own. He reported it

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Speaker 3: the very next day to like the Academic Society and

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Speaker 3: then won the Nobel Prize for it.

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Speaker 1: WHOA, I wonder why he decided to develop the photographic

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Speaker 1: plate anyway, Yeah.

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Speaker 3: People asked him this and he was just like, I

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Speaker 3: don't know on a hunch. I just was wondering, you know,

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Speaker 3: just like curiosity.

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Speaker 1: Wow. Yeah, that is amazingly lucky.

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Speaker 3: It's very lucky. Yeah, absolutely, And he's also very lucky

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Speaker 3: because it turns out that somebody else did the same

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Speaker 3: thing forty years earlier and wrote it up and reported

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Speaker 3: it and was just totally ignored.

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Speaker 1: Oh no, And did Becquerel cite this other guy.

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Speaker 3: No, it was just like lost in the literature. You know,

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Speaker 3: how you've done something and then you think it's clever,

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Speaker 3: and then you discovered that some Soviet dude did it

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Speaker 3: in nineteen seventy eight much better than you did.

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Speaker 1: Happens to me all the time.

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Speaker 3: That's because we have good literature searches and they didn't

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Speaker 3: at that time. And so yeah, but this was really

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Speaker 3: a moment write an accident. Very quickly becherel realized what

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Speaker 3: it meant, and it changed our understanding of the whole

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Speaker 3: microscopic world. And this led to Curi's experiments and the

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Speaker 3: foundation of quantum mechanics.

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Speaker 4: Yeah.

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Speaker 1: So I always thought that Kuri discovered radioactivity. Can you

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Speaker 1: quickly tell us what it was that she discovered in particular?

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Speaker 3: Right? So, Curi discovered two new radioactive elements. Right, Becquerel

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Speaker 3: discovered radioactivity from uranium salts. Curi discovered polonium and radium.

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Speaker 3: She actually coined the term radioactivity. And Curi's real insight

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Speaker 3: is that radioactivity is an atomic property, not chemical one.

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Speaker 3: It's not like you got atoms bumping together and emitting

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Speaker 3: something due to some reaction. It's something inside the atom

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Speaker 3: that's happening.

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Speaker 1: Okay, awesome. So next I see that we're talking about

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Speaker 1: the m M experiment, which makes me think about eminem's

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Speaker 1: and now I'm hungry. Is this experiment delicious?

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Speaker 3: Yes, this is the experiment to discover whether different colors

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Speaker 3: of eminems actually have different flavors and.

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Speaker 1: Why they melt in your mouth but not in your hand,

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Speaker 1: which side note absolutely.

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Speaker 3: No, No, this is the Michael Sinmoreley experiment, the famous

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Speaker 3: experiment that taught us that light travels the same speed

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Speaker 3: for all observers and disproved the existence of the ether.

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Speaker 4: Oh.

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Speaker 1: That's important.

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Speaker 3: It's important, and it's often told as this groundbreaking experiment

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Speaker 3: which pivoted our understanding of the universe. And it's true

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Speaker 3: that this was an unexpected result and it proves something

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Speaker 3: really important about the universe. But contrary to the popular lore,

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Speaker 3: it's not something that was widely understood or appreciated at

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Speaker 3: the time. It's a little bit revisionist history to go

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Speaker 3: back and say, oh, yeah, this experiment happened, and then

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Speaker 3: everybody changed their mind.

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Speaker 1: Oh so this experiment happened. Nobody changed their mind because

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Speaker 1: they ignored it, just like the last guy who discovered radioactivity,

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Speaker 1: whose name I think we managed to not even say.

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Speaker 6: So.

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Speaker 1: Take that guy who did it first.

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Speaker 3: That was Abel, the Saint Victor, who discovered radioactivity forty

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Speaker 3: years before Becquerel, but was ignored by the Nobel Committee.

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Speaker 1: But we've just said it straight.

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Speaker 3: Yeah, and that's not exactly what happened here. People were

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Speaker 3: aware of this experiment. They just really struggled to digest

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Speaker 3: this bizarre concept that like could travel without a medium.

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Speaker 3: And so let's go back to eighteen eighty seven when

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Speaker 3: this experiment happened. Back then, we had interference experiments and

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Speaker 3: diffraction studies. We had all this data showing that light

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Speaker 3: was a wave, and Maxwell had his equations that described

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Speaker 3: light as ripples in electromagnetism. But they were wondering, like,

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Speaker 3: what is it a ripple in you know like sound

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Speaker 3: is a ripple in air, and water waves are obviously

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Speaker 3: ripples in water. But what is light propagating through you?

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Speaker 3: This velocity that we see should be relative to some

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Speaker 3: medium if light is the same kind of thing as

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Speaker 3: everything else we've studied. And so Michael Sen Morley did

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Speaker 3: this experiment to try to detect that medium. They said, well,

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Speaker 3: if light is moving through some medium, let's call it

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Speaker 3: the ether, and it fills the universe, the Earth is

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Speaker 3: also moving through it because the Earth goes around the Sun.

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Speaker 3: And so as the Earth goes around the Sun, we

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Speaker 3: should see different velocities of the speed of light because

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Speaker 3: we have a different velocity relative to the ether. And

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Speaker 3: so they did this cool experiment with interferometers where they

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Speaker 3: had a light beam and they split it and it

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Speaker 3: went into perpendicular directions and then came back. And they

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Speaker 3: were very sensitive to small differences because of their cool

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Speaker 3: optics and interferometry, and they expected when they did the

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Speaker 3: experiment in spring and in summer and in fall and

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Speaker 3: in winter, they would get different results and they could

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Speaker 3: measure our velocity through the ether. But what they found

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Speaker 3: was no difference. That there was never any difference in

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Speaker 3: how long it took light to go go one direction

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Speaker 3: or the other, and this was totally insensitive to the

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Speaker 3: time of year, and they it was really an amazing experiment,

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Speaker 3: like the detail they put in it to make this

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Speaker 3: thing super sensitive, and so they found nothing, and that

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Speaker 3: was very confusing. Like obviously now in hindsight, the conclusion

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Speaker 3: is there is no ether, and light moves to the

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Speaker 3: same velocity regardless of the observer, and it's a propagation

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Speaker 3: of electromagnetic waves through space itself. We know that now,

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Speaker 3: but it's not fair to say, like we thought there

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Speaker 3: was an ether. We had Michael Simmore the experiment. The

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Speaker 3: next day it was like, yeah, let's move on. Obviously

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Speaker 3: there's no ether. Instead, people clung to the ether hypothesis

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Speaker 3: for a long time. They thought, maybe there's a blob

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Speaker 3: of ether and the Earth is dragging it along with it,

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Speaker 3: so we can't detect our velocity relative to the ether

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Speaker 3: because we're like in a little pocket of ether. And

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Speaker 3: we had to do all sorts of other studies to

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Speaker 3: disprove that by looking at like the angles of stars

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Speaker 3: and how they changed through the year. And so it

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Speaker 3: wasn't widely accepted until after Einstein's theory of relative nineteen

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Speaker 3: oh five, So this is twenty years later. Einstein comes

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Speaker 3: up with this theoretical explanation for this experiment, which brings

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Speaker 3: it all together and finally makes it all make sense.

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Speaker 3: And it wasn't until then that everybody's like, Okay, yeah,

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Speaker 3: I can put this together and this is the way

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Speaker 3: the universe works. Really, the physics establishment was like, well,

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Speaker 3: that was a strange experiment. We don't understand it. Let's

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Speaker 3: put it in the HM category until we figure it out.

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Speaker 1: Well, one, I think it's nice that they at least

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Speaker 1: paid attention to it, even if they put it in

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Speaker 1: the HUM category. It was red, so that's good. But

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Speaker 1: did Eminem survive until nineteen oh five to see the

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Speaker 1: work validated? Oh, good question, because it would have been

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Speaker 1: a delicious moment to know that you were right.

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Speaker 3: Yes, both of them lived on for decades longer, so

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Speaker 3: they definitely saw the theory of relativity become widely accepted.

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Speaker 7: Ah.

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Speaker 1: I love hearing that scientists get validation within their lifetime.

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Speaker 1: That's a good feeling. All right, let's take a break

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Speaker 1: and we'll talk about another discovery before bringing on our

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Speaker 1: other experts. All right, So in our last experiment, our

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Speaker 1: scientists were deliciously validated. Who is the next scientist we're

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Speaker 1: going to talk about?

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Speaker 3: So we're going to talk about another famous discovery, that

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Speaker 3: of pulsars by Joscelyn Bell Burnell. This is a really

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Speaker 3: fun story, but there's a nuance here that I think

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Speaker 3: is not widely appreciated, which is again, how long it

437
00:21:37,560 --> 00:21:42,000
Speaker 3: took to really accept this sort of surprising result. Jocelyn

438
00:21:42,040 --> 00:21:45,359
Speaker 3: Bell Burnell was a graduate student. She was studying quasars.

439
00:21:45,359 --> 00:21:48,159
Speaker 3: She was not out to look for pulsars. She was

440
00:21:48,200 --> 00:21:52,160
Speaker 3: looking for these huge jets that shoot out of black holes.

441
00:21:52,480 --> 00:21:54,720
Speaker 3: So black holes at the center of galaxies have accretion

442
00:21:54,840 --> 00:21:57,879
Speaker 3: disks stuff that's swirling around them, but they also shoot

443
00:21:57,920 --> 00:22:01,000
Speaker 3: material up their north and south pole. And these things

444
00:22:01,040 --> 00:22:04,760
Speaker 3: are called quasars, are super duper bright and for a

445
00:22:04,760 --> 00:22:07,400
Speaker 3: long time not really understood because nobody could understand where

446
00:22:07,440 --> 00:22:10,920
Speaker 3: the energy for creating such a bright source was coming from.

447
00:22:11,480 --> 00:22:13,840
Speaker 3: And she was studying these and wanting to understand their

448
00:22:13,920 --> 00:22:17,200
Speaker 3: time variation. Like you know how a star twinkles because

449
00:22:17,200 --> 00:22:20,679
Speaker 3: it goes through the atmosphere, These quasars radiate in the

450
00:22:20,800 --> 00:22:24,680
Speaker 3: radio spectrum, and she was looking for their scintillation due

451
00:22:24,680 --> 00:22:28,040
Speaker 3: to the interaction with the solar wind like particles in space.

452
00:22:28,720 --> 00:22:32,200
Speaker 3: So she built this huge radio telescope. And a radio

453
00:22:32,200 --> 00:22:34,399
Speaker 3: telescope is not like a telescope you looked through with

454
00:22:34,440 --> 00:22:37,960
Speaker 3: your eyeball. It's more like a huge antenna. And she

455
00:22:38,200 --> 00:22:40,960
Speaker 3: rolled out one hundred and twenty miles of wire over

456
00:22:41,040 --> 00:22:43,600
Speaker 3: like four and a half acres to build this big

457
00:22:43,720 --> 00:22:47,080
Speaker 3: radio antenna to capture this information and to try to

458
00:22:47,160 --> 00:22:48,320
Speaker 3: understand quasars.

459
00:22:48,560 --> 00:22:53,240
Speaker 1: You know, sometimes graduate students do just like absolute mind

460
00:22:53,720 --> 00:22:56,639
Speaker 1: blowing quantities of work, Like I imagine it took a

461
00:22:56,720 --> 00:22:59,960
Speaker 1: long time to lay all of that out. So oh yeah,

462
00:23:00,040 --> 00:23:01,720
Speaker 1: shout out to the grad students out there.

463
00:23:01,920 --> 00:23:04,320
Speaker 3: I know she did all the work on this. She

464
00:23:04,359 --> 00:23:07,920
Speaker 3: spent two years just building this telescope. And the data

465
00:23:07,960 --> 00:23:11,040
Speaker 3: is hilariously old fashioned. You know. You might imagine you're

466
00:23:11,040 --> 00:23:13,359
Speaker 3: sitting in your laptop, the data comes in, you're analyzing

467
00:23:13,400 --> 00:23:16,560
Speaker 3: it with some cool visuals. She had a printer which

468
00:23:16,600 --> 00:23:19,320
Speaker 3: produced one hundred feet of paper per day with the

469
00:23:19,400 --> 00:23:22,320
Speaker 3: data on it, and she like visually analyzed it and

470
00:23:22,359 --> 00:23:23,760
Speaker 3: looked for stuff like this.

471
00:23:24,000 --> 00:23:24,320
Speaker 7: Wow.

472
00:23:24,680 --> 00:23:28,440
Speaker 3: And on November twenty eighth, nineteen sixty seven, while looking

473
00:23:28,440 --> 00:23:33,280
Speaker 3: for Quasars. She saw something weird. She saw pulses separated

474
00:23:33,320 --> 00:23:36,919
Speaker 3: by regular time intervals from one location. So it's like

475
00:23:37,320 --> 00:23:41,440
Speaker 3: beep beep, beep beep, and this is really weird, right,

476
00:23:41,640 --> 00:23:43,399
Speaker 3: this is not the kind of thing you expect to

477
00:23:43,440 --> 00:23:46,040
Speaker 3: hear from the universe. You might expect to hear it

478
00:23:46,040 --> 00:23:50,760
Speaker 3: from like satellites or from radios or other artificial sources.

479
00:23:51,480 --> 00:23:53,560
Speaker 3: And so at first she nicknamed it in her notes

480
00:23:53,920 --> 00:23:57,800
Speaker 3: LGM one for Little Green Men. She was like, am

481
00:23:57,880 --> 00:24:01,159
Speaker 3: I getting signals from aliens? Here have I received the

482
00:24:01,200 --> 00:24:03,160
Speaker 3: first interstellar transmission.

483
00:24:03,359 --> 00:24:06,600
Speaker 1: It's interesting that the Little Green Men troope was around

484
00:24:06,640 --> 00:24:08,480
Speaker 1: that early. I guess I hadn't realized that we've been

485
00:24:08,480 --> 00:24:12,080
Speaker 1: imagining aliens as little green news for that long.

486
00:24:12,720 --> 00:24:15,200
Speaker 3: I think it comes from the history of like badly

487
00:24:15,200 --> 00:24:17,639
Speaker 3: informed fiction about life on Mars, doesn't it.

488
00:24:17,760 --> 00:24:20,639
Speaker 1: Oh, I don't know, Yeah, there's an episode we should do.

489
00:24:20,840 --> 00:24:22,480
Speaker 3: And so she was wondering, like, well, what are the

490
00:24:22,560 --> 00:24:27,560
Speaker 3: possible explanations for this other than alien's right, And so

491
00:24:27,640 --> 00:24:30,400
Speaker 3: they went through all sorts of cross checks to try

492
00:24:30,440 --> 00:24:32,920
Speaker 3: to understand what this is. So this is not like

493
00:24:33,040 --> 00:24:36,520
Speaker 3: Becquarel where she discovers this. She understands immediately what it is,

494
00:24:36,600 --> 00:24:39,119
Speaker 3: she goes and publishes it and then wins the Nobel Prize.

495
00:24:39,440 --> 00:24:42,720
Speaker 3: Now instead, she spent months thinking about ways she could

496
00:24:42,720 --> 00:24:46,640
Speaker 3: be fooling herself, Like, could this be signals reflected off

497
00:24:46,640 --> 00:24:49,119
Speaker 3: the moon? Right? Could this just be something from an

498
00:24:49,200 --> 00:24:52,399
Speaker 3: orbiting satellite. Could be like an effect from a big

499
00:24:52,440 --> 00:24:56,360
Speaker 3: building near the telescope, that's like gathering and focusing radio waves.

500
00:24:56,560 --> 00:24:58,680
Speaker 3: She thought about all of these things and like this

501
00:24:58,880 --> 00:24:59,520
Speaker 3: is good.

502
00:24:59,320 --> 00:25:00,719
Speaker 1: Science, right, yeah, good for her.

503
00:25:00,800 --> 00:25:03,280
Speaker 3: Think about all the ways that you could be fooling yourself,

504
00:25:03,320 --> 00:25:05,840
Speaker 3: because she didn't want to embarrass herself go off and

505
00:25:05,840 --> 00:25:07,880
Speaker 3: publish a paper about aliens. And then it turns out

506
00:25:07,960 --> 00:25:09,320
Speaker 3: it was just a tea kettle.

507
00:25:09,040 --> 00:25:11,879
Speaker 1: In the lounge, right, yeah, yeah, that would be embarrassing.

508
00:25:12,240 --> 00:25:14,960
Speaker 3: But finally it was confirmed with another radio telescope, so

509
00:25:15,040 --> 00:25:18,199
Speaker 3: she knew it wasn't instrumentation. But this took months. It

510
00:25:18,240 --> 00:25:21,480
Speaker 3: took a long time, and then finally people understood also

511
00:25:21,840 --> 00:25:24,560
Speaker 3: that it really was a signal, But it wasn't aliens.

512
00:25:24,840 --> 00:25:28,000
Speaker 3: These were just super fast spinning neutron stars that emit

513
00:25:28,080 --> 00:25:31,240
Speaker 3: beams along their poles, and then their poles sweep across

514
00:25:31,240 --> 00:25:34,080
Speaker 3: the surface of the earth leaving these regular blips in

515
00:25:34,119 --> 00:25:37,399
Speaker 3: the radio. So really an amazing and very important discovery

516
00:25:37,640 --> 00:25:40,520
Speaker 3: for which her advisor won the Nobel Prize. And she

517
00:25:40,680 --> 00:25:41,760
Speaker 3: didn't know.

518
00:25:41,960 --> 00:25:44,240
Speaker 1: That's what I was gonna guess. Is one of those

519
00:25:44,240 --> 00:25:47,760
Speaker 1: stories where the woman's advisor gets the credit. Ah cud.

520
00:25:48,040 --> 00:25:50,679
Speaker 3: Yeah, And she is so classy. She came to UCI

521
00:25:50,840 --> 00:25:53,880
Speaker 3: and talked about this, and she is very classy and

522
00:25:54,200 --> 00:25:55,080
Speaker 3: not bitter at all.

523
00:25:55,240 --> 00:25:55,840
Speaker 1: That's for her.

524
00:25:56,000 --> 00:25:57,600
Speaker 3: Anyway. It's a good story.

525
00:25:57,720 --> 00:26:01,240
Speaker 1: Well, it's an awful story, but a good Yeah, she

526
00:26:01,320 --> 00:26:02,080
Speaker 1: did great.

527
00:26:02,080 --> 00:26:04,720
Speaker 3: She's handled it very well. Yeah, okay, exactly, and a

528
00:26:04,800 --> 00:26:07,920
Speaker 3: really fascinating discovery and one that really took a long

529
00:26:08,000 --> 00:26:10,880
Speaker 3: time to verify that this is real, right, And that's

530
00:26:10,920 --> 00:26:13,000
Speaker 3: the thing I want people to understand, is like it's

531
00:26:13,160 --> 00:26:15,760
Speaker 3: very rare to have a moment where it's obvious that

532
00:26:15,800 --> 00:26:18,320
Speaker 3: you've discovered something and you really don't need to do

533
00:26:18,359 --> 00:26:21,360
Speaker 3: any other cross checks. But it does happen, and very

534
00:26:21,440 --> 00:26:24,640
Speaker 3: soon after the discovery of the pulsars, there was exactly

535
00:26:24,680 --> 00:26:28,120
Speaker 3: this kind of discovery. And while these folks were making

536
00:26:28,160 --> 00:26:31,840
Speaker 3: their discovery, they accidentally left a tape recorder on what

537
00:26:32,240 --> 00:26:35,560
Speaker 3: so we have audio you're gonna hear of folks making

538
00:26:35,600 --> 00:26:37,720
Speaker 3: a mind blowing discovery in real time.

539
00:26:37,840 --> 00:26:38,600
Speaker 1: Oh that's awesome.

540
00:26:38,800 --> 00:26:42,440
Speaker 3: So this story starts with Bell's discovery of the pulsars, right,

541
00:26:42,440 --> 00:26:45,320
Speaker 3: but these are in the radio, and people were wondering, like,

542
00:26:45,840 --> 00:26:49,160
Speaker 3: could you also have pulsars that are in the optical

543
00:26:49,160 --> 00:26:52,440
Speaker 3: that you could like see in a telescope. So John

544
00:26:52,520 --> 00:26:56,080
Speaker 3: Cock and Mike Disney were two theorists. These are not astronomers.

545
00:26:56,119 --> 00:26:58,399
Speaker 3: They didn't like know how to operate a telescope or

546
00:26:58,640 --> 00:27:01,600
Speaker 3: do data analysis. They were like, well, this is possible.

547
00:27:01,680 --> 00:27:03,359
Speaker 3: Let's give this a try. Let's go out there and

548
00:27:03,359 --> 00:27:07,119
Speaker 3: try some experiments. And so they got some time on

549
00:27:07,160 --> 00:27:09,600
Speaker 3: a telescope at kit Peek near Tucson, which is a

550
00:27:09,640 --> 00:27:11,600
Speaker 3: gorgeous place and anyone in Arizona should go up to

551
00:27:11,680 --> 00:27:14,600
Speaker 3: kit Peak. And they set up this machinery to convert

552
00:27:14,600 --> 00:27:17,720
Speaker 3: the flashes into ticks and then listen to it, which

553
00:27:17,720 --> 00:27:20,119
Speaker 3: is why they had a tape recorder going. But then

554
00:27:20,160 --> 00:27:22,320
Speaker 3: they converted the tics into frequency, and so they were

555
00:27:22,320 --> 00:27:24,719
Speaker 3: looking for a pulse on their a silloscope, looking for

556
00:27:24,760 --> 00:27:27,520
Speaker 3: like a little peak on their selescope. And they thought

557
00:27:27,520 --> 00:27:29,000
Speaker 3: they had it all set up, and they went up

558
00:27:29,000 --> 00:27:30,520
Speaker 3: there and they tried it and they saw nothing, and

559
00:27:30,520 --> 00:27:33,320
Speaker 3: they were very disappointed. And they had two more days

560
00:27:33,359 --> 00:27:35,920
Speaker 3: to do observations, and those two days were both cloudy,

561
00:27:36,119 --> 00:27:38,679
Speaker 3: so they lost out. And while it was cloudy, they

562
00:27:38,720 --> 00:27:40,320
Speaker 3: were going for walks and thinking about it, and they

563
00:27:40,359 --> 00:27:42,879
Speaker 3: realized they had a mistake in their calculation. They were

564
00:27:42,880 --> 00:27:45,480
Speaker 3: looking in the wrong place. But they didn't have any

565
00:27:45,480 --> 00:27:49,000
Speaker 3: more time. Oh no, Fortunately the next guy on the

566
00:27:49,000 --> 00:27:51,000
Speaker 3: telescope got sick and so he had to give up

567
00:27:51,040 --> 00:27:54,000
Speaker 3: his time. So they had one more night, and so

568
00:27:54,040 --> 00:27:56,760
Speaker 3: they went and they tried their new calculations, and they

569
00:27:56,760 --> 00:27:58,879
Speaker 3: plugged the thing in, and you know, they're just like

570
00:27:58,920 --> 00:28:01,399
Speaker 3: getting started. They just plug it in, turn it on. Okay,

571
00:28:01,480 --> 00:28:04,600
Speaker 3: let's get going. They didn't really expect to see something.

572
00:28:04,960 --> 00:28:08,000
Speaker 3: And as you'll hear in this audio, they're really surprised

573
00:28:08,040 --> 00:28:10,560
Speaker 3: to be making this discovery. So here it is the

574
00:28:10,600 --> 00:28:11,960
Speaker 3: audio of their discovery.

575
00:28:12,680 --> 00:28:18,000
Speaker 4: This next observation will be observation number eighteen. You've got

576
00:28:18,000 --> 00:28:27,280
Speaker 4: a bleeding pulse here. Hey, wow, you don't suppose that's

577
00:28:27,280 --> 00:28:27,760
Speaker 4: really working.

578
00:28:27,800 --> 00:28:31,800
Speaker 8: You can do sure bang in the middle of the periods,

579
00:28:31,840 --> 00:28:33,639
Speaker 8: but don't mean right bang the middle of scale.

580
00:28:34,240 --> 00:28:35,840
Speaker 7: I really looks something from the oven.

581
00:28:36,880 --> 00:28:39,040
Speaker 3: M it was growing too.

582
00:28:40,120 --> 00:28:41,360
Speaker 5: Let's been out the side of it too.

583
00:28:41,520 --> 00:28:49,240
Speaker 8: Here bottle, isn't it? Yeah, cookies, look a bleeding post.

584
00:28:51,160 --> 00:28:56,000
Speaker 8: It's growing, John, it is, Look it is. You're right.

585
00:28:56,720 --> 00:28:57,680
Speaker 1: This is so much fun.

586
00:28:57,840 --> 00:29:00,480
Speaker 3: I love also their mid Atlantic accents. It looks like

587
00:29:00,520 --> 00:29:01,440
Speaker 3: a bleeding pulse.

588
00:29:03,000 --> 00:29:05,520
Speaker 1: I'm not sure that's exactly the mid Atlantic accent that

589
00:29:05,560 --> 00:29:08,680
Speaker 1: I grew up with in New Jersey, but yes, it's

590
00:29:08,680 --> 00:29:09,360
Speaker 1: a fun accent.

591
00:29:09,480 --> 00:29:11,520
Speaker 3: I love listening to this. You know where they're trying

592
00:29:11,520 --> 00:29:13,880
Speaker 3: to convince themselves it can't be it, but it really is.

593
00:29:13,960 --> 00:29:16,840
Speaker 3: Oh my gosh, look at it's going. It's so exciting.

594
00:29:16,880 --> 00:29:17,640
Speaker 3: Way we did it.

595
00:29:17,760 --> 00:29:18,160
Speaker 1: We did it.

596
00:29:18,240 --> 00:29:20,200
Speaker 3: There really was nothing else that this could be. It

597
00:29:20,280 --> 00:29:23,000
Speaker 3: was exactly what they were hoping for and exactly the

598
00:29:23,040 --> 00:29:24,960
Speaker 3: place they thought they might be able to see it,

599
00:29:24,960 --> 00:29:27,600
Speaker 3: and it all worked and boom and they had it.

600
00:29:27,640 --> 00:29:31,480
Speaker 3: So sometimes you really do have those amazing moments of discovery.

601
00:29:31,760 --> 00:29:33,040
Speaker 1: Did they also get Nobels?

602
00:29:33,240 --> 00:29:35,480
Speaker 3: No, it helped us understand the crab nebula and it

603
00:29:35,480 --> 00:29:38,200
Speaker 3: was a really important result. But their discovery was in

604
00:29:38,280 --> 00:29:42,160
Speaker 3: sixty nine, and Bell discovered her first pulsar in sixty eight.

605
00:29:42,200 --> 00:29:45,280
Speaker 3: And in seventy four the Nobel Prize in Physics was

606
00:29:45,320 --> 00:29:47,640
Speaker 3: not given to any of these folks, only to the

607
00:29:47,720 --> 00:29:49,000
Speaker 3: advisor of Bell.

608
00:29:49,520 --> 00:29:55,920
Speaker 1: That is not cool, cool exactly. All right, Well, we've

609
00:29:55,960 --> 00:29:59,000
Speaker 1: now gone through some really exciting examples to give you,

610
00:29:59,040 --> 00:30:01,560
Speaker 1: like a real personal taste for what it's like to

611
00:30:01,560 --> 00:30:02,680
Speaker 1: make these discoveries.

612
00:30:02,840 --> 00:30:06,120
Speaker 3: Let's talk to somebody who's actual expert in discoveries, a

613
00:30:06,320 --> 00:30:09,720
Speaker 3: historian of science, a philosopher of science, who thinks about

614
00:30:09,720 --> 00:30:13,320
Speaker 3: the nature of discovery. So it's my pleasure to welcome

615
00:30:13,320 --> 00:30:16,080
Speaker 3: to the podcast professor and Lydia Patton. She's a professor

616
00:30:16,080 --> 00:30:19,160
Speaker 3: of philosophy at Virginia Tech, where she specializes in philosophy

617
00:30:19,240 --> 00:30:22,320
Speaker 3: of science and history of science, especially on the development

618
00:30:22,320 --> 00:30:25,280
Speaker 3: of experimental and formal methods. Some of her recent work

619
00:30:25,280 --> 00:30:29,360
Speaker 3: focuses on gravitational wave discoveries. Lydia, thank you very much

620
00:30:29,360 --> 00:30:30,720
Speaker 3: for joining us on the podcast.

621
00:30:31,000 --> 00:30:32,800
Speaker 5: Absolutely, it's great to talk to you.

622
00:30:33,640 --> 00:30:36,560
Speaker 3: So we are, too, scientists on this podcast talking about

623
00:30:36,600 --> 00:30:40,640
Speaker 3: our experience of discovery and our understanding of it. But

624
00:30:40,760 --> 00:30:43,240
Speaker 3: we're not experts in that right. We are scientists, doesn't

625
00:30:43,280 --> 00:30:45,880
Speaker 3: make us experts in like the history of science, philosophy

626
00:30:45,880 --> 00:30:47,880
Speaker 3: of science, which is why I want to invite you

627
00:30:47,920 --> 00:30:50,719
Speaker 3: on the show and ask you about the concept of

628
00:30:50,920 --> 00:30:54,520
Speaker 3: scientific discovery. Most people, I think, have a view of

629
00:30:54,560 --> 00:30:58,080
Speaker 3: discovery as sort of a Eureka moment. You see one thing,

630
00:30:58,320 --> 00:31:00,600
Speaker 3: you understand the universe is different from the way you

631
00:31:00,640 --> 00:31:03,080
Speaker 3: thought it was. It all clicks in your head, You

632
00:31:03,160 --> 00:31:05,040
Speaker 3: run down the street naked, shouting at the top of

633
00:31:05,080 --> 00:31:07,040
Speaker 3: your lungs. Everybody accepts it, and then we sort of

634
00:31:07,080 --> 00:31:10,280
Speaker 3: move on and make the next discovery. Is that real?

635
00:31:10,320 --> 00:31:12,640
Speaker 3: Does that really happen often? Or does that sort of

636
00:31:12,680 --> 00:31:15,160
Speaker 3: clash with the reality of the day to day working

637
00:31:15,240 --> 00:31:17,080
Speaker 3: of science. Yeah?

638
00:31:17,160 --> 00:31:21,000
Speaker 6: So, I mean our chimmedies supposedly did happen at least

639
00:31:21,000 --> 00:31:24,840
Speaker 6: once that someone did that. But I think there I

640
00:31:24,840 --> 00:31:30,720
Speaker 6: think there are moments when everything falls into place. And

641
00:31:30,960 --> 00:31:33,120
Speaker 6: the first thing that I think it's really easy to

642
00:31:33,200 --> 00:31:37,840
Speaker 6: understand is that those moments are often hard one. So

643
00:31:38,960 --> 00:31:42,560
Speaker 6: even the our Communities moment, it wasn't as if he

644
00:31:43,480 --> 00:31:45,520
Speaker 6: just came up with the concept of the lever came

645
00:31:45,600 --> 00:31:48,280
Speaker 6: up with the concept of displacement like out of nowhere.

646
00:31:48,440 --> 00:31:50,400
Speaker 6: He had been thinking about that for a long time.

647
00:31:50,440 --> 00:31:53,200
Speaker 6: And there are great sort of accounts of that in

648
00:31:53,200 --> 00:31:54,160
Speaker 6: the history of science.

649
00:31:54,600 --> 00:31:56,680
Speaker 3: So are you telling me this really happened, like we

650
00:31:56,800 --> 00:32:00,040
Speaker 3: actually have documented evidence that this happened.

651
00:31:59,760 --> 00:32:04,840
Speaker 5: Or oh, probably not, that's the no.

652
00:32:05,040 --> 00:32:08,320
Speaker 6: The myth is that he was in his bath tub,

653
00:32:08,360 --> 00:32:11,200
Speaker 6: which I you know, who knows whether they even have

654
00:32:11,400 --> 00:32:14,479
Speaker 6: bath tubs at the time, right, But and that's he

655
00:32:14,680 --> 00:32:18,000
Speaker 6: figured out the concept of displacement from something falling in

656
00:32:18,040 --> 00:32:20,600
Speaker 6: the water, and that that's why he was running through

657
00:32:20,600 --> 00:32:25,160
Speaker 6: the streets naked shouting eureka, like I figured But even

658
00:32:25,240 --> 00:32:29,200
Speaker 6: that story, which is probably apocryphal, he has to know

659
00:32:29,720 --> 00:32:30,840
Speaker 6: what he's looking for.

660
00:32:30,720 --> 00:32:33,440
Speaker 5: In the first place, Like he has to know why.

661
00:32:33,480 --> 00:32:35,680
Speaker 6: Like the average person if they just see something fall

662
00:32:35,720 --> 00:32:37,560
Speaker 6: in their bath water, are not going to say, oh,

663
00:32:37,600 --> 00:32:40,760
Speaker 6: this is a physics concept. You know, this is something

664
00:32:40,800 --> 00:32:43,840
Speaker 6: that that I can use to solve all these physics problems. Well,

665
00:32:43,880 --> 00:32:45,320
Speaker 6: you had to have a lot of training to even

666
00:32:45,360 --> 00:32:48,400
Speaker 6: recognize that that's the problem, and you had to have

667
00:32:48,400 --> 00:32:50,760
Speaker 6: a lot of background to even figure out like, Okay,

668
00:32:50,760 --> 00:32:52,480
Speaker 6: this is going to help me with mechanics, This is

669
00:32:52,480 --> 00:32:54,200
Speaker 6: going to help me with something with a problem that

670
00:32:54,200 --> 00:32:56,840
Speaker 6: I want to solve. And so I think that the

671
00:32:56,880 --> 00:32:59,640
Speaker 6: first thing is even with those kind of Eureka moments,

672
00:32:59,720 --> 00:33:03,760
Speaker 6: there's often, you know, five ten years of difficult training

673
00:33:03,800 --> 00:33:06,600
Speaker 6: and preparation in the background of them to even recognize

674
00:33:06,600 --> 00:33:07,800
Speaker 6: what it is when you see.

675
00:33:07,640 --> 00:33:11,720
Speaker 3: It, and not just training to recognize, but also lots

676
00:33:11,720 --> 00:33:13,840
Speaker 3: of failures, right, lots of moments where it didn't all

677
00:33:13,840 --> 00:33:15,720
Speaker 3: come together, things you tried that didn't.

678
00:33:15,480 --> 00:33:18,000
Speaker 6: Work, that didn't work out, and things that didn't solve

679
00:33:18,000 --> 00:33:21,320
Speaker 6: the problem. And it's like it. I mean, people often

680
00:33:21,440 --> 00:33:24,240
Speaker 6: use the example of solving a puzzle. That's not quite it,

681
00:33:24,400 --> 00:33:28,600
Speaker 6: but it's the idea, is you even if it is

682
00:33:28,640 --> 00:33:32,600
Speaker 6: something as simple as solving a puzzle, and I would

683
00:33:32,640 --> 00:33:35,920
Speaker 6: agree that science is more complicated than that. But even

684
00:33:35,960 --> 00:33:39,800
Speaker 6: with a puzzle solving metaphor, you have to try and

685
00:33:39,840 --> 00:33:41,400
Speaker 6: fail a whole bunch of times.

686
00:33:41,160 --> 00:33:42,680
Speaker 5: Before you start figuring it out.

687
00:33:42,760 --> 00:33:44,000
Speaker 6: Like if you think about when you were a kid

688
00:33:44,000 --> 00:33:46,280
Speaker 6: and you tried to do the Rubi's cue, it took

689
00:33:46,280 --> 00:33:48,960
Speaker 6: a long time to try to figure it out until

690
00:33:49,000 --> 00:33:50,160
Speaker 6: you could reliably do it.

691
00:33:51,040 --> 00:33:52,200
Speaker 5: And it's kind of the same thing.

692
00:33:52,400 --> 00:33:55,880
Speaker 3: Fascinating, and so even this canonical story, this Eureka moment,

693
00:33:56,520 --> 00:34:00,360
Speaker 3: is probably a story that's been made up to invey

694
00:34:00,480 --> 00:34:03,880
Speaker 3: to the general public. What this is, Like how long

695
00:34:03,880 --> 00:34:05,720
Speaker 3: has there been sort of this disconnect? Why are we

696
00:34:05,840 --> 00:34:09,759
Speaker 3: making up stories about how scientific discoveries happen? Like where

697
00:34:09,800 --> 00:34:12,279
Speaker 3: do these cartoon versions come from? And why do we

698
00:34:12,360 --> 00:34:12,719
Speaker 3: need them?

699
00:34:12,920 --> 00:34:15,720
Speaker 6: That is one of the biggest questions that I think

700
00:34:16,440 --> 00:34:19,480
Speaker 6: historians of science wrestle with philosophers of science.

701
00:34:19,520 --> 00:34:21,960
Speaker 5: Maybe a bit less, but philosophers of.

702
00:34:21,960 --> 00:34:25,200
Speaker 6: Science deal with something where we wonder a lot about

703
00:34:26,200 --> 00:34:28,800
Speaker 6: why we have a need for truth in science.

704
00:34:29,000 --> 00:34:31,239
Speaker 3: That seems like an obvious question, and it's an.

705
00:34:31,120 --> 00:34:35,000
Speaker 6: Obvious questions, but it's a tough question to answer. Why

706
00:34:35,000 --> 00:34:37,480
Speaker 6: do we want to think that science describes reality?

707
00:34:37,719 --> 00:34:37,959
Speaker 5: Right?

708
00:34:38,040 --> 00:34:39,840
Speaker 6: And so this is one of the biggest questions in

709
00:34:39,880 --> 00:34:44,279
Speaker 6: contemporary philosophy of science is why what makes us think

710
00:34:44,320 --> 00:34:47,960
Speaker 6: that the claims of science or claims about real things

711
00:34:48,000 --> 00:34:51,200
Speaker 6: that actually exist, or claims about truth or true claims.

712
00:34:52,120 --> 00:34:56,640
Speaker 6: And I think that there's something so seductive about truth

713
00:34:56,719 --> 00:34:58,880
Speaker 6: that the idea is that, for one thing, you can

714
00:34:58,960 --> 00:35:00,879
Speaker 6: use it to win any our argument, which to any

715
00:35:00,880 --> 00:35:03,000
Speaker 6: philosopher is going to be super attractive.

716
00:35:03,200 --> 00:35:06,799
Speaker 5: Right. It's like your sort of trump card.

717
00:35:06,880 --> 00:35:09,160
Speaker 6: You lay it down and you win the argument because

718
00:35:09,400 --> 00:35:13,360
Speaker 6: you have made a claim that's just true, and I

719
00:35:13,360 --> 00:35:17,520
Speaker 6: think that that's that kind of feeling, like, oh, now

720
00:35:17,560 --> 00:35:18,600
Speaker 6: I win any argument.

721
00:35:18,760 --> 00:35:20,239
Speaker 5: Now I just come out on top.

722
00:35:21,000 --> 00:35:23,080
Speaker 6: You know, if I end up in an argument on

723
00:35:23,120 --> 00:35:25,520
Speaker 6: social media, like if I just bring this out.

724
00:35:25,400 --> 00:35:27,680
Speaker 5: Everybody will have to agree that I'm right, you know.

725
00:35:28,719 --> 00:35:34,640
Speaker 6: And I think that kind of certainty is what's very attractive. Certainty,

726
00:35:35,560 --> 00:35:39,160
Speaker 6: winning the argument, being right, These are all very attractive things.

727
00:35:40,160 --> 00:35:44,880
Speaker 6: And I think that what's masked behind that. So, of course,

728
00:35:45,120 --> 00:35:48,080
Speaker 6: if we think of science as being the source of certainty,

729
00:35:48,120 --> 00:35:52,799
Speaker 6: the source of rightness, and a privileged source of being

730
00:35:52,800 --> 00:35:56,360
Speaker 6: able to win any argument, even a political or social argument.

731
00:35:56,760 --> 00:35:59,040
Speaker 6: If we think of science as being in that position,

732
00:36:00,120 --> 00:36:04,719
Speaker 6: then that means that if someone makes a scientific discovery

733
00:36:05,200 --> 00:36:09,360
Speaker 6: that gives us truth and certainty and ways of winning

734
00:36:09,360 --> 00:36:12,400
Speaker 6: the argument, then that sort of fits in with that

735
00:36:12,480 --> 00:36:16,800
Speaker 6: narrative that oh, okay, now we're on top, we're winning,

736
00:36:17,719 --> 00:36:20,439
Speaker 6: and we have this certain, true picture of the way

737
00:36:20,440 --> 00:36:22,920
Speaker 6: the world works, which is also extremely attractive.

738
00:36:23,280 --> 00:36:25,920
Speaker 3: I see. So it's compelling to imagine that truth is

739
00:36:26,000 --> 00:36:29,080
Speaker 3: revealed to us in these moments and that we can

740
00:36:29,120 --> 00:36:31,160
Speaker 3: share with people and be like, see, look, this is

741
00:36:31,200 --> 00:36:33,880
Speaker 3: the way the universe works. It's X and it's not y,

742
00:36:34,520 --> 00:36:38,160
Speaker 3: and the data itself will convince everyone that's the idea.

743
00:36:38,120 --> 00:36:41,319
Speaker 5: That's the idea. And there have been multiple examples of that.

744
00:36:41,360 --> 00:36:44,480
Speaker 6: One of my favorites is with somebody I've studied some

745
00:36:44,560 --> 00:36:48,399
Speaker 6: in my careers, someone named hermon Vun Helmholtz and who's

746
00:36:48,440 --> 00:36:55,880
Speaker 6: a German polymath. Really he physicists, philosopher, mathematician, many other things.

747
00:36:55,920 --> 00:36:59,520
Speaker 6: And one of the things that he did was in

748
00:36:59,560 --> 00:37:02,920
Speaker 6: the beginning of his career he really went after vitalism

749
00:37:02,960 --> 00:37:05,600
Speaker 6: and medicine, the idea that there's a kind of vital

750
00:37:05,640 --> 00:37:09,719
Speaker 6: force over and above the forces of metabolism and so

751
00:37:09,760 --> 00:37:13,080
Speaker 6: forth in the human body. And the thing is that

752
00:37:13,320 --> 00:37:19,759
Speaker 6: many medical systems, many medical approaches in like ancient Chinese medicine,

753
00:37:20,120 --> 00:37:24,560
Speaker 6: and in many traditional medical sort of paradigms, are based

754
00:37:24,600 --> 00:37:28,400
Speaker 6: on this idea of a life force, that what medicine

755
00:37:28,440 --> 00:37:30,920
Speaker 6: is doing is kind of helping the life force to

756
00:37:31,000 --> 00:37:34,480
Speaker 6: get stronger so that people will survive. And one of

757
00:37:34,560 --> 00:37:36,480
Speaker 6: the first things that Helmholtz did, and he wasn't even

758
00:37:36,480 --> 00:37:38,919
Speaker 6: a medical doctor, you know, was do a whole bunch

759
00:37:38,960 --> 00:37:45,440
Speaker 6: of experiments that disproved in his mind the vitalist hypothesis

760
00:37:46,520 --> 00:37:50,000
Speaker 6: and his achievement, in conjunction with the achievements of a

761
00:37:50,040 --> 00:37:53,760
Speaker 6: bunch of other people in that same vein, basically killed

762
00:37:53,760 --> 00:37:56,279
Speaker 6: the vitalist paradigm and.

763
00:37:56,200 --> 00:37:57,880
Speaker 5: It had a huge impact.

764
00:37:58,080 --> 00:38:00,480
Speaker 6: And so what happened was that people have this kind

765
00:38:00,480 --> 00:38:03,680
Speaker 6: of certainty like he had this kind of certainty. I

766
00:38:03,760 --> 00:38:06,800
Speaker 6: honestly look back at Helmholtz, and I think he didn't

767
00:38:06,840 --> 00:38:10,800
Speaker 6: really know. He was involved with a group of people

768
00:38:11,120 --> 00:38:16,520
Speaker 6: who the Berlin Physical Society. They thought that vitalism was

769
00:38:16,560 --> 00:38:20,200
Speaker 6: wrong and that everything should be explained by material processes

770
00:38:20,239 --> 00:38:22,400
Speaker 6: in the body and so forth. But they didn't have

771
00:38:22,400 --> 00:38:25,040
Speaker 6: any absolute proof of it, but they were seeking it,

772
00:38:25,120 --> 00:38:28,319
Speaker 6: and so that was what they wanted to find. And

773
00:38:28,360 --> 00:38:31,120
Speaker 6: so there's this kind of sense that if there's something

774
00:38:31,239 --> 00:38:35,520
Speaker 6: that you want to establish beyond any possible doubt, you

775
00:38:35,680 --> 00:38:37,759
Speaker 6: try to look for this eureka moment, You try to

776
00:38:37,800 --> 00:38:40,719
Speaker 6: look for this certainty in science, and that that's the

777
00:38:40,840 --> 00:38:43,120
Speaker 6: value of science. That's one account of the value of

778
00:38:43,160 --> 00:38:45,840
Speaker 6: science is that it gives you this kind of truth

779
00:38:45,880 --> 00:38:47,279
Speaker 6: and certainty that you're looking for.

780
00:38:47,600 --> 00:38:50,439
Speaker 3: That's just something a little bit troubling that you're more

781
00:38:50,560 --> 00:38:54,239
Speaker 3: likely to be convinced by something you expect to hear right,

782
00:38:54,640 --> 00:38:56,840
Speaker 3: which is maybe why it takes a long time to

783
00:38:56,920 --> 00:39:00,560
Speaker 3: accept some data which counters you or understanding, you know,

784
00:39:00,600 --> 00:39:04,560
Speaker 3: tectonic plates in the Michaelson Morley experiment. Why can't we

785
00:39:04,760 --> 00:39:07,400
Speaker 3: just let the data speak? Is there some part of

786
00:39:07,440 --> 00:39:11,000
Speaker 3: our science which is too subjective, which you know, makes

787
00:39:11,080 --> 00:39:15,000
Speaker 3: us skeptical of some discoveries and more accepting of others.

788
00:39:15,120 --> 00:39:18,319
Speaker 3: Is there a way we can upgrade our science to

789
00:39:18,440 --> 00:39:19,719
Speaker 3: make it less subjective?

790
00:39:20,200 --> 00:39:20,359
Speaker 7: Oh?

791
00:39:20,440 --> 00:39:23,000
Speaker 5: Yeah, that is That is a great and huge question.

792
00:39:23,120 --> 00:39:26,080
Speaker 6: I think why can't we I'll tackle why can't we

793
00:39:26,160 --> 00:39:29,480
Speaker 6: just let the data speak? Because to me, that is

794
00:39:29,640 --> 00:39:31,759
Speaker 6: that is one of the biggest questions that I look at.

795
00:39:32,920 --> 00:39:35,280
Speaker 6: Data does not speak in and of itself.

796
00:39:35,320 --> 00:39:35,840
Speaker 5: That's one.

797
00:39:36,640 --> 00:39:38,000
Speaker 6: There are a lot of people who say, well, oh

798
00:39:38,040 --> 00:39:40,279
Speaker 6: I'm evidence based. Oh I just go by what the

799
00:39:40,400 --> 00:39:42,880
Speaker 6: data said. Oh I just go And there's something to

800
00:39:42,880 --> 00:39:44,640
Speaker 6: be said for that. I mean, you do need to

801
00:39:44,680 --> 00:39:48,000
Speaker 6: test your claims against the evidence. If your claims just

802
00:39:48,120 --> 00:39:52,319
Speaker 6: keep getting refuted by obvious experiments, then either you need

803
00:39:52,360 --> 00:39:54,839
Speaker 6: to adjust your claims somehow, or you know. I mean

804
00:39:54,840 --> 00:39:58,080
Speaker 6: that I think everyone knows is the scientific method that

805
00:39:58,120 --> 00:40:01,319
Speaker 6: you have to part of a scientific meth method is

806
00:40:01,360 --> 00:40:04,560
Speaker 6: that if what you're saying just keeps being refuted by

807
00:40:04,760 --> 00:40:10,839
Speaker 6: experiments or tests, then it's wrong. But to say that

808
00:40:11,239 --> 00:40:14,320
Speaker 6: is not to say that you can gather new data

809
00:40:14,680 --> 00:40:18,440
Speaker 6: and immediately know everything about what it says. And a

810
00:40:18,440 --> 00:40:22,200
Speaker 6: lot of times even very high level scientists will say, look,

811
00:40:22,280 --> 00:40:24,799
Speaker 6: you know, we're running this experiment and one of the

812
00:40:24,800 --> 00:40:27,160
Speaker 6: most exciting things about it is that we're getting data

813
00:40:27,200 --> 00:40:28,759
Speaker 6: that even we don't understand.

814
00:40:29,360 --> 00:40:30,440
Speaker 5: You know, even.

815
00:40:30,200 --> 00:40:33,200
Speaker 6: We need a new paradigm or a new framework to

816
00:40:33,600 --> 00:40:36,920
Speaker 6: fit this in in order to understand what it's telling us.

817
00:40:36,920 --> 00:40:39,719
Speaker 6: It's like learning a new language. You know, you have

818
00:40:39,880 --> 00:40:42,360
Speaker 6: all of the information there, but you need to be

819
00:40:42,360 --> 00:40:45,040
Speaker 6: able to translate it into something to allow us to

820
00:40:45,160 --> 00:40:48,040
Speaker 6: understand what's happened. And I think there are a lot

821
00:40:48,040 --> 00:40:51,000
Speaker 6: of discoveries in science that worked that way, where a

822
00:40:51,040 --> 00:40:53,839
Speaker 6: lot of experiments, especially in science, that work that way,

823
00:40:54,480 --> 00:40:59,160
Speaker 6: where they were what Friedrich Steinley calls exploratory experiments where

824
00:40:59,200 --> 00:41:01,960
Speaker 6: people were just trying eyeing out different hypotheses, just testing

825
00:41:02,000 --> 00:41:04,560
Speaker 6: out what they might be able to find, and then

826
00:41:04,600 --> 00:41:07,360
Speaker 6: they get this data and it's really interesting data, but

827
00:41:07,400 --> 00:41:09,279
Speaker 6: they're not really sure what it means, and they have

828
00:41:09,320 --> 00:41:12,399
Speaker 6: to come up with a new explanation even to even

829
00:41:12,480 --> 00:41:14,520
Speaker 6: get the kind of the juice out of it, to

830
00:41:14,560 --> 00:41:16,840
Speaker 6: get the real information out of the data.

831
00:41:16,920 --> 00:41:18,840
Speaker 3: Well, so it sounds like you're telling me, and I

832
00:41:18,880 --> 00:41:22,560
Speaker 3: apologize for asking you to summarize or simplify an entire

833
00:41:22,800 --> 00:41:26,200
Speaker 3: like one hundred year long argument among philosophers, but it

834
00:41:26,280 --> 00:41:28,040
Speaker 3: sounds like you're telling me that there's no way to

835
00:41:28,080 --> 00:41:32,440
Speaker 3: be purely objective about science because the process of interpreting

836
00:41:32,520 --> 00:41:38,359
Speaker 3: data is inherently subjective or personal or dependent on your

837
00:41:38,360 --> 00:41:40,279
Speaker 3: point of view and the questions you're asking and the

838
00:41:40,880 --> 00:41:43,000
Speaker 3: explanations you're interested in accepting.

839
00:41:43,360 --> 00:41:46,640
Speaker 6: Okay, so that's a slight that's a somewhat provocative way

840
00:41:46,640 --> 00:41:51,960
Speaker 6: of putting way I just said, so I would somewhat

841
00:41:52,160 --> 00:41:56,120
Speaker 6: So the whole objectivity subjectivity debate is a big one.

842
00:41:56,239 --> 00:41:59,480
Speaker 6: And so what I would say is it's not so

843
00:41:59,600 --> 00:42:02,600
Speaker 6: much that you have to choose your subjective slant on

844
00:42:02,640 --> 00:42:07,160
Speaker 6: the data, but it is that even objective facts require

845
00:42:07,200 --> 00:42:11,600
Speaker 6: an interpretation of the data. So I think it's actually

846
00:42:11,680 --> 00:42:15,600
Speaker 6: kind of independent of the objective subjective divide. I think

847
00:42:15,600 --> 00:42:18,359
Speaker 6: it's that if a lot of you know, a lot

848
00:42:18,360 --> 00:42:22,920
Speaker 6: of times what you have is just like, this detector

849
00:42:23,120 --> 00:42:26,319
Speaker 6: clicked five times in a minute, Well, what does that mean?

850
00:42:27,640 --> 00:42:29,120
Speaker 5: We only know what that means.

851
00:42:30,040 --> 00:42:31,719
Speaker 6: We don't have It's not like we have to pick

852
00:42:31,800 --> 00:42:34,360
Speaker 6: what we think about it or what we expect or

853
00:42:34,400 --> 00:42:37,040
Speaker 6: what we want out of it. It's that even in

854
00:42:37,160 --> 00:42:39,960
Speaker 6: order to know what that means, why did the detector

855
00:42:39,960 --> 00:42:42,960
Speaker 6: click so many times? What's going on there? You need

856
00:42:43,000 --> 00:42:45,200
Speaker 6: to know what the setup of the experiment is. You

857
00:42:45,239 --> 00:42:46,879
Speaker 6: need to know what the theory is that it's trying

858
00:42:46,920 --> 00:42:49,080
Speaker 6: to test. You need to have some kind of framework

859
00:42:49,080 --> 00:42:51,680
Speaker 6: for interpretation. And that I think is the part that

860
00:42:52,120 --> 00:42:55,600
Speaker 6: sometimes gets confused is people think, well, that's just your opinion,

861
00:42:55,680 --> 00:42:59,240
Speaker 6: then that's not science, and like, well, no, the science

862
00:42:59,320 --> 00:43:03,640
Speaker 6: is in knowing all of that, like knowing how the

863
00:43:03,719 --> 00:43:07,440
Speaker 6: experiment works, what kind of information we can sort of

864
00:43:08,040 --> 00:43:11,120
Speaker 6: get from the data once we get it, and that

865
00:43:11,200 --> 00:43:15,200
Speaker 6: process doesn't have to be subjective, but it doesn't give

866
00:43:15,239 --> 00:43:19,920
Speaker 6: us objective results without any effort. I think that's really

867
00:43:19,960 --> 00:43:21,200
Speaker 6: where I see attention.

868
00:43:21,480 --> 00:43:25,000
Speaker 3: So science is sort of a complex and nuanced process.

869
00:43:25,520 --> 00:43:27,279
Speaker 3: But I think that a lot of people have the

870
00:43:27,320 --> 00:43:31,760
Speaker 3: impression that science sort of came into being all very quickly.

871
00:43:31,880 --> 00:43:34,759
Speaker 3: A few hundred years ago, when you know Galleo and

872
00:43:34,840 --> 00:43:40,200
Speaker 3: Bacon understood the importance of empiricism and doing experiments. Is

873
00:43:40,200 --> 00:43:43,160
Speaker 3: that a cartoonish, simplified version of the development of science.

874
00:43:43,320 --> 00:43:45,439
Speaker 3: Can you give us a sort of more nuanced view

875
00:43:45,560 --> 00:43:50,000
Speaker 3: of like how we came to develop this engine for discovery.

876
00:43:50,520 --> 00:43:57,320
Speaker 6: The process of coming to a scientific understanding didn't come

877
00:43:57,480 --> 00:44:04,319
Speaker 6: into being immediately, and even thinking of our understanding of

878
00:44:04,320 --> 00:44:09,680
Speaker 6: the world as scientific is a relatively recent phenomenon. So

879
00:44:10,920 --> 00:44:12,959
Speaker 6: most of the people who we think of as the

880
00:44:13,040 --> 00:44:15,840
Speaker 6: pioneers of the scientific method would have thought of themselves

881
00:44:15,880 --> 00:44:22,839
Speaker 6: as natural philosophers. The tradition of natural philosophy encompassed philosophy, science, theology,

882
00:44:23,160 --> 00:44:28,600
Speaker 6: just multiple ways of understanding the world. And the publication

883
00:44:28,680 --> 00:44:31,080
Speaker 6: of Newton, as you probably know, the publication of Newton,

884
00:44:31,120 --> 00:44:33,839
Speaker 6: where he introduces the laws of nature and the laws

885
00:44:33,840 --> 00:44:38,320
Speaker 6: of physics and so forth, was called the mathematical Principles

886
00:44:38,320 --> 00:44:42,600
Speaker 6: of natural philosophy, not the mathematical Principles of physics. And

887
00:44:42,680 --> 00:44:44,680
Speaker 6: so for a long time the idea was just we're

888
00:44:44,719 --> 00:44:48,520
Speaker 6: trying to understand the world. We're trying to understand things

889
00:44:48,600 --> 00:44:54,480
Speaker 6: from whatever perspective we may have, and the idea of science, however,

890
00:44:54,640 --> 00:44:59,560
Speaker 6: is extremely old. So you have even you know, some

891
00:44:59,640 --> 00:45:04,960
Speaker 6: of the ancient Greek philosophers talking about science, and so

892
00:45:05,239 --> 00:45:07,200
Speaker 6: the idea that it came into being with Bacon and

893
00:45:07,239 --> 00:45:11,239
Speaker 6: Galileo is actually even too recent, right, Like the idea

894
00:45:11,239 --> 00:45:15,280
Speaker 6: of scientific understanding is very old. But at the same time,

895
00:45:15,680 --> 00:45:17,840
Speaker 6: even people who were doing what we would think of

896
00:45:17,880 --> 00:45:22,399
Speaker 6: as pioneering science did so under the banner of another heading, right.

897
00:45:22,520 --> 00:45:26,399
Speaker 6: So it was really, in my view historically in the

898
00:45:26,600 --> 00:45:31,480
Speaker 6: eighteen hundreds that those two things started blending in an

899
00:45:31,520 --> 00:45:35,880
Speaker 6: institutional context to give us something like the modern idea

900
00:45:36,000 --> 00:45:38,799
Speaker 6: that there is a department or a faculty in the

901
00:45:38,920 --> 00:45:43,720
Speaker 6: university that is specifically devoted to science. And that's really

902
00:45:43,760 --> 00:45:47,200
Speaker 6: more of a professional idea than anything to do with

903
00:45:47,320 --> 00:45:51,480
Speaker 6: the essence of the way that science is carried out.

904
00:45:52,360 --> 00:45:54,399
Speaker 6: This is the briefest thing I can say about it.

905
00:45:54,800 --> 00:45:57,360
Speaker 6: If you spend a lot of time around historians of

906
00:45:57,360 --> 00:46:00,920
Speaker 6: philosophy of science, historians of science, you will realize that

907
00:46:01,000 --> 00:46:04,600
Speaker 6: the further back you get, the more complicated this all is,

908
00:46:05,560 --> 00:46:09,520
Speaker 6: and the more you find people in very different fields

909
00:46:09,640 --> 00:46:13,560
Speaker 6: contributing to science. You find people like Girta contributing to

910
00:46:13,640 --> 00:46:18,680
Speaker 6: plant science Schiller in the nineteenth century. They were cited

911
00:46:18,760 --> 00:46:23,280
Speaker 6: often by like major scientists in the German nineteenth century,

912
00:46:23,760 --> 00:46:25,920
Speaker 6: and we don't really know what to do with that

913
00:46:26,280 --> 00:46:31,239
Speaker 6: because we have a particular idea of the way of

914
00:46:31,280 --> 00:46:34,920
Speaker 6: who a scientist is and who gets to be a scientist,

915
00:46:36,040 --> 00:46:39,000
Speaker 6: and that person works at a certain type of university

916
00:46:39,160 --> 00:46:42,239
Speaker 6: or a research project, that person has certain types of

917
00:46:42,280 --> 00:46:47,200
Speaker 6: professional bona fides that we require, and historically that just

918
00:46:47,239 --> 00:46:50,799
Speaker 6: hasn't been true because that didn't exist. And so I

919
00:46:50,800 --> 00:46:53,440
Speaker 6: think that there's been much more of a broad, sort

920
00:46:53,440 --> 00:46:56,480
Speaker 6: of pluralistic understanding of what science is. The more you

921
00:46:56,520 --> 00:46:59,440
Speaker 6: sort of push things backwards. A lot of people were

922
00:46:59,440 --> 00:47:02,400
Speaker 6: doing research for like private corporations.

923
00:47:02,440 --> 00:47:03,400
Speaker 5: They were doing research.

924
00:47:03,440 --> 00:47:05,239
Speaker 6: I mean, if you look at Michael Faraday, you know

925
00:47:05,280 --> 00:47:07,680
Speaker 6: he was one of the most important people in the

926
00:47:07,719 --> 00:47:10,560
Speaker 6: history of electricity and magnetism, and a lot of his

927
00:47:10,640 --> 00:47:13,640
Speaker 6: work was done privately. It wasn't done at a university

928
00:47:13,640 --> 00:47:17,440
Speaker 6: because he didn't have university training. But that's one point,

929
00:47:17,480 --> 00:47:20,440
Speaker 6: that's the sort of historical point that science is very

930
00:47:20,440 --> 00:47:24,560
Speaker 6: complicated in it. The current understanding is actually very historically specific,

931
00:47:25,080 --> 00:47:28,719
Speaker 6: even though we think of it as again searching for

932
00:47:28,800 --> 00:47:32,160
Speaker 6: this kind of certainty and eternal truths. We think of

933
00:47:32,200 --> 00:47:34,080
Speaker 6: it as like the way to be a scientist, but

934
00:47:34,160 --> 00:47:35,960
Speaker 6: it's certainly not in history.

935
00:47:36,239 --> 00:47:39,000
Speaker 3: And Faraday's examples should give motivation to all the folks

936
00:47:39,040 --> 00:47:42,319
Speaker 3: out there who are amateur physicists coming up with their

937
00:47:42,360 --> 00:47:44,480
Speaker 3: own theories of everything in the garage, right, it.

938
00:47:44,440 --> 00:47:47,160
Speaker 6: Can happen one hundred percent. I mean, this is the

939
00:47:47,160 --> 00:47:51,680
Speaker 6: guy who came up with the motor. Basically, I think

940
00:47:52,440 --> 00:47:53,920
Speaker 6: that should be an example to anyone.

941
00:47:54,200 --> 00:47:57,200
Speaker 3: So you alluded earlier to this deep question in philosophy

942
00:47:57,320 --> 00:48:00,879
Speaker 3: about whether science is discovering truth. Is what we're learning

943
00:48:00,920 --> 00:48:03,879
Speaker 3: about the universe really universal? Does it reflect the way

944
00:48:03,880 --> 00:48:06,640
Speaker 3: we think? Fascinating question. I'd love to dig into it

945
00:48:06,680 --> 00:48:08,319
Speaker 3: in another episode, but I want to ask you a

946
00:48:08,320 --> 00:48:12,600
Speaker 3: related question, which is about the universality of the process

947
00:48:12,640 --> 00:48:16,040
Speaker 3: of science. We have this technique we've been building up

948
00:48:16,080 --> 00:48:19,760
Speaker 3: and evolving, this that developing to learn about the universe.

949
00:48:20,200 --> 00:48:24,440
Speaker 3: Do you think that it's likely that other intelligent civilized

950
00:48:24,520 --> 00:48:29,359
Speaker 3: races around the galaxy, for example, are doing science. You know,

951
00:48:29,400 --> 00:48:31,759
Speaker 3: I'm not asking is there a person they call a

952
00:48:31,840 --> 00:48:34,560
Speaker 3: scientist and do they have the same cultural institutions I

953
00:48:34,560 --> 00:48:36,880
Speaker 3: think that's very unlikely. But do you think they have

954
00:48:37,040 --> 00:48:42,359
Speaker 3: also stumbled on the process of building hypotheses, doing experiments

955
00:48:42,400 --> 00:48:44,600
Speaker 3: refining that. Do you think we're likely to find that

956
00:48:45,000 --> 00:48:46,799
Speaker 3: in alien species?

957
00:48:47,040 --> 00:48:51,040
Speaker 5: Oh, that's a great question. So I think one of

958
00:48:51,080 --> 00:48:51,800
Speaker 5: the things I think.

959
00:48:51,680 --> 00:48:55,640
Speaker 6: About that is that it's closely related to another question,

960
00:48:56,600 --> 00:49:00,920
Speaker 6: which is science inevitable in the way that we've developed it.

961
00:49:01,080 --> 00:49:05,279
Speaker 6: So on any planet, with any species, or even if

962
00:49:05,360 --> 00:49:10,000
Speaker 6: we went back and re ran the tape of our history,

963
00:49:10,480 --> 00:49:13,959
Speaker 6: would it all happen the same way? And I think

964
00:49:14,320 --> 00:49:18,360
Speaker 6: it wouldn't necessarily, even if the changes were just minor.

965
00:49:19,000 --> 00:49:23,960
Speaker 6: There are people who argue that certain formal features of

966
00:49:24,000 --> 00:49:27,160
Speaker 6: science would always inevitably be the same way. We would

967
00:49:27,160 --> 00:49:29,720
Speaker 6: always find some way to do experiments, we would always

968
00:49:29,760 --> 00:49:31,880
Speaker 6: find some way to test our claims, we would always

969
00:49:31,880 --> 00:49:34,160
Speaker 6: find some way to incorporate formal reasoning.

970
00:49:34,280 --> 00:49:34,440
Speaker 4: Right.

971
00:49:35,520 --> 00:49:36,560
Speaker 5: I'm not sure that's true.

972
00:49:36,640 --> 00:49:39,200
Speaker 3: It seems awfully flattering, right to say that the way

973
00:49:39,239 --> 00:49:41,040
Speaker 3: we're doing it has got to be the only way.

974
00:49:41,560 --> 00:49:45,840
Speaker 6: We are very triumphalist about our way of doing science.

975
00:49:47,400 --> 00:49:49,040
Speaker 6: We think that we have the way and that this

976
00:49:49,160 --> 00:49:52,520
Speaker 6: is the right way. And I think that sometimes people

977
00:49:52,560 --> 00:49:54,920
Speaker 6: cling to it as a way of solving our problems.

978
00:49:54,920 --> 00:49:55,080
Speaker 3: You know.

979
00:49:55,200 --> 00:49:57,160
Speaker 6: The idea is if we could just all get on board,

980
00:49:57,320 --> 00:50:00,800
Speaker 6: if everyone could just trust the science and tru scientists,

981
00:50:00,800 --> 00:50:02,719
Speaker 6: and we would all get And it's funny how the

982
00:50:02,719 --> 00:50:04,839
Speaker 6: people who get the most skeptical look in their eyes

983
00:50:04,880 --> 00:50:07,160
Speaker 6: when they hear this are scientists, right, They're.

984
00:50:06,960 --> 00:50:09,760
Speaker 5: Like us, why are we supposed to save everybody?

985
00:50:09,840 --> 00:50:10,000
Speaker 7: You know?

986
00:50:10,080 --> 00:50:11,600
Speaker 5: Like, what's wait a minute?

987
00:50:11,680 --> 00:50:14,360
Speaker 6: And I think that's one of the one of the

988
00:50:14,400 --> 00:50:17,200
Speaker 6: aspects of science that's kind of funny is that, you know,

989
00:50:17,239 --> 00:50:20,799
Speaker 6: what it shouldn't be required to do is save the world.

990
00:50:21,640 --> 00:50:24,760
Speaker 6: And I think we want it to, but it shouldn't

991
00:50:24,800 --> 00:50:27,160
Speaker 6: be required to It's a means of discovery. It's a

992
00:50:27,160 --> 00:50:30,359
Speaker 6: means of exploration. Now do I think that there would

993
00:50:30,400 --> 00:50:36,719
Speaker 6: be scientific discovery in any curious, intelligent species on other

994
00:50:37,000 --> 00:50:39,799
Speaker 6: planets or wherever they might be. Of course, yeah, right,

995
00:50:39,880 --> 00:50:42,480
Speaker 6: I mean I think in their own way, right, Like

996
00:50:42,560 --> 00:50:46,520
Speaker 6: bacteria explore and you know, this is something that, of

997
00:50:46,520 --> 00:50:49,720
Speaker 6: course a biologist would be better suited to talk about

998
00:50:49,760 --> 00:50:52,920
Speaker 6: in detail. But there are species that in their own

999
00:50:52,960 --> 00:50:56,720
Speaker 6: way are exploring, making experiments, figuring out which environments are better,

1000
00:50:57,520 --> 00:50:59,600
Speaker 6: and we don't have any way of knowing whether they're

1001
00:50:59,640 --> 00:51:03,319
Speaker 6: doing that intentionally or for what purpose. But I think

1002
00:51:03,360 --> 00:51:07,239
Speaker 6: that it's a little condescending to assume that because we

1003
00:51:07,320 --> 00:51:11,160
Speaker 6: don't know that they're not doing anything, you know, I

1004
00:51:11,160 --> 00:51:14,080
Speaker 6: think even if we just look at our planet, there

1005
00:51:14,120 --> 00:51:16,720
Speaker 6: are lots more species that are probably doing something closer

1006
00:51:16,719 --> 00:51:19,080
Speaker 6: to the scientific method than we might think.

1007
00:51:19,320 --> 00:51:20,960
Speaker 3: What's a good candidate to think.

1008
00:51:21,080 --> 00:51:23,800
Speaker 6: Well, one of my colleagues at Virginia Tech, Ashley, she

1009
00:51:24,080 --> 00:51:27,360
Speaker 6: did her dissertation on New Caledonian crows, that there is

1010
00:51:27,480 --> 00:51:30,160
Speaker 6: other work on New Caledonian crows. I think they're a

1011
00:51:30,160 --> 00:51:34,239
Speaker 6: good example of tool using creatures in any case, and

1012
00:51:34,560 --> 00:51:35,160
Speaker 6: who have done.

1013
00:51:35,360 --> 00:51:37,000
Speaker 5: If I were better versus in this area, I would

1014
00:51:37,000 --> 00:51:38,040
Speaker 5: have lots more examples.

1015
00:51:38,120 --> 00:51:41,600
Speaker 3: But just having many examples on Earth make an argument

1016
00:51:41,719 --> 00:51:44,760
Speaker 3: that it's more likely to exist on other planets as well,

1017
00:51:44,800 --> 00:51:46,480
Speaker 3: like other environments.

1018
00:51:46,719 --> 00:51:48,839
Speaker 6: I would like for that to be true, because, as

1019
00:51:48,880 --> 00:51:51,480
Speaker 6: you say, maybe you didn't intend to say this, but

1020
00:51:51,520 --> 00:51:52,640
Speaker 6: it's his interpretation.

1021
00:51:53,239 --> 00:51:55,520
Speaker 5: It kind of throws a mirror up to our own.

1022
00:51:55,480 --> 00:52:00,640
Speaker 6: Practices and says, look again, what we want is this

1023
00:52:00,760 --> 00:52:03,279
Speaker 6: idea of the inevitability of the scientific method in the

1024
00:52:03,280 --> 00:52:07,719
Speaker 6: way that we've discovered it or developed it. The certainty

1025
00:52:07,760 --> 00:52:10,640
Speaker 6: of science, the truth of science, the idea that we've

1026
00:52:10,680 --> 00:52:14,120
Speaker 6: figured out the one right way. And I think the

1027
00:52:14,440 --> 00:52:18,839
Speaker 6: triumphalism is a nice word for that. And I think

1028
00:52:18,880 --> 00:52:21,920
Speaker 6: that thinking about, well, wait, what if they do it

1029
00:52:22,000 --> 00:52:24,879
Speaker 6: differently elsewhere? What if there are other ways of doing this,

1030
00:52:25,920 --> 00:52:29,319
Speaker 6: whether on the Earth or elsewhere in the galaxy. And

1031
00:52:29,400 --> 00:52:35,160
Speaker 6: we're more able to reach out send signals to other

1032
00:52:35,239 --> 00:52:39,319
Speaker 6: places now than we ever have been. And I think

1033
00:52:39,360 --> 00:52:43,360
Speaker 6: that the possibility that there might be another way of

1034
00:52:43,400 --> 00:52:46,200
Speaker 6: doing science, on the one hand, it sort of undermines

1035
00:52:46,280 --> 00:52:49,240
Speaker 6: that idea of certainty and truth, and on the other hand,

1036
00:52:49,280 --> 00:52:51,480
Speaker 6: that could be seen as a good thing.

1037
00:52:51,640 --> 00:52:53,280
Speaker 5: That could be a good thing, wonderful.

1038
00:52:53,360 --> 00:52:55,719
Speaker 3: Well, I look forward to all these developments in the

1039
00:52:55,760 --> 00:52:59,360
Speaker 3: process of science itself and our social relationship with science.

1040
00:53:00,160 --> 00:53:02,279
Speaker 3: To end by asking you one last question, and this

1041
00:53:02,360 --> 00:53:06,279
Speaker 3: is going to be the most controversial, politically charged question.

1042
00:53:06,320 --> 00:53:08,560
Speaker 3: I'm going to ask you, if you had to choose,

1043
00:53:08,600 --> 00:53:11,360
Speaker 3: would you rather live in Virginia or California?

1044
00:53:11,520 --> 00:53:20,280
Speaker 6: Oh? Oh, oh, my gosh, Okay, I mean but California.

1045
00:53:22,080 --> 00:53:24,680
Speaker 3: Thank you, all right, excellent, you've come down on my

1046
00:53:24,800 --> 00:53:27,520
Speaker 3: side of the argument. I appreciate it from a professor

1047
00:53:27,680 --> 00:53:30,319
Speaker 3: in Virginia. All right, well, thank you very much for

1048
00:53:30,320 --> 00:53:32,160
Speaker 3: coming on the pod and talking to us about the

1049
00:53:32,160 --> 00:53:33,840
Speaker 3: process of science and discovery.

1050
00:53:33,960 --> 00:53:35,919
Speaker 5: Absolutely, thank you, great to talk.

1051
00:53:56,840 --> 00:53:59,160
Speaker 3: We're back and today we're talking about the process of

1052
00:53:59,400 --> 00:54:03,040
Speaker 3: science discovery. Up next, we have a fun interview with

1053
00:54:03,120 --> 00:54:06,520
Speaker 3: Professor Brian Keating, who's written a book about his interviews

1054
00:54:06,560 --> 00:54:10,280
Speaker 3: with Nobel Prize laureates. So it's my pleasure to welcome

1055
00:54:10,320 --> 00:54:14,240
Speaker 3: back to the podcast Professor Brian Keating. He's a cosmologist

1056
00:54:14,239 --> 00:54:17,480
Speaker 3: and a distinguished professor of physics at University of California,

1057
00:54:17,560 --> 00:54:20,879
Speaker 3: San Diego. He's also the co director of the Arthur C.

1058
00:54:20,880 --> 00:54:24,279
Speaker 3: Clark Center for the Human Imagination. He's a principal investigator

1059
00:54:24,320 --> 00:54:27,640
Speaker 3: of the Simons Observatory, and he has a side hustle

1060
00:54:27,840 --> 00:54:30,520
Speaker 3: of writing books and doing podcasts. He's the author of

1061
00:54:30,680 --> 00:54:35,080
Speaker 3: Losing the Nobel Prize of Into the Impossible of volume two,

1062
00:54:35,160 --> 00:54:37,680
Speaker 3: focused like a Nobel Prize winner will be talking about today,

1063
00:54:38,000 --> 00:54:41,000
Speaker 3: and he's the host of the End of the Impossible podcast.

1064
00:54:41,400 --> 00:54:44,239
Speaker 3: So he's one of those rare unicorns that both does

1065
00:54:44,280 --> 00:54:47,200
Speaker 3: physics research and talks about it to the public. Brian

1066
00:54:47,360 --> 00:54:48,319
Speaker 3: welcome back to the pod.

1067
00:54:48,600 --> 00:54:50,920
Speaker 2: Ah, it's great to see you, you know, yeah, it's

1068
00:54:50,960 --> 00:54:52,040
Speaker 2: always great to be with you.

1069
00:54:52,160 --> 00:54:54,879
Speaker 3: Wonderful. Well, I really enjoyed reading your book. It's fascinating

1070
00:54:55,040 --> 00:54:58,400
Speaker 3: to hear these thoughts from all of these luminaries. My

1071
00:54:58,440 --> 00:55:00,319
Speaker 3: first question to you is a simple one, though, like,

1072
00:55:00,480 --> 00:55:03,480
Speaker 3: what is your secret for getting access to all these

1073
00:55:03,480 --> 00:55:07,319
Speaker 3: Nobel Prize winners for young science journalists or aspiring podcasters

1074
00:55:07,360 --> 00:55:10,640
Speaker 3: out there? How do you manage to set up these conversations?

1075
00:55:11,000 --> 00:55:13,800
Speaker 2: Well, I think you know it's it's called the I

1076
00:55:13,840 --> 00:55:16,680
Speaker 2: think it's called the Matthew effect. So say Matthew said,

1077
00:55:17,360 --> 00:55:20,960
Speaker 2: the rich get richer effectively. So it started off, as

1078
00:55:21,000 --> 00:55:23,840
Speaker 2: you said, with the Arthur C. Clark Center for Human Imagination,

1079
00:55:24,560 --> 00:55:26,680
Speaker 2: and we were blessed here to have people like Freeman

1080
00:55:26,800 --> 00:55:31,080
Speaker 2: Dyson and you know, a local on staff, and so

1081
00:55:31,160 --> 00:55:33,200
Speaker 2: we just got to hang out. And to say he

1082
00:55:33,320 --> 00:55:35,680
Speaker 2: was my first guest on the podcast is pretty awesome.

1083
00:55:36,120 --> 00:55:39,400
Speaker 2: Awesome expression. I never thought would would you know, be

1084
00:55:40,000 --> 00:55:42,480
Speaker 2: a thing that I could say. And then after you know,

1085
00:55:42,520 --> 00:55:45,760
Speaker 2: getting people like him, then a Nobel laureate like Roger Penrose,

1086
00:55:45,760 --> 00:55:47,960
Speaker 2: who I knew before he was a Nobel laureate.

1087
00:55:48,080 --> 00:55:52,080
Speaker 7: Some say, you know, responsible for it, but that's just me.

1088
00:55:52,160 --> 00:55:55,280
Speaker 3: People are saying, yeah.

1089
00:55:54,239 --> 00:55:55,520
Speaker 7: The voices in my skull.

1090
00:55:56,160 --> 00:55:59,480
Speaker 2: And then other just great luminaries would come to give

1091
00:55:59,480 --> 00:56:02,799
Speaker 2: a colloquial very parish or you know, people like that.

1092
00:56:03,400 --> 00:56:05,040
Speaker 2: And then I thought it was a real shame and

1093
00:56:05,080 --> 00:56:08,759
Speaker 2: a disservice to the University of California, the people that

1094
00:56:08,840 --> 00:56:12,240
Speaker 2: you and I serve so selflessly in such low wages,

1095
00:56:12,640 --> 00:56:16,080
Speaker 2: that we you know, wouldn't share that with the California

1096
00:56:16,120 --> 00:56:18,840
Speaker 2: taxpayers and with the locals that couldn't make it the campus.

1097
00:56:18,840 --> 00:56:22,560
Speaker 2: And so decided to record audio and then later on

1098
00:56:22,719 --> 00:56:25,480
Speaker 2: made it into videos. And then every time someone of

1099
00:56:25,520 --> 00:56:28,399
Speaker 2: a great stature, whether a Nobel laureate or not, would

1100
00:56:28,480 --> 00:56:30,919
Speaker 2: come by, I would ask them if they wouldn't mind

1101
00:56:30,920 --> 00:56:33,000
Speaker 2: sitting for an interview. Well, you know, half of them

1102
00:56:33,000 --> 00:56:35,920
Speaker 2: agreed to come on. Unfortunately I didn't have the opportunity.

1103
00:56:35,960 --> 00:56:38,640
Speaker 2: There were only I think there's only four living women

1104
00:56:38,760 --> 00:56:40,919
Speaker 2: who have won the Nobel Prize, and only I think

1105
00:56:40,920 --> 00:56:43,480
Speaker 2: two are American or three are American, and so it

1106
00:56:43,520 --> 00:56:45,520
Speaker 2: was hard to get you know them, especially because they

1107
00:56:45,640 --> 00:56:46,600
Speaker 2: they're sick of getting asked.

1108
00:56:46,640 --> 00:56:47,239
Speaker 7: So, what's it like?

1109
00:56:47,280 --> 00:56:49,960
Speaker 2: To be a woman, you know, so I try not

1110
00:56:50,040 --> 00:56:52,560
Speaker 2: to do that. So but for this volume, the second volume,

1111
00:56:53,000 --> 00:56:56,040
Speaker 2: I did get the opportunity to speak to Donna Strickland,

1112
00:56:56,040 --> 00:57:01,600
Speaker 2: who is an amazing experimentalist and hilarious and disarming and

1113
00:57:01,800 --> 00:57:06,680
Speaker 2: ultimately incredibly gracious. I've interviewed twenty two so far, including

1114
00:57:06,800 --> 00:57:07,279
Speaker 2: I have his.

1115
00:57:07,280 --> 00:57:08,160
Speaker 7: Books, some maround.

1116
00:57:08,239 --> 00:57:12,600
Speaker 2: Here the guy who invented viagra, doctor leuig Naro, who's

1117
00:57:12,600 --> 00:57:16,280
Speaker 2: at UCLA not far from you. And here's my twenty

1118
00:57:16,320 --> 00:57:19,440
Speaker 2: second interview. And after the second group of nine, so eighteen,

1119
00:57:19,560 --> 00:57:21,760
Speaker 2: I decided I'd put out another volume.

1120
00:57:21,800 --> 00:57:23,480
Speaker 7: And that's where we're at today.

1121
00:57:23,880 --> 00:57:25,920
Speaker 3: So of all the people on the earth, or at

1122
00:57:25,960 --> 00:57:28,320
Speaker 3: least the people I know, you've probably spoken to more

1123
00:57:28,360 --> 00:57:30,000
Speaker 3: Nobel Prize winners than anybody.

1124
00:57:30,080 --> 00:57:30,760
Speaker 7: I think that's tran.

1125
00:57:31,200 --> 00:57:33,120
Speaker 3: You know. I want to dig into in a minute

1126
00:57:33,160 --> 00:57:36,120
Speaker 3: what you think their methods have in common. But what

1127
00:57:36,160 --> 00:57:38,960
Speaker 3: do you think there are moments of discovery have in common?

1128
00:57:39,000 --> 00:57:41,960
Speaker 3: Do you think they all share this like Eureka moment

1129
00:57:42,080 --> 00:57:43,320
Speaker 3: or do you think in each case it was like

1130
00:57:43,320 --> 00:57:47,800
Speaker 3: a gradual understanding of this novel realization about the universe.

1131
00:57:48,080 --> 00:57:49,480
Speaker 3: What are those moments have in common?

1132
00:57:49,880 --> 00:57:52,840
Speaker 2: Yeah, I mean, there's just a cliche from Isaac Asimov

1133
00:57:52,960 --> 00:57:56,120
Speaker 2: that you know, a real scientist doesn't say eureka, because

1134
00:57:56,120 --> 00:57:59,120
Speaker 2: that's kind of means I have found it in Greek,

1135
00:57:59,200 --> 00:58:01,560
Speaker 2: as we all know, and uh, and that means you

1136
00:58:01,640 --> 00:58:03,520
Speaker 2: found what you're looking for, which is the recipe for

1137
00:58:03,560 --> 00:58:06,160
Speaker 2: confirmation bias, which we're not supposed to fall victim to.

1138
00:58:07,080 --> 00:58:10,280
Speaker 2: So I think the you know, the reaction is more

1139
00:58:10,560 --> 00:58:12,840
Speaker 2: more often than not, you know what I call sheer

1140
00:58:12,960 --> 00:58:17,040
Speaker 2: terror of suspecting that you might be right, but with

1141
00:58:17,200 --> 00:58:20,760
Speaker 2: so little confidence and conviction that you could be wrong.

1142
00:58:21,240 --> 00:58:24,360
Speaker 2: And effectively that that least this type of paralysis where

1143
00:58:24,360 --> 00:58:26,280
Speaker 2: you're like, not sure, and so what do you do

1144
00:58:26,320 --> 00:58:28,760
Speaker 2: as a good science You just keep collecting data. And

1145
00:58:28,840 --> 00:58:31,560
Speaker 2: I think the thing that separates these individuals from you

1146
00:58:31,560 --> 00:58:35,280
Speaker 2: know me, I'll say, not you, but me, is that

1147
00:58:35,360 --> 00:58:37,880
Speaker 2: they don't, you know, kind of they had this courage

1148
00:58:37,960 --> 00:58:40,840
Speaker 2: to be you know, to lean into the discovery and

1149
00:58:40,920 --> 00:58:43,840
Speaker 2: really you know, kind of reify it and make it,

1150
00:58:44,040 --> 00:58:46,480
Speaker 2: make it whole. And and I think that that kind

1151
00:58:46,520 --> 00:58:49,160
Speaker 2: of courage is rare. It's rare and individuals, let alone

1152
00:58:49,200 --> 00:58:52,240
Speaker 2: and scientists. So I think that ability to see that

1153
00:58:52,280 --> 00:58:54,760
Speaker 2: they've done enough that like the perfect is the enemy

1154
00:58:54,760 --> 00:58:57,280
Speaker 2: of the good, enough that you know, once you've established

1155
00:58:57,280 --> 00:58:59,480
Speaker 2: this thing, is now to you to kind of then

1156
00:58:59,600 --> 00:59:03,520
Speaker 2: convert from scientists to what I call salesman mode, where

1157
00:59:03,680 --> 00:59:06,520
Speaker 2: you really have to convince other scientists that you're right,

1158
00:59:06,520 --> 00:59:08,240
Speaker 2: and it's not enough for you to think you're brilliant.

1159
00:59:08,560 --> 00:59:11,400
Speaker 2: I mean, only one person in this whole collection of

1160
00:59:11,400 --> 00:59:16,520
Speaker 2: twenty two people has admitted to me that they deserved

1161
00:59:16,520 --> 00:59:18,520
Speaker 2: the Noble Prize. Like, you know, there was something they

1162
00:59:18,560 --> 00:59:20,560
Speaker 2: were gone for their whole life. They knew where they

1163
00:59:20,560 --> 00:59:23,200
Speaker 2: were going to win it. It was preternaturally preordained.

1164
00:59:23,320 --> 00:59:25,160
Speaker 3: Yeah, So what do you think these folks have done

1165
00:59:25,280 --> 00:59:28,440
Speaker 3: to prepare themselves for these moments, for these great discoveries.

1166
00:59:28,960 --> 00:59:31,760
Speaker 3: Is it just luck? Or have they sort of made themselves?

1167
00:59:31,760 --> 00:59:33,880
Speaker 3: Have they sort of set themselves up to be lucky?

1168
00:59:34,200 --> 00:59:38,240
Speaker 2: Some say that they are lucky a lot just never

1169
00:59:38,360 --> 00:59:41,400
Speaker 2: stop working on stuff, and the fact that they won

1170
00:59:41,520 --> 00:59:45,040
Speaker 2: a Nobel Prize was sort of incidental that it was,

1171
00:59:45,360 --> 00:59:47,920
Speaker 2: you know, it was something that they didn't plan on.

1172
00:59:48,040 --> 00:59:48,200
Speaker 4: You know.

1173
00:59:48,240 --> 00:59:51,480
Speaker 2: For example, I talked to Georgio Parisi, who you know,

1174
00:59:51,520 --> 00:59:54,760
Speaker 2: won the Nobel Prize in part for you know, predictions

1175
00:59:54,760 --> 00:59:59,400
Speaker 2: and theoretical physics ranging from spin glasses what are called

1176
00:59:59,440 --> 01:00:04,640
Speaker 2: spin glass to your kind of chaotic invariance and chaos theory.

1177
01:00:04,760 --> 01:00:06,680
Speaker 2: And there's a few people in the book that have

1178
01:00:06,960 --> 01:00:10,360
Speaker 2: relevance to chaos theory. And so it's almost impossible to

1179
01:00:11,120 --> 01:00:13,520
Speaker 2: kind of predict that I'm gonna, you know, go out

1180
01:00:13,520 --> 01:00:15,200
Speaker 2: and solve this thing that has to do with how

1181
01:00:15,200 --> 01:00:18,400
Speaker 2: these birds migrate called starlings, and how they flock and

1182
01:00:18,960 --> 01:00:22,200
Speaker 2: the behavior and the phase transitions that they exhibit after

1183
01:00:22,280 --> 01:00:26,640
Speaker 2: working on so ten symmetry group, after looking at spin

1184
01:00:26,720 --> 01:00:29,760
Speaker 2: glasses and so forth. So a lot of them have

1185
01:00:29,840 --> 01:00:33,600
Speaker 2: these very tortured paths to the Nobel Prize. But their

1186
01:00:33,640 --> 01:00:38,000
Speaker 2: intellects are just such of such a magnitude that it's

1187
01:00:38,080 --> 01:00:39,760
Speaker 2: sort of obvious.

1188
01:00:39,440 --> 01:00:41,520
Speaker 7: In hindsight that they would get to this level.

1189
01:00:41,880 --> 01:00:44,680
Speaker 3: And what about their daily habits? Is there anything they

1190
01:00:44,680 --> 01:00:47,160
Speaker 3: have in common? You know, do they all start with

1191
01:00:47,200 --> 01:00:50,480
Speaker 3: the same super espresso or do they all you know,

1192
01:00:50,640 --> 01:00:54,640
Speaker 3: like block out timed for themselves, or is there anything

1193
01:00:54,640 --> 01:00:57,040
Speaker 3: there that's like very concrete that we can extract from

1194
01:00:57,040 --> 01:00:57,640
Speaker 3: their success.

1195
01:00:58,200 --> 01:01:02,080
Speaker 2: Unfortunately, no, there's no like you know, special cereal, you know,

1196
01:01:04,520 --> 01:01:06,200
Speaker 2: Wheedi's or sweeties or.

1197
01:01:06,160 --> 01:01:06,800
Speaker 7: Something like that.

1198
01:01:07,920 --> 01:01:11,000
Speaker 2: But there are you know, kind of traits I would

1199
01:01:11,040 --> 01:01:15,040
Speaker 2: say there wouldn't say necessarily habits, although they all have

1200
01:01:15,200 --> 01:01:19,680
Speaker 2: this you know, kind of chimeric ability to be incredibly

1201
01:01:20,360 --> 01:01:23,200
Speaker 2: joyous when they're working. It's not a drudge. It's not

1202
01:01:23,400 --> 01:01:26,840
Speaker 2: something that they do if that's tedious or and I

1203
01:01:26,880 --> 01:01:29,960
Speaker 2: found it, you know, a little bit depressing, because what

1204
01:01:30,000 --> 01:01:33,960
Speaker 2: we do is experimental scientists working on big projects. Almost

1205
01:01:34,000 --> 01:01:36,200
Speaker 2: none of it, at least in my experiences, has to

1206
01:01:36,240 --> 01:01:39,000
Speaker 2: do with physics. I mean, yesterday, we are on telecon

1207
01:01:39,120 --> 01:01:41,160
Speaker 2: with my fellow you know, kind of co leaders, and

1208
01:01:41,200 --> 01:01:44,800
Speaker 2: we're talking about like how to get these louvers that

1209
01:01:44,960 --> 01:01:49,240
Speaker 2: open on the generators that power the Simons observatories, telescope

1210
01:01:49,280 --> 01:01:53,000
Speaker 2: motor platforms when they get clogged with snow and you

1211
01:01:53,040 --> 01:01:56,520
Speaker 2: want to you know, ingest the right volume of air

1212
01:01:56,640 --> 01:01:58,919
Speaker 2: to cool the turbines. You have to cool them even

1213
01:01:58,920 --> 01:02:02,000
Speaker 2: though you're you know, eight meters of snow fell this year,

1214
01:02:02,040 --> 01:02:04,320
Speaker 2: you know, and so it's just like, oh, the concrete

1215
01:02:04,400 --> 01:02:08,160
Speaker 2: you know, contractors on strike in Chile, which happens you know,

1216
01:02:08,560 --> 01:02:10,840
Speaker 2: once a month it's the season or whatever, and then

1217
01:02:10,920 --> 01:02:13,040
Speaker 2: we have to deal with so it's rare that we

1218
01:02:13,080 --> 01:02:16,440
Speaker 2: get to spend time like thinking about the cosmic macure background.

1219
01:02:16,840 --> 01:02:20,040
Speaker 2: And so I think the tenacity, the intellectual rigor, and

1220
01:02:20,120 --> 01:02:22,640
Speaker 2: the desire to lean into teaching and service and giving

1221
01:02:22,680 --> 01:02:24,720
Speaker 2: back after the prize, And I'm sure they did before

1222
01:02:24,760 --> 01:02:27,640
Speaker 2: the prize too, But that's a commonality I observe in

1223
01:02:27,680 --> 01:02:30,560
Speaker 2: their current state as I got to observe them collapsed

1224
01:02:30,560 --> 01:02:31,240
Speaker 2: in that way from me.

1225
01:02:31,800 --> 01:02:34,560
Speaker 3: And you draw another lesson from all of their experiences.

1226
01:02:34,680 --> 01:02:36,160
Speaker 3: I mean, it's in the title of your book and

1227
01:02:36,200 --> 01:02:38,560
Speaker 3: you go into it in great detail. You think that

1228
01:02:38,600 --> 01:02:41,320
Speaker 3: folks should focus on a topic, that we should go

1229
01:02:41,480 --> 01:02:45,440
Speaker 3: deep instead of broad as scientists. That's sort of clashes

1230
01:02:45,480 --> 01:02:48,760
Speaker 3: with some historical trends, right, folks like Gauss or Newton,

1231
01:02:49,040 --> 01:02:51,600
Speaker 3: you know, they're extremely broad. Why do you think that

1232
01:02:51,680 --> 01:02:54,840
Speaker 3: today scientists have to focus have to be deeper?

1233
01:02:55,200 --> 01:02:58,280
Speaker 2: Yeah, I think it's the fields and the amount of

1234
01:02:58,320 --> 01:03:03,280
Speaker 2: knowledge has expanded so much done it's it's basically impossible

1235
01:03:03,400 --> 01:03:07,720
Speaker 2: even when you focus on one subfield, sub sub subfield

1236
01:03:07,760 --> 01:03:10,800
Speaker 2: or you know, substances is a subfield, and to do that,

1237
01:03:11,040 --> 01:03:13,080
Speaker 2: you know, it's easier to do that in one field

1238
01:03:13,160 --> 01:03:16,160
Speaker 2: obviously than it is in Many, and I think it's

1239
01:03:16,200 --> 01:03:19,520
Speaker 2: incredibly fascinating when you see that they could do so

1240
01:03:19,600 --> 01:03:21,960
Speaker 2: many other things. You know, Ryan hard Genzel is a

1241
01:03:22,000 --> 01:03:24,240
Speaker 2: great example, like he could have done any He actually

1242
01:03:24,240 --> 01:03:28,520
Speaker 2: could have been an Olympic athlete. He was an incredible athlete.

1243
01:03:28,600 --> 01:03:32,520
Speaker 2: His father was very into physical sports in Germany. And

1244
01:03:32,800 --> 01:03:35,040
Speaker 2: you know, he could have done a lot of things,

1245
01:03:35,200 --> 01:03:39,680
Speaker 2: not just in outside of science or in technology and optics.

1246
01:03:39,720 --> 01:03:42,680
Speaker 2: You know, he really pioneered along with our colleague in

1247
01:03:42,680 --> 01:03:46,120
Speaker 2: the University of California, Andrea I Guez, this this concept

1248
01:03:46,320 --> 01:03:50,400
Speaker 2: application rather of adaptive optics to being up the black

1249
01:03:50,400 --> 01:03:53,040
Speaker 2: hole in the Milky Way Center as a laboratory to

1250
01:03:53,040 --> 01:03:54,200
Speaker 2: test general relativity.

1251
01:03:54,440 --> 01:03:55,480
Speaker 7: So there's so many things there.

1252
01:03:55,480 --> 01:03:57,280
Speaker 2: He could have gotten into optics, he could have gotten

1253
01:03:57,320 --> 01:04:02,160
Speaker 2: into general relativity, experimental, he could have done more stuff.

1254
01:04:02,280 --> 01:04:04,240
Speaker 7: But he could have also gone into.

1255
01:04:04,360 --> 01:04:07,400
Speaker 2: You know, DARPA, and you know, would they use these

1256
01:04:07,560 --> 01:04:11,320
Speaker 2: the same techniques in for example, in adaptive optics, where

1257
01:04:11,320 --> 01:04:14,480
Speaker 2: we have these deformable mirrors that compensate for the distortion

1258
01:04:14,640 --> 01:04:19,600
Speaker 2: of the Earth's lens like atmosphere that causes stars to twinkle, twinkle,

1259
01:04:19,840 --> 01:04:20,400
Speaker 2: Little Star.

1260
01:04:21,160 --> 01:04:22,120
Speaker 7: He could have applied that.

1261
01:04:22,080 --> 01:04:25,120
Speaker 2: As they do now to like sniper scopes, you know,

1262
01:04:25,120 --> 01:04:27,880
Speaker 2: which is an application of adaptive optics that you know

1263
01:04:28,000 --> 01:04:31,320
Speaker 2: is for military purposes. But there's many other things, artificial guides.

1264
01:04:31,520 --> 01:04:31,960
Speaker 7: A lot of the.

1265
01:04:31,880 --> 01:04:35,560
Speaker 2: Technology was classified, you know in the US at least,

1266
01:04:35,920 --> 01:04:37,800
Speaker 2: so he could have done a multitude of things.

1267
01:04:37,840 --> 01:04:39,280
Speaker 7: But that's really what he's done.

1268
01:04:39,440 --> 01:04:42,360
Speaker 2: And I think you know it's but it's he's only

1269
01:04:42,560 --> 01:04:46,640
Speaker 2: he's the literal next generation after Charles Towns, also a

1270
01:04:46,720 --> 01:04:50,040
Speaker 2: U see, you know, professor fellow of ours and and

1271
01:04:50,200 --> 01:04:54,800
Speaker 2: he you know, is known for extremely broad knowledge. I mean,

1272
01:04:54,840 --> 01:04:58,240
Speaker 2: he credits his his ability to blow glass. I don't

1273
01:04:58,240 --> 01:05:00,080
Speaker 2: know if knew that he went to like house in

1274
01:05:00,480 --> 01:05:04,240
Speaker 2: some small school had a like blow glass for you know,

1275
01:05:04,640 --> 01:05:07,520
Speaker 2: champagne bottles, and then that became very useful in making

1276
01:05:08,080 --> 01:05:13,440
Speaker 2: vacuum tubes for you know, eventually creating rarefied gas fials

1277
01:05:13,560 --> 01:05:17,560
Speaker 2: that were then used to do maser stimulation. That led

1278
01:05:17,600 --> 01:05:19,920
Speaker 2: to the mazer and then the laser, and then he

1279
01:05:19,960 --> 01:05:23,440
Speaker 2: got into like looking for aliens and optical search for

1280
01:05:23,480 --> 01:05:28,320
Speaker 2: extraterrestrial intelligence and adaptive optic just incredibly, so that was

1281
01:05:28,360 --> 01:05:32,440
Speaker 2: one generation between him and his advisy is his student

1282
01:05:33,000 --> 01:05:36,440
Speaker 2: Reinhart Gonzel and yet you know he could do it

1283
01:05:36,520 --> 01:05:40,080
Speaker 2: and it was I don't think Reinhart's less intelligent. So yeah,

1284
01:05:40,120 --> 01:05:42,320
Speaker 2: from my perspective, I think there's just so much to

1285
01:05:42,400 --> 01:05:46,560
Speaker 2: know now, So it's hard to focus because so many distractions.

1286
01:05:46,720 --> 01:05:48,600
Speaker 2: I'm not talking about outside the lot, I'm talking about

1287
01:05:48,640 --> 01:05:49,680
Speaker 2: inside your own field.

1288
01:05:50,120 --> 01:05:50,960
Speaker 7: How do you focus?

1289
01:05:51,000 --> 01:05:53,960
Speaker 2: And I like this acronym that people you know use

1290
01:05:54,080 --> 01:05:56,000
Speaker 2: that you know, focus should be thought of as an

1291
01:05:56,040 --> 01:06:01,760
Speaker 2: acronym for follow one course until success, and I wish

1292
01:06:01,840 --> 01:06:03,640
Speaker 2: I had done that. You know, I'm glad that I

1293
01:06:03,640 --> 01:06:06,720
Speaker 2: have kind of a broad education, not just to within

1294
01:06:06,800 --> 01:06:09,920
Speaker 2: physics but outside of physics. But I think there's a

1295
01:06:09,960 --> 01:06:13,000
Speaker 2: lot greater path to success to do something that only

1296
01:06:13,040 --> 01:06:13,600
Speaker 2: you can do.

1297
01:06:14,040 --> 01:06:16,560
Speaker 3: But how do you know when to focus? Like, how

1298
01:06:16,560 --> 01:06:19,000
Speaker 3: do you know as a young scientist that you found

1299
01:06:19,040 --> 01:06:21,480
Speaker 3: the right field? Personally, I started out in plasma physics

1300
01:06:21,520 --> 01:06:23,560
Speaker 3: and then solid state physics, and it wasn't until I

1301
01:06:23,600 --> 01:06:25,400
Speaker 3: got to particle physics and I was like, oh, this

1302
01:06:25,480 --> 01:06:28,200
Speaker 3: is my jam, this is where I want to dive deep.

1303
01:06:28,680 --> 01:06:30,640
Speaker 3: So you know, if I had focused too early, i'd

1304
01:06:30,640 --> 01:06:33,160
Speaker 3: be doing fusion research right now and promising you know,

1305
01:06:33,160 --> 01:06:36,160
Speaker 3: the Tokomac would turn on and ignite next year for

1306
01:06:36,200 --> 01:06:38,600
Speaker 3: the last ten years. So how do you know when

1307
01:06:38,680 --> 01:06:39,240
Speaker 3: to focus?

1308
01:06:39,640 --> 01:06:43,240
Speaker 2: So I think maybe you wouldn't in the sense that

1309
01:06:43,600 --> 01:06:46,840
Speaker 2: you weren't really able to focus at the level of say,

1310
01:06:47,360 --> 01:06:50,520
Speaker 2: you know, Michael Jordan practicing a thousand jump shots after

1311
01:06:50,560 --> 01:06:51,880
Speaker 2: every game or something like that.

1312
01:06:51,960 --> 01:06:52,160
Speaker 7: You know.

1313
01:06:52,760 --> 01:06:56,360
Speaker 2: In other words, you had to find your path and

1314
01:06:56,440 --> 01:06:59,080
Speaker 2: then you followed the course that led to success. In

1315
01:06:59,120 --> 01:07:02,400
Speaker 2: your case, I was particle physics. I also started off

1316
01:07:02,480 --> 01:07:05,360
Speaker 2: I want to be a condensed matter theorist. God forbid,

1317
01:07:05,760 --> 01:07:09,800
Speaker 2: you know. Now I'm an experimental cosmologist. But I think

1318
01:07:09,960 --> 01:07:12,960
Speaker 2: a lot of my success, at least are my ability

1319
01:07:13,000 --> 01:07:15,920
Speaker 2: to maintain This is not the subject at all. I

1320
01:07:15,960 --> 01:07:18,400
Speaker 2: think has nothing to do with the subject. So from

1321
01:07:18,440 --> 01:07:22,520
Speaker 2: my perspective, the focus of the book is to implement

1322
01:07:22,640 --> 01:07:26,280
Speaker 2: skills and tactics and habits and strategies so that you

1323
01:07:26,320 --> 01:07:27,640
Speaker 2: can become an expert.

1324
01:07:28,000 --> 01:07:31,280
Speaker 3: So there's this lore about big discoveries. I've often heard

1325
01:07:31,320 --> 01:07:35,040
Speaker 3: people say that you can't make paradigm shifting discoveries after

1326
01:07:35,080 --> 01:07:38,760
Speaker 3: you're thirty or something. So in your experience talking to folks,

1327
01:07:38,800 --> 01:07:41,120
Speaker 3: did they make these discoveries when they were young or

1328
01:07:41,200 --> 01:07:44,200
Speaker 3: is it after like decades of focusing and refining and

1329
01:07:44,240 --> 01:07:46,720
Speaker 3: coming to the edge of the field that they've made

1330
01:07:46,760 --> 01:07:47,600
Speaker 3: their discoveries.

1331
01:07:48,000 --> 01:07:50,240
Speaker 7: Most of them did make it as young people.

1332
01:07:51,760 --> 01:07:52,240
Speaker 3: Yeah.

1333
01:07:52,280 --> 01:07:55,400
Speaker 2: Well, well here's the thing though, Well, first time we say,

1334
01:07:55,480 --> 01:07:58,320
Speaker 2: I think that also correlates with what I said earlier,

1335
01:07:58,360 --> 01:08:00,200
Speaker 2: that you know, you want to get on course early

1336
01:08:00,760 --> 01:08:04,320
Speaker 2: in life. I don't necessarily correlate it with age as

1337
01:08:04,360 --> 01:08:07,680
Speaker 2: well as I do with thinking yourself as a professional.

1338
01:08:08,080 --> 01:08:10,720
Speaker 2: So getting on track early is I think, you know,

1339
01:08:10,760 --> 01:08:13,360
Speaker 2: a cornerstone. So they all got on track that some

1340
01:08:13,440 --> 01:08:15,800
Speaker 2: of them did, you know, kind of branch out either

1341
01:08:16,120 --> 01:08:19,200
Speaker 2: after or at the same time, you know, most notably,

1342
01:08:19,280 --> 01:08:22,000
Speaker 2: you know, I think Kip Thorn is probably the exception

1343
01:08:22,120 --> 01:08:23,880
Speaker 2: that he really did the work that I want him

1344
01:08:23,880 --> 01:08:26,599
Speaker 2: the Nobel Prize in his fifties, you know, if you'd

1345
01:08:26,640 --> 01:08:29,920
Speaker 2: think about it. But the groundwork was laid in his

1346
01:08:30,120 --> 01:08:32,960
Speaker 2: twenties and thirties, so I think that's important to know.

1347
01:08:33,080 --> 01:08:35,040
Speaker 2: But but the way that they get to it, everyone

1348
01:08:35,080 --> 01:08:36,639
Speaker 2: gets to Sweden in a different way.

1349
01:08:37,920 --> 01:08:40,120
Speaker 3: So talking to all these folks, has it changed the

1350
01:08:40,120 --> 01:08:41,360
Speaker 3: way that you do science?

1351
01:08:41,720 --> 01:08:44,680
Speaker 2: Well, first of all, I had an unhealthy obsession with

1352
01:08:44,720 --> 01:08:47,600
Speaker 2: the Nobel Prize as a as a kid, as a

1353
01:08:47,640 --> 01:08:50,639
Speaker 2: young scientist, as I wrote about in my first book,

1354
01:08:50,840 --> 01:08:53,840
Speaker 2: Losing the Nobel Prize, which is a memoir about, you know,

1355
01:08:53,960 --> 01:08:58,440
Speaker 2: the bicep affair of thinking we discovered cosmic inflationary gravitational

1356
01:08:58,479 --> 01:09:01,240
Speaker 2: waves and then having to re track that, and then

1357
01:09:01,680 --> 01:09:04,320
Speaker 2: you know the aftermath of that, biting the dust as

1358
01:09:04,360 --> 01:09:06,320
Speaker 2: you called it, very painfully.

1359
01:09:06,360 --> 01:09:08,400
Speaker 7: So damn it. I'm still smarting from that.

1360
01:09:08,720 --> 01:09:11,840
Speaker 2: But in reality, yeah, how do you recover? How do

1361
01:09:11,880 --> 01:09:15,360
Speaker 2: you do science? How do you compete with your colleagues

1362
01:09:15,439 --> 01:09:17,960
Speaker 2: and all sorts of nasty stuff about science that you

1363
01:09:18,000 --> 01:09:20,160
Speaker 2: don't really ever get to see, because science is always

1364
01:09:20,200 --> 01:09:22,719
Speaker 2: presented as you know, so and so had this brilliant idea,

1365
01:09:22,720 --> 01:09:24,479
Speaker 2: and then so and so won the Nobel Prize, and

1366
01:09:24,479 --> 01:09:26,479
Speaker 2: then this is now how we teach it, even our

1367
01:09:26,560 --> 01:09:30,080
Speaker 2: labs at UCSD. I'm sure Ervine too, you know we're

1368
01:09:30,120 --> 01:09:32,680
Speaker 2: teaching here's a Nobel Prize winning experiment, here's some of

1369
01:09:32,720 --> 01:09:35,879
Speaker 2: these things took forty years to get to work, and

1370
01:09:35,920 --> 01:09:38,840
Speaker 2: we just do it in an afternoon. So I think there,

1371
01:09:39,200 --> 01:09:41,720
Speaker 2: it's changed my opinion that I don't venerate it. I

1372
01:09:41,760 --> 01:09:45,080
Speaker 2: don't venerate the prize. The people are impressive, but they're

1373
01:09:45,120 --> 01:09:47,920
Speaker 2: just people, and a lot of them. Bary Barrass wrote

1374
01:09:47,920 --> 01:09:51,080
Speaker 2: the forward to the first volume, Think like a Nobel Prize,

1375
01:09:51,120 --> 01:09:55,200
Speaker 2: and you know, he said that he had the imposter

1376
01:09:55,360 --> 01:09:58,720
Speaker 2: syndrome even worse after he won the Nobel Prize than

1377
01:09:58,760 --> 01:09:59,760
Speaker 2: he did before it.

1378
01:10:00,120 --> 01:10:01,960
Speaker 7: I said, what are you talking about? He said, well,

1379
01:10:02,120 --> 01:10:02,720
Speaker 7: when you went in.

1380
01:10:02,680 --> 01:10:05,880
Speaker 2: About prize keating, you'll never know this feeling. But you

1381
01:10:05,920 --> 01:10:09,799
Speaker 2: go to Stockholm and you get this huge gold medal,

1382
01:10:09,920 --> 01:10:13,040
Speaker 2: like you know, flava flame, and they want to make

1383
01:10:13,080 --> 01:10:16,040
Speaker 2: sure that you confirm that you got your prize due

1384
01:10:16,080 --> 01:10:18,519
Speaker 2: to you, and so they make you sign this book,

1385
01:10:18,560 --> 01:10:21,639
Speaker 2: this ledger that has every single Nobel laureate in physics

1386
01:10:21,640 --> 01:10:24,559
Speaker 2: back to the beginning in nineteen o one with the

1387
01:10:24,640 --> 01:10:28,000
Speaker 2: invention of the X ray by Wilhelm Renken. And so

1388
01:10:28,600 --> 01:10:32,120
Speaker 2: Barry tells me in twenty you know, twenty twenty that

1389
01:10:32,200 --> 01:10:34,680
Speaker 2: when he won it in twenty seventeen, he went there

1390
01:10:34,720 --> 01:10:37,160
Speaker 2: and he's a curious guy and he's turns the pages

1391
01:10:37,200 --> 01:10:39,679
Speaker 2: in the book and he sees, you know, oh my god,

1392
01:10:39,720 --> 01:10:42,920
Speaker 2: there's there's fine man, Oh my god, there's you know,

1393
01:10:43,040 --> 01:10:47,280
Speaker 2: Madame Currie, Oh my god, there's Einstein. And he said

1394
01:10:47,280 --> 01:10:49,400
Speaker 2: that he saw Einstein's signature. He said, I don't deserve

1395
01:10:49,439 --> 01:10:51,880
Speaker 2: to be in the same book as him, let alone,

1396
01:10:51,920 --> 01:10:54,519
Speaker 2: you know, be in the same mention as him. And

1397
01:10:54,560 --> 01:10:56,800
Speaker 2: I said, Barry, I've got good news, and good news

1398
01:10:56,800 --> 01:11:00,000
Speaker 2: for you. First of all, Einstein had the imposter syndrome.

1399
01:11:00,320 --> 01:11:02,759
Speaker 2: And he's like, what are you talking about. He's like Einstein.

1400
01:11:02,840 --> 01:11:06,759
Speaker 2: I told him. Einstein wrote that Isaac Newton contributed more

1401
01:11:07,240 --> 01:11:11,400
Speaker 2: to civilization than even he did to science, and his

1402
01:11:11,560 --> 01:11:14,920
Speaker 2: contributions to science will never be matched again. And I said,

1403
01:11:14,920 --> 01:11:17,920
Speaker 2: but that's not all, Arry, because Isaac Newton had the

1404
01:11:17,960 --> 01:11:20,679
Speaker 2: imposter syndrome. And now he's like, oh, you gotta be kidding.

1405
01:11:21,840 --> 01:11:24,400
Speaker 2: And then he said, I told him no. Actually, Isaac

1406
01:11:24,439 --> 01:11:26,800
Speaker 2: Newton felt that he utterly failed to live up to

1407
01:11:27,400 --> 01:11:29,240
Speaker 2: the standard set by his hero.

1408
01:11:29,280 --> 01:11:30,799
Speaker 7: Wow Jesus Christ.

1409
01:11:30,960 --> 01:11:34,479
Speaker 2: Okay, in fact, he reputedly died of virgin in order

1410
01:11:34,520 --> 01:11:36,400
Speaker 2: to emulate the only way he could emulate. You know,

1411
01:11:36,720 --> 01:11:40,280
Speaker 2: couldn't turn loaves into fishes, water into wine, but he

1412
01:11:40,320 --> 01:11:42,200
Speaker 2: could die of virgin and in fact he did.

1413
01:11:42,520 --> 01:11:43,720
Speaker 7: But some say that was because of his.

1414
01:11:43,720 --> 01:11:48,920
Speaker 3: Personality, Like the first inel. That's right.

1415
01:11:48,960 --> 01:11:50,160
Speaker 7: So it's changed me.

1416
01:11:50,280 --> 01:11:53,439
Speaker 2: I think to not venerate the prize as much as

1417
01:11:53,479 --> 01:11:55,639
Speaker 2: I do. Think it's type of idol on So one.

1418
01:11:55,560 --> 01:11:57,559
Speaker 3: Of the things I like about your book is that

1419
01:11:57,640 --> 01:12:00,839
Speaker 3: you look forward to the next generations and you imagine

1420
01:12:00,840 --> 01:12:03,880
Speaker 3: that young people are reading it and thinking about their careers,

1421
01:12:04,479 --> 01:12:06,960
Speaker 3: and so what is the takeaway for young readers? You

1422
01:12:06,960 --> 01:12:10,120
Speaker 3: have to give them one piece of advice. To aspiring scientists,

1423
01:12:10,240 --> 01:12:13,679
Speaker 3: or you're talking to your graduate students or prospective grad students,

1424
01:12:13,800 --> 01:12:16,000
Speaker 3: what do you advise them about how to chart a

1425
01:12:16,040 --> 01:12:18,840
Speaker 3: path through a changing field, you know, which is different

1426
01:12:18,840 --> 01:12:20,720
Speaker 3: from the field that we grew up in and will

1427
01:12:20,760 --> 01:12:22,800
Speaker 3: be different in twenty years. What is your advice to

1428
01:12:22,840 --> 01:12:23,559
Speaker 3: the next generation.

1429
01:12:23,880 --> 01:12:24,800
Speaker 7: That's exactly right.

1430
01:12:24,960 --> 01:12:27,840
Speaker 2: So for me, it's all comes down to conservation laws

1431
01:12:28,080 --> 01:12:31,479
Speaker 2: in this case, conservation of energy, you know, energy time,

1432
01:12:31,560 --> 01:12:33,880
Speaker 2: whatever you want to say, and it's very hard to

1433
01:12:34,040 --> 01:12:36,960
Speaker 2: but if you concentrate and you conserve, it's a form

1434
01:12:37,000 --> 01:12:40,200
Speaker 2: of focus, right. I mean, you take a magnifying glass,

1435
01:12:40,200 --> 01:12:42,519
Speaker 2: you take a light, you can concentrate the sunlight and

1436
01:12:43,240 --> 01:12:46,360
Speaker 2: burn up those little worms that no, no, I'm just kidding.

1437
01:12:46,520 --> 01:12:49,559
Speaker 2: I never do that out there. Peta but you can

1438
01:12:49,640 --> 01:12:51,559
Speaker 2: melt an army man, right, You ever did that there?

1439
01:12:51,960 --> 01:12:55,040
Speaker 7: Yeah, But you can't just hold them up in the sun.

1440
01:12:55,120 --> 01:12:55,280
Speaker 3: Right.

1441
01:12:55,320 --> 01:12:57,240
Speaker 2: So you have to concentrate, You have to focus, you

1442
01:12:57,320 --> 01:13:00,479
Speaker 2: have to conserve it and narrow down. So for me,

1443
01:13:00,560 --> 01:13:04,840
Speaker 2: it's prioritization. What is the most important thing on your plate?

1444
01:13:04,960 --> 01:13:08,800
Speaker 2: Like do the hardest tasks that are most necessary. You know,

1445
01:13:08,840 --> 01:13:12,599
Speaker 2: there's this Eisenhower matrix framework and an important urgent you know,

1446
01:13:12,640 --> 01:13:14,640
Speaker 2: and whatever.

1447
01:13:14,320 --> 01:13:16,360
Speaker 7: Different spectrum of tasks.

1448
01:13:16,400 --> 01:13:18,960
Speaker 2: And you know, for me, it's like the most important

1449
01:13:18,960 --> 01:13:20,800
Speaker 2: thing I think a young person can do is to

1450
01:13:20,840 --> 01:13:24,080
Speaker 2: say no, because the better you are. You know, there's

1451
01:13:24,320 --> 01:13:26,600
Speaker 2: there's a saying in the business world like if you

1452
01:13:26,640 --> 01:13:29,160
Speaker 2: want something done right, ask someone who's too busy to

1453
01:13:29,240 --> 01:13:31,960
Speaker 2: do it, because they're the ones that are. And you

1454
01:13:32,040 --> 01:13:34,439
Speaker 2: know this, there's like only a handful of people on

1455
01:13:34,479 --> 01:13:38,240
Speaker 2: an experiment that really do you know, ninety percent of

1456
01:13:38,240 --> 01:13:40,320
Speaker 2: the work. There might be ten percent that do ninety

1457
01:13:40,320 --> 01:13:44,160
Speaker 2: percent ork And those people they're so oversubscribed that their

1458
01:13:44,280 --> 01:13:47,400
Speaker 2: energy is so drained or so distracted and they're so

1459
01:13:48,040 --> 01:13:51,400
Speaker 2: you know, kind of torn by their eagerness to please

1460
01:13:52,320 --> 01:13:55,519
Speaker 2: that they don't set boundaries, and so I really do

1461
01:13:55,720 --> 01:13:59,360
Speaker 2: tell my students to concentrate, conserve, focus whatever you want

1462
01:13:59,400 --> 01:14:03,280
Speaker 2: to say on energy, and do that by having appropriate

1463
01:14:03,280 --> 01:14:05,639
Speaker 2: boundaries in time and in space.

1464
01:14:05,760 --> 01:14:08,320
Speaker 3: All right, well, thanks very much. The book is called

1465
01:14:08,680 --> 01:14:12,679
Speaker 3: Into the Impossible, Volume two Focus like end Nobel Prize winner,

1466
01:14:12,920 --> 01:14:14,960
Speaker 3: Thanks very much for coming and telling us about all

1467
01:14:14,960 --> 01:14:18,400
Speaker 3: the wisdom you've gleaned from all of these successful stories.

1468
01:14:18,600 --> 01:14:19,320
Speaker 7: Thank you, Daniel.

1469
01:14:19,360 --> 01:14:21,280
Speaker 2: I want to get back to your audience too, because

1470
01:14:21,280 --> 01:14:23,400
Speaker 2: I love the audience and your audience is kind of

1471
01:14:23,400 --> 01:14:26,519
Speaker 2: a key demographic. So for people that do get a

1472
01:14:26,560 --> 01:14:29,599
Speaker 2: copy of this book, if you're in academia, I love

1473
01:14:29,640 --> 01:14:30,760
Speaker 2: to give out these meteorites.

1474
01:14:30,760 --> 01:14:32,120
Speaker 7: I think I've given them to Daniel.

1475
01:14:32,360 --> 01:14:33,439
Speaker 3: I have one here on my shelf.

1476
01:14:33,479 --> 01:14:36,080
Speaker 2: Yes, give them to your kids and so to get

1477
01:14:36,080 --> 01:14:39,520
Speaker 2: one if you're in academia, like my ideal target demographic,

1478
01:14:39,960 --> 01:14:43,240
Speaker 2: just go to Brian Keating dot com slash edu and

1479
01:14:43,640 --> 01:14:45,639
Speaker 2: sign up for my mailing list, which I sent out

1480
01:14:45,640 --> 01:14:49,000
Speaker 2: every Monday with some cool stuff including appearances like this

1481
01:14:49,200 --> 01:14:52,080
Speaker 2: and thoughts on academia and life as a scientist, et cetera.

1482
01:14:52,520 --> 01:14:54,960
Speaker 2: So Brian Kane dot com slash du with your edu

1483
01:14:55,000 --> 01:14:57,519
Speaker 2: email address, and if you live in the USA, you

1484
01:14:57,560 --> 01:15:00,679
Speaker 2: will get one of these beauties that was delivered by gravity,

1485
01:15:00,760 --> 01:15:02,120
Speaker 2: not the US Postal Service.

1486
01:15:02,200 --> 01:15:05,679
Speaker 3: I will deliver it amazing. And you can also catch

1487
01:15:05,680 --> 01:15:09,599
Speaker 3: Brian on his podcast Into the Impossible. All right, Thanks

1488
01:15:09,680 --> 01:15:11,080
Speaker 3: very much, Brian, Thanks Dan.

1489
01:15:18,160 --> 01:15:22,000
Speaker 1: Daniel and Kelly's Extraordinary Universe is produced by iHeartRadio. We

1490
01:15:22,040 --> 01:15:23,439
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1491
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01:15:26,720 --> 01:15:29,360
Speaker 3: have about this Extraordinary Universe.

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1497
01:15:39,680 --> 01:15:42,880
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1498
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1499
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