#96 - David Epstein: How a range of experience leads to better performance in a highly specialized world
Episode Stats
Length
2 hours and 37 minutes
Words per minute
220.06898
Harmful content
Misogyny
23
sentences flagged
Hate speech
19
sentences flagged
Summary
David Epstein is the bestselling author of The Sports Gene and Range: Why Generalists Triumph in a Specialized World, which ironically makes him a specialist of generalists. He was previously a science and investigative reporter at ProPublica and a senior writer at Sports Illustrated.
Transcript
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Hey everyone, welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,
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the end of this episode, I'll explain what those benefits are. Or if you want to learn more now,
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head over to peteratiyahmd.com forward slash subscribe. Now, without further delay, here's
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today's episode. I guess this week is David Epstein. David is the author of the bestselling book,
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The Sports Gene, and more recently, Range, Why Generalists Triumph in a Specialized World,
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which ironically makes him a specialist of generalists. He was previously a science and
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investigative reporter at ProPublica. And prior to that, a senior writer at Sports Illustrated.
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I have followed David's work for some time, have enjoyed his articles, his books,
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and reached out to him several months ago, asking to interview him, even though I had already heard
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him on a couple of other podcasts that frankly, I thought did a great job, but I just knew there was
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more I wanted to explore with him. So of course, if you've heard David on other podcasts, I wouldn't
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let that discourage you from listening to him here. We go into, in my opinion, sort of a broader,
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deeper discussion that's sort of enabled by our long format. We talk about a lot of things,
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but I think at the root of it, it's basically trying to get a better understanding of how we
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can improve our own performance. And perhaps you can see we get into a lot of stuff around kids,
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but as parents, how do we manage the exposure of our kids to various things? I think anyone
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listening to this who is a parent obviously feels pretty strongly about giving their kids the best
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chance at finding something they love and doing well at it. There are so many things we go into
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in this podcast that are just fascinating beyond belief, including a really good explanation of
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why the 10,000 hour rule that most people take for granted is essentially an axiom or dogma,
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i.e. that 10,000 hours of deliberate practice is what is required for mastery and greatness. And I think
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David goes into a great explanation of why that's probably completely nonsense, which is not to say that
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deliberate practice is not incredibly important, but to break it down to something as simple as 10,000
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hours is almost assuredly incorrect. So without further delay, please enjoy my conversation with
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Your work has been something I followed for quite a long time now. And even before your most recent book
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came out, just on the basis of the book you wrote, was it in 2013?
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Yeah. Just on the basis of that book, people had always said, oh, you got to interview him. And I was
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always like, yeah, yeah, I know, I know, I know, I know. And then the new book comes out and it's
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like, well, now there's no excuse not to. So, and I guess it's tough for you because you have this new
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book and everybody wants to talk about it, but I kind of want to talk about the old one too, if that's okay.
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Whatever you want. We can talk about something other than my books if you want, whatever you want.
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We have a lot to talk about actually, because I learned a number of things about you in getting ready to sit down
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today, but somehow it escaped me that you were a fan of IR10 Senna.
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Yeah. I mean, first of all, one of the all-time great sports documentaries if people have seen
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Senna, but I used to follow racing and just, I loved racing in general. Like if you put two
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paper boats on a pond, you know, I was interested basically. And then as I learned about him and his
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start in karting and the different types of racing he did, the fact that he was a good gymnast as a
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young guy, that he basically tried to retire from racing at one point, you know, and that he was also
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very quietly charitable. And I think, I think kind of a sensitive soul in a lot of ways, and obviously
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a very dramatic story. And I think the greatest Def 1 driver ever. And so just a lot of, I don't know
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nearly as much as you, so I'm kind of cautious about saying anything, but yeah.
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I think all of those things are really interesting and resonant. And so last week I went to the beach
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and it was with my kids and the two older kids were in the water. So just me and the toddler,
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who's two, who's actually named after Senna, his name is Arathon. And then these other two boys
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came up and started playing. And so then I'm sort of overseeing a play group, basically one of mine
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and two others. And for like 20 minutes, this is going on. And then the mother of these two other
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boys comes up and she's thanking me or whatever for playing with them. And I can sense a Brazilian
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accent. I said, oh, are you Brazilian? She says, yeah. And I said, oh, great, blah, blah, blah, blah,
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blah. And we get chatting. And I can't talk to somebody who's Brazilian for more than five minutes
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without of course asking them, do you remember when Senna died and blah, blah, blah. And I'm still
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waiting for the exception to this to happen. It's never happened yet where that person doesn't
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immediately transform into, oh my God, Senna is the greatest manifestation and representation of
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Brazil. It was the saddest day of my life when he died. And this woman would have been seven when he
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died. And our nanny, also Brazilian, same thing, was like four when Senna died, but it's seared in her
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mind. So I'm talking Uber driver, person at rest, it doesn't matter. Anytime I meet someone from Brazil,
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we talk about Senna and it is without exception, they speak of him with a reverence that I don't
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think Americans can relate to. There is no athlete we talk about. There's no politician. There's no
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scientist we can speak about in the way a Brazilian talks about Senna.
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That's amazing. So it sounds like what people here of certain generation might think of where
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they were when Kennedy or Martin Luther King were assassinated or something like that.
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It's absolutely that way because of course, everybody in Brazil was watching F1. So the world
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stopped every Sunday to watch the race. So now you take, everybody is there stopping to watch
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your guy doing this thing. And then you see this person die. But unlike maybe with say JFK,
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where yes, anybody who was old enough at that moment would remember it. I don't even think that
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they can speak about JFK the way, with as much love or reverence as they do Senna. So it's kind of
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That's interesting because obviously we have Ali as the first person who would come to mind.
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But in his day, a lot of people hated him. It's a lot of athletes like him. I think
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they become beloved once they're sort of older and non-threatening feeling. And so a lot of people
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who love them don't actually really know what it was like for them at the time. But that's
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fascinating. And I think his reputation, I think a lot of the, it turned out after Senna died that
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he had been doing like a lot of charity that people didn't even know about with no,
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no fanfare whatsoever. And so I think his legacy was, and that's amazing. That's not very,
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That's right. Very few people know about how much he did for, for the people in Brazil and how
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seriously he took his position of, he came from privilege, came from a wealthy family,
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achieved this unbelievable success. And people love this humility that he had that,
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because remember, it's not like he was the first Brazilian F1 champion. I mean,
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Fittipaldi was a two-time champion, Nelson Piquet, a three-time champion, who, by the way,
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Senec won his first championship the year after Piquet won his last. So it's like a complete overlap
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with another, but they don't even belong in the same sentence for most Brazilians. In fact,
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I asked this question of almost everybody as well, which is, how does he compare to Pelé?
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Yeah, I guess that's the most telling question you could ask in Brazil, probably, right?
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Yeah. I'll be going for my first time, actually, to Sao Paulo soon to watch an F1 race and to go,
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and I want to be able to visit the memorial where he was buried and go to the foundation and stuff
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I don't do anything in moderation, I think is what it kind of comes down to. And I've always loved
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and been attracted to people that are incredibly passionate and great at what they do. And I do think
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that his perfectionism, well, I'll take a step back and say, I was probably attracted to things
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about him that I didn't appreciate the pathology in at the time. So I do think that his desire to
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win probably also killed him. And I think that the sharpness of that edge, I probably found incredibly
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appealing in a way that almost maybe speaks to my own demons. And I think that's probably true of a
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lot of people. I don't think I'm unique in that. So I just remember, one of the things I remember
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loving about him during his career was how much he cared about the engine and what was going on
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with the car and the setup and the time he would spend with the mechanics. I mean, it was always
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telling to me that the Honda mechanics loved him. I mean, just loved him. You'd have some guys that
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would show up, they would drive and they would leave, but not Senna. Like he could spend the entire
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night in the garage, machinating over every minute detail of the car. So it was just this sort of
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incredible degree of perfectionism. Also, I do think that there was just a certain,
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there were just things that he did that to this day can't be explained. I think his qualifying
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session in 1988 at Monaco, there is no explanation for what he did that day. I'm sure you're familiar
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with it just for the listener. Monaco is a very short circuit. So in a short circuit, the difference
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between qualifying times should be tenths of seconds, hundredths of seconds. His teammate
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that year, meaning someone driving the exact same car, which they had the best car in the field,
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was Alain Prost, who was himself a three-time world champion at the time. Unbelievable driver.
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Some would argue one of the more underrated drivers ever. Senna out-qualified him by a second
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and a half. A second and a half on Monaco in a quali might as well be a day.
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All right. It's like winning the hundred meters of the Olympics by a second and a half.
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That's exactly right. It's like even Usain Bolt at his most dominant couldn't win a race by a second,
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even though there's no actual onboard footage of Senna during that quali lap because he was already
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on pole. So I don't think the networks were even paying attention to his very last quali lap, which
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why would he try to go any faster? He'd already secured pole. But when you watch Senna at Monaco over
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and over again, which is one of the most demanding circuits because of how tight it is,
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I have my kids watch these videos because I'm like, I don't think you guys understand.
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You think daddy drives a race car and that's fun because he can go fast. But I want you to see
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what the best in the world is seeing in real time because we can't do this. Humans can't do what
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he's doing. The other sort of extension to that story that speaks to this sort of love I have is
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the tormented nature of this, which is what most people don't realize is he qualifies first in
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Monaco or what most people I think have forgotten is he qualifies first from Monaco in 1988 by
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literally a second and a half as the race is going on and on and on. He has built up such a lead. He
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almost has a lap lead over the field with a very short duration to go in the race. I don't remember
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how many laps, I think like maybe six to 10 laps to go. He could basically stop, get out of his car,
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get back in it and still win the race. But he's pushing very hard. He's pushing so hard that he
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actually crashed. He is disgusted with himself. He gets out of the car, literally leaves, goes
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straight to his home in Monaco, doesn't speak with anybody for days. And to me, this is a guy for whom
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it's not about winning. Yeah. Yeah. This actually gets to something. You said I could be digressive.
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So I'm gonna make a multi, multi jump. Let's do it. Something I've been thinking about that I used to
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think about a lot and then came up recently was at a certain point when I was at Sports Illustrated
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and I was doing reporting on doping and I would get a lot of reader feedback of why are you reporting
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on this? You're sort of a killjoy, that kind of stuff. I took it seriously and started thinking
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about should I be doing this? What's the value that comes out of sport? And somehow I landed on
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this book called The Grasshopper by a Canadian philosopher named Bernard Suits. And it's called The
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Grasshopper because it's sort of a inversion of this Aesop fable where there's a grasshopper who's
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playing games all summer. And while the ant is storing up food in the summer and then come
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winter, the grasshopper doesn't have any food and the ant does. And the grasshopper goes to the ant
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and asks for some food. And the ant says, no, you were playing while you should have been collecting
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food. And so moral is kind of obvious. But in Suits, there had been this philosophical debate
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that was supposed to be settled by Wittgenstein about is there any necessary and sufficient core
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of sports and games? And he said, no. He said, no, absolutely. There's not.
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And Suits, in writing this book, The Grasshopper, the grasshopper is a character who's playing these
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games. And his disciples are come saying, you should be storing food. You're going to die.
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And he says, no, this is who I am. I understand what's coming. But this is the best thing I can
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be doing, this endeavor, for the love of what he was doing. And Suits says there is a core to all
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sports and games. And it's the voluntary acceptance of unnecessary obstacles, which I thought was kind of
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amazing. And he talks about what he calls the lucery attitude, which is the attitude you adopt
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when you get involved in these things, which I think is kind of a love of difficulty, essentially.
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And I think he sort of united something. Aristotle had these two, he put actions into two categories.
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One was kinesis, which is like, build a house. You're doing it for the end. And the other was
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energia, which is something like philosophical contemplation. You're doing it for the doing,
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not for the end. And he said, these two things have to be separate. And I think what one of the
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things Suits was saying was in sports and games, these things are united. There is an end that
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you're going for, but the love of difficulty in the middle is what's really important. And you're
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always doing something, you're intentionally doing something inefficient, right? Like you could walk a
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ball and put it into a goal. That would be the most efficient way to do it. Or you could cut across
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the track and get there faster, but you're intentionally engineering an inefficiency in order to
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facilitate a certain experience. I'm sure Senna had that love of difficulty. And one of the things,
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not to tie it to my own stuff, but one of the reasons I think about it is, to me, I don't know
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that readers would say this, but to me, one of the major themes of my new book is that sometimes the
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things you can do to cause the most rapid apparent short-term progress can undermine long-term
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development. And that actually you don't always want to be as efficient as possible. And I think
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that's very much embodied in this love of difficulty in sports and games, where you are
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intentionally engineering in inefficiency in order to facilitate an experience that you hope has some
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value and some learning. So sorry, that was my multi-jump. No, that is so true. I think that
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actually in one sort of story captures the essence of the greatness we see in sports, which is, as you
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said, it has to have a struggle in it. It's not interesting if there's no struggle, but it's in
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service of some destination that can be quite arbitrary, by the way. I mean, race car driving happens to be
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one of the less arbitrary ones. Going fast seems somewhat understandable and innate. Mountaineering
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seems somewhat understandable and innate. Get to the top. But many sports, like basketball and
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football, are kind of arbitrary in what we're asking people to do. Think of baseball. It's like
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bananas. It's like if you were just watching it with no sense of the conceptual structure,
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it would look ridiculous. Like, why doesn't the guy just stay at home plate? They're already there.
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Yeah, that's so funny. Well, before we get to your new book, because there are so many questions I
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have on that theme, both personally and then with respect to my profession, and then even more
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broadly, I do want to go back to the gene. Because I remember when the book came out, I think it came
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out on the heels of an article you had written in Sports Illustrated, correct?
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Wow, I'm surprised you remember that. Yeah, the sports gene. Yeah, it did. Yeah. I want to confess
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something really quick. This that nobody really calls me on is I wrote that article in Sports
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Illustrated. It passed fact checking at Sports Illustrated because when the fact checkers called
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back the scientists, they said, oh, this is true, this is true. But then after a year of, before my
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books the first year, I try to just read 10 journal articles a day every day for the first year, no
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writing. And having done that for the year researching the sports gene, I realized that while I had quoted
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these scientists appropriately, some of them had told me things that could not be concluded from their
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data. And so I cited my own article as one that was mistaken, but nobody really called me on that.
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But that's, I think if you're writing about science, something you're writing about is going to be
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wrong. So you have to kind of be ready for that. Well, it's so funny you bring this up. So Bob Kaplan,
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who's my head of research, we are in the process now of going through the fact checking for this book
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that I've been painfully and slowly working on for more time than I care to admit. And what we realized
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is he can't be the fact checker, nor can I, because it's not just facts we're checking,
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it's interpretation. And we are already so biased by our view on this. So we actually have another
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one of our analysts doing the fact checking, but we specifically refer to it as fact plus
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interpretation, fact plus interpretation, which turns out to be really a long process and a very
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challenging process because you do, I mean, I've done this a handful of times where you pull up one
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of the citation classics in medicine or science that people have referenced so many times. It's been
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triply referenced internally to the point where I don't think the people referencing it anymore,
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even know what the paper says, let alone what it's citing. Telephone game of citations. It's
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unbelievable. And the few times I've had our team extract from those papers, I've been mortified at
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how wrong they are, which again, they're not necessarily orthogonally wrong, but they've missed
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so many things. Like it's like, oh, well, of course this so-and-so does such and such and such and
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such. Well, let's go back and look, wait a minute. You realize that was in one really,
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really, really bad experiment in mice in which you could never make that inference into another mammal.
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And now yet it's taken as sort of a fact. I have to say not that that's good, but I have noticed
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that that sort of thing provides opportunities for people like me where I'll go and read the
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original research of things that have just been at the core of other bestselling books. It's kind of a
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great, if you're willing to do it, it's sort of a competitive advantage. You know, it gives an
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opportunity, not that I want people to be citing things wrongly, but I think you're totally right.
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I started as a fact checker at Sports Illustrated and that's where you realize how many ways there
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are to go wrong. Are you looking for any more work right now? No, no, no. I was happy to get out of
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my fact checking days. I'm in my post book, never again phase, which I was in before, but that's where
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I am right now. No, but yeah, I hired independent fact checkers also. And that doesn't mean there
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aren't things that are wrong or interpretations that are wrong, but it certainly, certainly cuts it down
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compared to, I think most books probably have no fact checking at all. Yeah. I'm super paranoid
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about it because I also realized that we can't catch them all. That's the difference between a
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blog post and a book is, you know, I've written more blog posts than I'll ever be able to count.
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And the good news is the week it comes out, someone smarter than you is going to catch something that
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you did wrong. And you're like, oh my God, yeah, totally right. Thank you for that. Boom. I can change
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it. I can't do that with a book. And that is crippling me. Yeah. I mean, you can do small stuff for
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second printings and things like that, but it's not as easy, right? It doesn't happen right away.
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And if it, well, especially if it's the interpretation, it's one thing, if you get a
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fact wrong, when you start to interpret something incorrectly and you come around, it's very difficult
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to unwind that. Definitely. And if you're going to change, yeah, as I learned this time, the,
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both of my books, there are 352 pages, I guess, if you count the front and back and because they
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get printed in sets of 16. So everything has to fit to a multiple of 16, including the index and
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the citations and everything. So if you have to change something major, like an interpretation,
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where it's not one sentence, if you're going to mess up the page flow, it's not so doable.
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You're making some unhappy folks. You alluded to something there, which is
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the opportunity to go back and look at something that people have sort of taken as dogma and
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questioning it. And in many ways, that's a big part of what the gene does and what your current book
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does. I'll share with you sort of my bias coming into this discussion, not this discussion with
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us per se, but, but sort of this theme, which is, so Daniel Coyle wrote a book in 2009 called
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The Talent Code. And before that, there were a number of other books and pieces of literature
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on that subject matter. And I was obsessed with this. I was obsessed with this idea of how can one
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be great? Obsessed with this even as a child. And certainly when I was doing my surgical training,
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I really remember spending lots of time reading literature on technically achieving mastery.
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Like what does it mean to be a great musician or a great surgeon or a great athlete? Things where
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there's some sort of dexterity and skill required that goes beyond just thinking and cognitive prowess.
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And so I would say I completely bought this idea that deliberate practice is the only thing that
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matters. And I think a lot of people sort of have taken that to be the case. What made you question
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that in the first place? Or did you not question that and instead stumbled organically into questioning
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I did not question it in the first place. And I should say Dan's a friend and I'm a big fan of
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his writing also. And yeah, I did not question it. In fact, if you saw my book proposal for The
00:20:40.720
Sports Gene, The Talent Code, in the book proposal, sometimes you do a section that, I don't know if you had to do
00:20:45.960
this or not, but other books that yours will be like. Other books like, yes, yes, yes.
00:20:49.320
I skipped that part for my second proposal. But in the first one, I had to do it. And Talent Code
00:20:53.080
was one of the ones that I said it was going to be like. And obviously, I would say for the casual
00:20:57.440
reader, it looks like they're actually diametrically opposed in many ways. And I don't see them as
00:21:02.140
diametrically opposed, but there are certainly some differences. And it was probably when I went back
00:21:08.460
and started looking at some of the original literature. The 10,000 hours rule was, who was I to question
00:21:13.340
that? I mean, the one good thing is I was in my past training to be a scientist. And I was like
00:21:17.380
living in a tent in the Arctic when I decided for sure to become a writer. So I knew I should leverage
00:21:21.200
that background of, I was in the geological sciences, which are pretty methodologically
00:21:25.060
rigorous, I would say, as the sciences go. And so I decided to go look at these original papers if I'm
00:21:29.760
going to study them. And I come across the first, the so-called 10,000 hour study that the scientists
00:21:34.860
who wrote it wouldn't call it that. But this was with violinists? Violinists, yeah. 30 violinists,
00:21:39.140
Famous Music Academy in Berlin, split into three groups. The top 10 who were deemed to potentially
00:21:44.480
be international soloists practiced in deliberate practice, highly focused error correction focused
00:21:49.700
practice, on average 10,000 hours by the age of 20. The first thing I noticed was that there were
00:21:57.000
no measures of variance reported in the study, which is not something when I was a grad student
00:22:02.260
that one could have gotten away with, reporting no measures of variance. So I was-
00:22:05.580
Explain that some folks might not even know what that means. So like, there's an example.
00:22:08.780
So if you look at a table and it says, this person practiced this many hours, this many
00:22:12.980
hours, this many hours, what was missing in that description?
00:22:15.220
First of all, no range. So several of the books and the paper wrote that there was complete
00:22:19.720
correspondence between the number of hours of practice and what group someone fell into.
00:22:24.140
And I said, well, I can't tell that from this data. Like, maybe someone in the lowest group
00:22:28.260
actually practiced more than someone in the highest group, but you haven't included the range
00:22:32.400
of practice hours or the standard deviations of practice hours. What is the individual variation?
00:22:36.880
Any time you take an average, it could be that nobody practiced 10,000 hours. It could be that
00:22:41.820
somebody practiced 100,000 hours and a bunch of people were much less.
00:22:45.660
So sort of like, what's my average, your average, and Bill Gates' average wealth?
00:22:53.380
That's right. I mean, so for example, in the chess literature, it takes 11,053 hours on average
00:22:57.920
to reach international master status. So 10,000 hours would be low. That's one level down from
00:23:02.120
grandmaster. But some people have made it in 3,000 hours. And some people finished a study
00:23:06.260
at 25,000. They still hadn't made it. So we don't really know where their endpoint is.
00:23:10.500
So you can tell someone, well, it takes 11,053 hours on average to reach international master
00:23:14.980
status, but it doesn't tell you anything about the breadth of actual skill acquisition.
00:23:19.400
So how is that possible, by the way? I mean, I can't imagine looking at a paper that wouldn't
00:23:22.820
at a minimum include a standard deviation for that type of calculation.
00:23:26.220
Don't know. Okay. So eventually I organized, I noticed that the most famous researcher on
00:23:31.560
that paper, who I think has done some very interesting work, and especially in the area
00:23:34.440
of memory, some work that I myself have tried to incorporate into things I do. But I noticed
00:23:38.620
that he was, in a lot of his work, saying there's no such thing as talent, it doesn't matter,
00:23:43.140
just pick any random thing and you'll be great at it.
00:23:46.260
Right, right, exactly. That it doesn't matter what you match with. And I noticed he was citing
00:23:50.560
a lot of physiology papers that I knew something about, like sports physiology papers,
00:23:54.300
and not, like you said, not in the way, the interpretation, it was kind of like these
00:24:00.200
secondary interpretations, telephone game stuff. And so I organized a panel at the American
00:24:04.520
College of Sports Medicine and invited him. And this was, I thought, a problem. He was
00:24:08.900
citing a lot of their papers. His work, Anders Ericsson, was super influential in expertise.
00:24:14.800
I think that 10,000 Hours paper is clearly the most influential paper ever in the development
00:24:18.420
of expertise. But they weren't talking to each other. So I organized this panel. And in that,
00:24:22.500
a researcher stood up named Tim Lightfoot and asked, what's the variance around that 10,000
00:24:27.180
hours? And he said, well, that doesn't really matter because the people were actually inconsistent
00:24:31.480
on multiple retrospective recalls. Because what they did is they just asked for retrospective
00:24:35.400
recall and then had the performers keep a diary for a week and then extrapolated it, basically.
00:24:40.060
Which, by the way, don't even get me started on the noise that's introduced by both of those
00:24:45.140
Right. There was just a replication attempt, by the way, last month it published and failed. But we can
00:24:49.260
talk about that if you want. But in that, there was actually, in the new replication attempt,
00:24:52.780
there was someone at 4,000 Hours who got to the highest group and someone at 11,000 Hours who was
00:24:57.060
still in the lowest group. But anyway, so he asked, what's the variance around that 10,000 Hours?
00:25:02.020
And Ericsson says, he said, first of all, there was inconsistent recall. And so Tim says, yeah,
00:25:08.260
a lot of us struggle with imperfect data, but we still put measures of variance. And so Anders says,
00:25:13.660
well, that'll be like more valid when we have video diaries and we can really track it because
00:25:19.000
we're not being that precise anyway. And he says, again, we all struggle with imperfect data,
00:25:24.000
but we include measures of variance. Was it? And then he asked, so what was it? And he says,
00:25:27.480
I don't know. I'd have to go look back. And so Lightfoot says, definitely more than 500. And
00:25:32.520
that's where we leave it. And then I think two years ago, something, a couple of years ago,
00:25:36.980
Ericsson did publish measures of variance. And it turns out there was enormous variance.
00:25:39.800
Not only was there enormous variance in the original paper, the papers from 1993,
00:25:44.660
and it was three or four years ago that he finally published the variance,
00:25:47.920
made clear that their conclusions were wrong, that there was not complete correspondence between the
00:25:52.780
number of practice hours and the group that someone was in. Well, I think that's sort of where I'm
00:25:56.220
going with this question, which is you can't even make an observation of statistical significance
00:26:02.320
without variance. So I don't really understand what the paper is saying. This is the first thing
00:26:06.980
where I was reading it and saying, something's not right here. And so then I started asking these
00:26:11.020
very basic questions. Because I'd been an athlete, I'd gone from being like the worst walk-on on my
00:26:15.240
college team to being like a university record holder. So I'm like, yeah, maybe if I had trained
00:26:19.560
even more, I would have been even better. And that probably is true. But I was, I was like, oh, okay,
00:26:24.480
so there is no such thing as talent. I was convinced for a while. And then when I started seeing this,
00:26:28.500
I started asking the very basic questions like, okay, in my third year of training,
00:26:33.540
I could break the women's world record. So there has to be at least some basic genetic
0.99
00:26:38.720
difference because I haven't worked harder than the women who are pros by any stretch of the
0.99
00:26:42.440
imagination. And so I said, okay, let's start with that basic question. I'd contact sort of some of
00:26:46.440
the, I shouldn't call them the 10,000 hours researchers because they kind of disavowed that,
00:26:49.960
but the deliberate practice framework. And I remember contacting one and saying, wouldn't you agree
00:26:56.180
that a man and a woman who practice the same, like the man has advantages, which is why we separate
0.99
00:27:01.380
sexes in sports. And she sort of hedged and said, maybe not if they all train the same. I said,
00:27:08.280
really? And so she sent me a paper saying, in fact, we think this applies to other organisms.
00:27:12.860
If you look at this paper about racing dogs, you'll see that they practice the best ones in
00:27:18.060
the highest class practice about the equivalent to their lifespan of 10,000 hours. And so I'm reading
00:27:23.860
this and I started reading all the citations. And one of them notes that like half of these dogs
00:27:28.000
have what is otherwise an incredibly rare myostatin mutation.
00:27:31.820
Let me pause for a moment and explain to the listener what myostatin mutations are. So if you
00:27:35.200
knock out the myostatin gene, you look like a bodybuilder. Myostatin is a gene that inhibits
00:27:39.980
muscle growth. And there are lots of myostatin mutants out there that all have hypo-functioning
00:27:46.960
Yeah. And so racing breeders had been, they didn't know about the gene, but they were breeding for fast.
00:27:53.860
Yeah. Yeah. And what they wanted was a single myostatin. If you get two, then you have a bully whip it and
00:27:57.720
Google that. It's pretty cool to see. Bully whip it.
00:27:59.660
That thing probably can't even move. It's so big.
00:28:06.220
So I wasn't going to like use this study or anything, but I just started saying,
00:28:09.160
these people aren't reading the primary stuff that they're citing or they're not tracking the
00:28:12.760
references back. And so I started to have doubts.
00:28:14.720
Is this a broader problem with non-experimental science?
00:28:20.000
Because we do the same dumb thing in medicine, by the way. People sort of think of medicine,
00:28:23.280
which we're going to get to in spades as it's so rigorous. And yeah,
00:28:27.320
sometimes medicine does get to leverage the scientific method and actually get to do what
00:28:31.940
Francis Bacon talked about. But a lot of times you don't. I mean, when you think of some of the
00:28:36.420
most important public health measures that are out there, oftentimes they are based on exactly the
00:28:42.780
type of inference you're being appropriately critical of, which is observational, heavily selected,
00:28:49.840
range restricted, which I can't wait. You talk about this so eloquently that I cannot wait
00:28:54.600
to have you go off on your tangent soapbox, whatever, rant on that problem. But these are
00:29:01.780
Yeah. Yeah. I mean, that was the other thing. I don't know if I should skip to range restriction.
00:29:05.880
Well, let's start with medicine. So I wrote this one article when I was at ProPublica called
00:29:08.980
When Evidence Says No and Doctors Say Yes. And I should say, I love the medical profession. I think
00:29:13.780
it's filled with a variety of people like any profession, but a lot of people who really care and got into the
00:29:19.660
profession because they want to do something that is challenging and useful. But also there's like a
00:29:24.340
lot of poor science and there are a lot of things that continue to be done even once evidence shows
00:29:27.940
they don't work anymore. What Mike Joyner at the Mayo Clinic always calls bioplausible, something that
00:29:32.760
clearly makes sense. It definitely should work. It's just that when somebody does like a randomized
00:29:36.460
controlled trial, it doesn't. You probably saw the finished study of partial arthroscopic meniscus
00:29:42.920
repair. I think there's a lot of devils in the details. That said, it was interesting. They gave some
00:29:47.360
people sham surgery where they basically made an incision, banged around like they performed
00:29:51.060
surgery and sent them to physical therapy. And they did as well as the people who were getting
00:29:54.660
the surgery, which is mind boggling because everyone's doing something that seems like it
00:29:58.200
has to work. Someone's got knee pain. You bring them in, you give them imaging. They've got a tear,
00:30:03.180
fix it. How could that not work? But then I guess it turns out that some huge number of
00:30:06.640
people have incidental tear that doesn't have anything to do with the knee pain.
00:30:11.060
The meniscal tear is a huge thorn in the side of the orthopedic specialty because frankly,
00:30:16.600
I don't know the answer. I mean, my intuition is that that's a procedure that is probably done
00:30:20.320
far too much, but it's also probably a procedure that if you knew how to select the right patients,
00:30:24.560
you could probably make a difference. But because we don't, we end up applying the tool
00:30:29.060
far too broadly and we dilute the outcome. I'll give you a much more specific example that is so nerdy,
00:30:34.560
but there's a drug called ezetimibe or Zetia, which blocks cholesterol reabsorption. So the body
00:30:39.620
makes a ton of cholesterol. Virtually all the cholesterol in the body is made by the body and it gets
00:30:43.720
recirculated throughout the body. Well, part of this recirculation pathway requires that cholesterol
00:30:47.840
be dumped into along with bile into the gut. And then in your gut, you can reabsorb it. And the
00:30:53.920
body has a way to regulate how much of that's happening. But it turns out there's a drug that
00:30:58.380
blocks this thing called the Neiman Pixie one, like one transporter that drags cholesterol back in.
00:31:03.620
Now, when that drug is given in monotherapy, it lowers cholesterol, but not that much. And it
00:31:10.240
doesn't save lives. So it's not a drug that's really, in fact, it's absolutely therefore not
00:31:16.340
considered a first-line agent and it's never considered something that should be used in
00:31:19.620
isolation. Now, when you give it with a statin, it turns out it lowers cholesterol and it reduces
00:31:23.800
events. So the things that you care about, the actual hard outcomes change.
00:31:29.820
Correct. That's right. Because you can compare it to statin versus statin alone. So I have probably
00:31:36.020
kind of a contrarian view on this, which is I actually think this drug alone would work if you
00:31:41.420
actually only gave it to people who were hyper absorbers. But that's never been done. Because we can
00:31:46.300
measure how much absorption capacity a person has, but that's a kind of advanced measurement. You
00:31:51.580
wouldn't normally do that in a clinical setting. But if you select for patients who have mega
00:31:57.120
amounts of absorption, it's certainly possible that those patients... So I don't know the answer
00:32:02.180
to this. And only if a trial was done testing that way could you get it. But I do think that
00:32:06.980
this problem exists in medicine, which is you dilute by taking such a heterogeneous population
00:32:12.700
to test an intervention on. And you're therefore not really powered to detect an effect because
00:32:19.700
in your power calculation, you're using the entire population as your denominator. And really,
00:32:25.160
it probably needs to be a subset. And so my intuition is that's probably the case with some of these
00:32:29.440
procedures like meniscal repairs, which still offers no help to you or I right now if we're having knee
00:32:36.380
pain with an MRI that shows a meniscal tear. I actually don't know the answer in that setting.
00:32:41.000
That's interesting on so many levels. The first is what you're talking about with absorption
00:32:44.760
is this sort of lesson that there's huge individual variation in that stuff.
00:32:49.240
Staggering variation, by the way. I measure absorption synthesis in every single patient,
00:32:53.640
non-negotiable, no questions asked. And I am constantly amazed at how much variation exists.
00:32:59.440
Basically, three variables are determining this, right? It's sort of how much do you make,
00:33:03.140
how much do you absorb, and how much do you clear out of circulation with the LDL receptor?
00:33:07.440
And the variation is, it's overwhelming. And yet it's amazing to me that our profession looks at
00:33:13.360
just one metric, which is how much LDL cholesterol is there. And that's going to be the basis for
00:33:17.260
treatment. It strikes me as flying without instruments and deciding you only get to look at the horizon.
00:33:23.060
That's interesting. That gets at two things I want to remember. First, this idea of the
00:33:26.320
McNamara fallacy, you've heard of named after the Secretary of Defense during Vietnam, which is,
00:33:30.400
he said, are we winning the war or are we losing? Let's use something measurable,
00:33:33.320
our bodies versus their bodies. And since we're always winning, by that metric said,
00:33:37.560
okay, we're winning, obviously ignoring a lot of other important things.
00:33:41.880
Yeah. So it's like, we often deem things important because they're easily measuring them
00:33:45.460
because they're important. But that individual variation gets to another thing that got me
00:33:48.660
interested that sort of caused the sports team to be very different from my proposal, which was
00:33:52.900
underlying the 10,000 hours rule, which is actually called the deliberate practice framework.
00:33:58.340
Because again, Erickson would not call it the 10,000 hours rule. There's something called the
00:34:02.560
monotonic benefits assumption. And essentially, if you have two people who've never done something,
00:34:07.480
for every equal unit of practice, they should progress exactly the same amount.
00:34:11.760
So it's that everyone's practice response is the same, is one of the assumptions underlying it.
00:34:18.760
To say it's not would be an interesting conclusion or observation. But how could that even be the
00:34:24.740
I don't know. Does it? It might be if people started from zero. I'm not sure what I would
00:34:27.400
think if they would progress exactly the same or not. But then people have done those studies,
00:34:30.580
you know- Meaning if we took a hundred people who have never spoken Spanish and we gave them
00:34:34.840
Spanish lessons, give me the evidence that if that were the case, wouldn't we see much more
00:34:42.960
I would think. I mean, Erickson would make the argument that, well, some of those kids
00:34:48.100
are engaged and some of them aren't, or maybe some of them had more practice before. So I think
00:34:51.740
to really evaluate this, you have to get some skill that nobody else has tried before, that
00:34:55.560
these people haven't done at all. Because who knows what they bring to school, all sorts of
00:34:58.440
other stuff. But there are studies like that where people who are sedentary do the exact same
00:35:02.120
exercise. One of the famous ones called the Heritage Family Study, where every member of two
00:35:05.740
generations of 98 families is totally sedentary, put on six months of identical cycling
00:35:10.780
training. And the range of variation was like a thousand percent, doing identical training.
00:35:17.420
Identical training. And you can see things like the military does this and people learning
00:35:20.740
sort of perceptual motor skills for air traffic controller simulations. And at very simple
00:35:25.540
simulations, actually, it's kind of like that. Like they converge if it's very simple. You just
00:35:30.340
have to see that one plane's coming, move one off the runway, and then it becomes about
00:35:33.860
how fast can you basically just move the mouse when you're doing a simulation. But as it gets
00:35:37.860
more complex, people start diverging with more practice. And so that monotonic benefits
00:35:43.000
assumption, I could find no evidence of it. It's like never shown up in a study of anything
00:35:47.760
unless it's an extremely simple task that everyone masters very, very quickly. And so again, I
00:35:51.960
was sort of saying that average is just obscuring individual variation.
00:35:56.540
So I keep preventing you from talking about this because I can't stop asking all these other
00:35:59.860
questions. But when you look at the title of the sports gene, the assumption would be, oh,
00:36:04.660
this is a book that explores the notion that a great athlete is genetically gifted. Michael
00:36:09.480
Jordan is Michael Jordan because he clearly has a set of genes that separate him from the
00:36:13.720
rest of us. And that's probably a bad example because it's so extreme. But talk to me about
00:36:18.260
some of the things that you found in that book that surprised you. And there were certain elements
00:36:22.780
of that book that didn't get that much attention, by the way, that I, in retrospect, thought I'm
00:36:27.060
surprised more people didn't fixate on that thing. Like, I don't know. Did it surprise you
00:36:30.340
what people drew out of that book as the most important insights?
00:36:33.760
Yeah. Yeah. I didn't think the thing that people were going to find the most controversial was the
00:36:36.960
10,000 hour rule, to be quite honest. I guess I didn't realize how...
00:36:42.400
Yeah. And that people were actually planning certain training plans, soccer teams, to 10,000
00:36:47.640
hours on the dot. And the thing that was the most important to me, I tried to write a book about
00:36:51.840
one of my closest friends and former training partner dropped dead at the end of a mile race. He was
00:36:57.300
like one of the top ranked guys in his age group in the country. Young Jamaican guy was going to be
0.65
00:37:01.280
the first in his family to go to college, all these things. And that kind of threw me for a loop. And
00:37:04.300
anyway, I got his family to sign a waiver allowing me to gather up his medical records. And it turned
00:37:08.800
out he had hypertrophic cardiomyopathy, textbook case, misdiagnosed because not easy to diagnose.
00:37:13.580
If he'd had a good family history, it turned out he probably clearly had a relative who... It's like
00:37:18.160
I started going to meetings for families that think they have HCM in their family. And they'd say,
00:37:22.740
well, we're not really sure, but cousin Jimmy died in the pool and he was a varsity swimmer.
00:37:26.800
And like Uncle Fred was in a one car accident. You're like, all right, these might be cardiac
00:37:31.040
arrest. And I wanted to write a book. One of the main reasons I got off the science track is I
00:37:35.320
wanted to write about sudden cardiac death in athletes. And that's what I tried to pitch a
00:37:39.080
first book on, but I didn't have the professional capital at the time and couldn't sell it. But
00:37:42.800
there's a section of that that I smuggled into one of the chapters in the sports gene, which is the
00:37:46.320
most personally important thing to me that I don't think I got asked about one time ever. So
00:37:50.500
I don't know if that's surprising or not. It just is. The most surprising findings of the book to me
00:37:55.340
were things like, I still don't know how to summarize the book, but that things that I
00:38:00.340
assumed were genetic, like the reflexes it takes to hit a hundred mile per hour fastball turn out
00:38:04.740
not to be the fact that major league baseball players don't have faster reflexes. That was
00:38:08.360
a surprise to me. I had assumed they do. The same is true by the way, for formula one drivers.
00:38:12.200
Is it? Yeah. So it turns out that. Oh, that makes sense. Perceptual motor skill,
00:38:16.020
right? They're probably using cues, like the changing size of something in there.
00:38:19.340
Well, one of my favorite exercises that you can see when you compare. So if you put a novice next
00:38:25.260
to Lewis Hamilton in a simulator, even adjusting for the speed at which things are moving, you won't
00:38:31.140
be blown away at where Lewis's eyes are at every moment that he is driving, how far ahead he is
00:38:38.680
able to see what's happening. So a few weeks ago, I was on the track and in an effort to really force
00:38:44.640
this type of learning. We have one camera that is actually looking directly at me, one camera that
00:38:50.180
is looking directly at the road and capturing all of the telemetry. And then I sit with my coach and
00:38:54.540
we review these two side by side because what I'm working very hard to overcome is the desire to
00:39:03.280
narrow my field to where I'm driving. And when you're going fast, that's innate. You don't want to
00:39:08.160
be looking somewhere way down the road. You're worried about falling off the road right now, but you can't
00:39:13.440
do that. So that's the thing that they've been able to train to do. It's not that they're going
00:39:18.040
faster. Sorry, that's what they have faster reflexes, which again, remember when I first was
00:39:22.700
shown these data, I was like, wow, looking at Senna, you'd think he has the fastest reflexes on the
00:39:27.620
planet. Right, right. Once you start reading about perceptual motor skills, it makes perfect sense
00:39:31.760
because any activity that's happening too fast, I mean, the things they have to do are too fast for
00:39:35.740
any human, even if they did have, were the top 0.001% of human reflexes, it wouldn't be fast enough.
00:39:41.380
So in boxing, there was this study I came across doing this sports gene where these
00:39:45.380
someone, I don't even know if they were doctors or scientists, did some test of Muhammad Ali.
00:39:50.380
I think that what they were trying to show was that even this brilliant black man has slower than
1.00
00:39:56.260
normal processing speed in his brain or something. And so they reported his, they would have him like
00:40:01.340
throwing a punch in response to a light or something like that. And they were saying like,
00:40:04.240
look, it's lower than average. And then, then someone said that they were testing it wrong. If you
00:40:08.020
subtract the delay for whatever cue they were giving, he actually, from first perceptible
00:40:12.340
motion to full extension, it was like 150 milliseconds, which is extremely fast. But
00:40:17.360
that means when he's throwing a punch also, I think other people throw punches that fast. I
00:40:21.080
don't think it was like an alone outlier for that, that it's faster than the minimum human reaction
00:40:25.460
time, which is a fifth of a second, just to see that something's in front of you and for that
00:40:29.840
message to get to your muscles, not to dodge. And so you literally have to be seeing things
00:40:35.680
before they happen or else you'd get hit by every punch. Of course, his genius at disguising what
00:40:40.040
he was doing was an attempt to confound people's ability to see the future. And so anything I think
00:40:44.460
that's happening at that speed, those aren't skills that anyone comes with. There might be
00:40:48.260
things that facilitate you downloading that software, but it doesn't, doesn't come with the
00:40:52.480
machine. You talk about kind versus wicked. I'm jumping between these books. I think we're just
00:40:57.440
going to end up doing that by the way. I really wanted to talk about the gene, but now I can't
00:41:00.560
stop, but help moving. So maybe use that example in boxing as an example. Is boxing a kind sport or
00:41:08.060
is it a wicked sport? And explain what those two distinctions mean.
00:41:11.080
Yeah. Kind and wicked are, so those are terms coined by the psychologist, Robin Hogarth in a kind
00:41:16.960
learning environment. He was trying to reconcile this issue in psychology and the study of expertise
00:41:22.980
about why some people who studied experts saw them get better and better and better with very narrow
00:41:27.580
experience. And some people saw them not get better, sometimes get worse or get more confident
00:41:31.820
and not get better. Like what was the difference? And it turns out that the difference often has a
00:41:35.860
lot to do with one, the way they're training, but also the environment that they are training in.
00:41:39.800
And a kind learning environment is one where all your information is clear. The next steps and goals
00:41:44.560
are totally clear. Work tomorrow will look like work yesterday. Patterns recur. And whenever you do
00:41:50.020
something, you get feedback that is immediate and fully accurate. On the other end of the spectrum.
00:41:55.120
So golf golf is a really kind learning environment because the ball is never actually moving towards
00:42:02.660
you. You're always starting with a static ball and there are almost a finite number of things that
00:42:07.600
you can see in that position and there's no rush. And you get automatic and real time feedback every
00:42:13.580
time something happens. So I think some of the people who study golf characterize it as like almost
00:42:17.420
an industrial task in the sense that part of what you're doing is trying to do a similar things over
00:42:21.740
and over with as little deviation as possible. Archery, which is my obsession, a very kind
00:42:26.280
learning environment. Absolutely. Totally kind. Absolutely. And a wicked learning environment on the
00:42:31.560
other hand is you might not know exactly what you're supposed to do next. You might not even know the
00:42:35.160
goal. Human behavior might be involved. There may be time pressure and work next year might not look
00:42:41.100
like work last year. And importantly, you don't always get automatic feedback. And sometimes when you get
00:42:45.840
feedback, it's delayed and sometimes it's inaccurate. One of the, there's actually a medical example that
00:42:51.320
I know the story you're going to tell. Yeah. Which is this doctor, this New York doctor who got wealthy
00:42:56.220
and famous because he could miraculously by palpating patients' tongues or feeling around their tongue with
00:43:01.340
his hands before they showed any symptoms, he could predict they would get typhoid. And he was right over
00:43:06.060
and over and over again. And one of his colleagues later observed using only his hands, he was a more
00:43:10.040
productive carrier of typhoid than even typhoid Mary. So he was giving people typhoid by touching their
00:43:14.600
tongues and getting the feedback that he was an amazing predictor and so would do it over. So he
00:43:19.780
was, the feedback was reinforcing the wrong lesson. So I wouldn't say most of us are in that wicked of
00:43:24.460
a situation either. But what Hogarth was doing was setting up this spectrum of learning. What do you
00:43:30.340
think is a bigger wickedness within the wicked environment? Because there are really at least two
00:43:35.460
variables that I think make that type of learning environment challenging. The first is the number of
00:43:43.060
scenarios you can face and the unpredictability of them. So in archery, the goal of archery actually
00:43:48.100
is to make every single shot identical, non-negotiable. So everything from the way you
00:43:53.840
stand to the way your shoulder sits to the way the release sits, we pay tremendous attention to
00:44:00.000
the feeling of the string on the nose and the feeling of the string on the corner of the mouth. I mean,
00:44:04.880
you're trying to reproduce the same thing ever and ever and ever. So part of it is, well, in tennis,
00:44:08.640
for example, there are an infinite number of ways that you could be standing and your opponent could
00:44:13.060
be standing and the ball could be coming with this spin versus that spin, or maybe not infinite,
00:44:17.220
but there are so many more variables. The second piece is this delay between feedback and reality,
00:44:23.120
which anybody who's ever tried to talk when they can't hear themselves or when there's a delay
00:44:27.680
realizes how much feedback matters. Which of those two do you think is more important in creating that
00:44:34.860
environment? I think delayed feedback is usually a killer. I think that the changing scenarios
00:44:40.820
is easier to accommodate with broader training in some ways. So this classic psychology finding
00:44:46.600
that can be summarized as breadth of training predicts breadth of transfer. Transfer is, and by
00:44:51.920
the way, I'd say tennis is definitely more on the wicked end than golf, but I would still-
00:44:56.560
As Hogarth said, most of us in the knowledge economy are playing Martian tennis. You see some people playing,
00:45:00.940
nobody's told you the rules, you have to deduce them. And by the way, they can change without notice.
00:45:05.240
And so breadth of training predicts breadth of transfer. Transfer is the term psychologists
00:45:08.780
use to mean your ability to take skills and knowledge and apply them to a situation you
00:45:13.100
haven't quite seen before. It might be similar, but something's a little different. And what
00:45:17.260
predicts your ability to do that is how broad your training was. If your training is broad,
00:45:20.700
it forces you, instead of expecting the same thing over and over, to build these sort of flexible
00:45:24.680
conceptual frameworks that you can bend when you see a new problem instead of just doing the same
00:45:29.320
thing over and over. So I think you can mitigate that with the right kind of training. The delayed feedback,
00:45:34.160
that really screws people up. In studies where people have to sort of drive remote-controlled
00:45:39.100
things, if they build in a delay between what they do and the movement, it completely screws them up.
00:45:43.660
All the way to, there's some interesting studies of software project managers. There's this famous
00:45:48.100
essay. I had to cut like 20 or 30,000 words from the book. This was something I had in there called
00:45:52.580
The Mythical Man Month. And it's an essay by this guy, Fred Brooks, who was like head of research at
00:45:58.460
Microsoft. And he went on to found the computer science department at the University of North
00:46:01.880
Carolina. And what he meant by The Mythical Man Month was he had noticed that when project managers,
00:46:08.220
when their projects got behind in software, if they were complicated, they would start adding more
00:46:13.260
person power, adding more man or woman power to the team. And that would cause the project to become
0.83
00:46:19.940
more late. And so Brooks's law is if you add people to an already late software project,
00:46:25.420
it will become more late in proportion to like how many people you add. And that's because there
00:46:29.140
was a delay between those people adding to the team. They needed to be assimilated. And the managers
00:46:33.820
never learned that lesson because of the delay. And so they keep doing the same thing over and over
00:46:37.900
and over. And a couple of researchers sort of followed up on that more recently and called this
00:46:41.600
the experience trap where these project managers, they come up with simpler projects where adding people
00:46:46.780
does help it get done faster because they can right away figure out what to do. And then they get promoted
00:46:52.300
and promoted and end up with more complicated projects. And in those cases, they do the same
00:46:56.500
thing and bring people on and they never learn about the assimilation delay that it takes. So
00:47:00.720
these researchers were saying we need to start telling them this is the time between you bringing
00:47:05.060
someone on and them making a positive impact. But they never learned that lesson because of the
00:47:08.940
feedback delay. So I think that's from the motor skills up to these much more sort of management
00:47:14.780
kind of softer skills, the feedback delay is really difficult.
00:47:17.660
That concept, ever since I read about it in your writing, I sort of look at the world a
00:47:22.420
bit differently now. I actually think of that question specifically. I'm like, how kind is
00:47:27.260
Me too. That's what happened. When I was reading this, I was like, oh, this is going to be the
00:47:30.120
frame that I'm going to think through, I bet, for everything in this book.
00:47:32.920
Well, I think about it a lot with kids. You have a kid, right? You've got one?
00:47:37.420
Yeah. So, I mean, think about the learning that's taking place. Think about the neuroplasticity of a
00:47:43.060
seven-month-old. And for example, it's why, sort of going back to the example before,
00:47:47.980
if a child is deaf, it's going to delay speaking, not because they can't speak,
00:47:51.960
but because they can't get that real-time assimilation and feedback. And watching,
00:47:57.740
it almost makes you think about how much do you want to intervene when they're doing something
00:48:01.980
wrong too. I don't know if you've found that, but it's like, okay, as long as they can't really
00:48:06.140
hurt themselves, I should probably let them do that thing that is going to hurt, but hopefully not
00:48:11.380
irreversibly hurt. Yeah. Yeah. I mean, that's a huge question. Again, like I said, what I think
00:48:16.300
of as, this would make a terrible subtitle, so it's not the subtitle of my book range, is
00:48:20.040
the things that you can do that seem the best in the moment maybe are not the best for long-term
00:48:24.720
development. And I think that applies to parenting. Maybe we should talk about that
00:48:28.260
college admission scandal or something. The snowplow parent isn't the new, but clearly that's not the
00:48:33.400
best for long-term development in many cases. There's a story you write about, I think it's at the
00:48:38.520
Air Force Academy that illustrates that point. Explain that insight. This was one of my favorite
00:48:43.660
studies in range, partly because the experimental setup is so cool. You could only do this at the
00:48:48.780
U.S. Air Force Academy. It's a true experiment. It has randomization, it's prospective, and there's
00:48:53.760
blinding. Check all the boxes. Yeah. Yeah. So at the U.S. Air Force Academy, about a thousand students
00:48:58.440
come in every year, and they have to take a sequence of three math courses, calculus one, two, and third
00:49:03.580
course. And they are randomized to professors in year one, re-randomized in year two, and re-randomized
00:49:09.460
in year three. And the characteristics they come in with are spread evenly across classes. And so
00:49:15.480
para-scientists wanted to see, okay, this is a great experimental setup for looking at what is the
00:49:20.720
impact of different math teachers. So they followed about a hundred professors and 10,000 students over
00:49:26.380
a decade. And one of their main findings was that the better a professor was, oh, and everyone takes
00:49:34.160
the same test in every class also, and it's graded by committee, so there's no one can make their own
00:49:38.240
students do better. What they found was the better a professor was at getting their students to
00:49:42.100
overperform in calculus one, the more those students then underperformed in the next two follow-on
00:49:47.720
courses. So there's an inverse relationship between how well students with a certain professor did in
00:49:52.520
the first course and how well they did in the second and third. So for example, and how they
00:49:56.580
rated their teachers. So I think the professor who was rated the sixth best by his students in calculus
00:50:02.520
one, and his students got the seventh best scores overall, I think, out of a hundred professors,
00:50:09.400
his students did the seventh best, was dead last in how his students then did in the next two courses.
00:50:15.300
And just to be clear, were they dead last or were they dead last in improvement?
00:50:20.000
So there was a value-added score, which said, here are the characteristics these kids come in
00:50:24.740
with, and here's how we'd expect them to do. Are they over or underperforming?
00:50:28.420
Yeah. So it's not that they were the worst in Calc 2, it's that they underperformed relative to
00:50:35.340
So they grew the least, maybe is the right way to think of this.
00:50:38.000
That's right. Yeah, absolutely. Compared to other people who came, other students who came in with
00:50:41.620
the exact same characteristics, they did worse than them in the follow-on courses. And what these
00:50:45.920
scientists found was that the way to get students to do the best in calculus one was to teach a
00:50:49.800
very narrow curriculum that was tailored to the test, where they learn a lot of what's called
00:50:53.800
using procedures knowledge, where they just learn how to execute algorithms and things like that
00:50:57.660
over and over. Whereas the professors who got rated worse by their students, and their students
00:51:04.400
did worse on the calculus one test, they learned more, it's called making connections knowledge,
00:51:08.700
where you have to draw together concepts essentially, and you're facing different types of problems
00:51:12.500
instead of repeating the same type over and over, which is another thing we should talk about
00:51:15.700
after this. But then when they go to the next courses, they have this more conceptual,
00:51:21.060
flexible knowledge. They're learning how to match a strategy to a type of problem instead of just
00:51:25.140
how to execute procedures. So they do better later on. And so there's this real conflict between how
00:51:30.340
they feel they're doing early and how they rate their professors and how they're really being set up
00:51:36.860
And that spoke to me on many levels, but one of which being is I love mathematics. And I think we spoke
00:51:43.180
before and maybe we'll tell the story, get into that, get into the issue later about, I've always
00:51:47.000
wondered about the transition I made when I decided to take school seriously. But that teacher who I
00:51:53.020
think sort of turned my life around would go on to teach me calculus as well. And he had a very unique
00:51:59.440
style of teaching, which was you approach every problem through the lens of understanding what is
00:52:04.520
being asked physically and seeing if in the end, the question says, okay, Johnny throws a ball at this
00:52:10.760
speed in this angle. Where does it land? That might be the question. I mean, that's a very simple
00:52:14.540
calculus question, but that's an example. But as the problems get more and more challenging, he would
00:52:19.080
still really insist that you try to understand graphically using sort of functional calculus,
00:52:26.620
like graphically what is happening, algebraically what is happening, and numerically what is happening.
00:52:31.440
And how can you converge the numerical solution with the algebraic solution with the graphical
00:52:35.780
solution? He said in calculus, you should almost always be able to come up with an
00:52:39.660
estimate of where the answer is based on graphing the functions and looking at how they behave.
00:52:46.160
Hard. I mean, a lot of kids didn't do very well in calculus. And yet those lessons took me all the
00:52:53.380
way through honors math and engineering. And another sort of example on that path that really spoke to me
00:53:00.000
was in my freshman year of calculus, I met this guy studying in the stacks. His name was JP. And he
00:53:06.380
became a legend to me because he had simultaneously, he couldn't decide if he wanted to be a mechanical
00:53:11.420
engineer or an electrical engineer. So he did both. And he literally got both degrees in four years.
00:53:16.160
It's not impossible to get both of those degrees in five or six years, but to do both in four years
00:53:20.020
is crazy. And he said, the only way he was able to do it was he never wanted to memorize how a type
00:53:27.260
of problem was solved. He wanted to derive everything from first principles. At the time, I think we were
00:53:31.600
learning about Coriolis acceleration, which is basically the acceleration of a body in rotation
00:53:36.760
where the radius is changing. So named after a guy who failed to figure this out when miners in a shaft
00:53:43.080
were moving down. So now you actually had a shrinking radius relative to the center of the earth. And that
00:53:48.300
changes the forces on the elevator shaft. And he said, you realize you could derive that all from
00:53:55.480
Newton's first law. And I was like, I never thought of it that way. And he goes, yeah, let's go through it.
00:54:00.040
And it's about a one page derivation, but you can do it. And that lesson stuck with me for the
00:54:04.460
remainder of my life, which was, oh my God, if you just think of it in these broader, initially more
00:54:10.540
painful ways, it yields huge dividends. This gets at so many things. I'm not even sure where to start
00:54:16.820
in range. But the first thing that popped in my head was I just saw somebody tweeting research on
00:54:20.040
Twitter today about how active learning students actually learn more, but they rate themselves as
00:54:23.880
having learned less. And they also rate their teachers worse. So it turns out we're early on, we're not
00:54:28.340
actually that good evaluators of how we're doing because the feeling of fluency and learning makes
00:54:32.520
us think we're doing well, but we're actually not. This is what I wrote about called desirable
00:54:35.920
difficulties. But what you were talking about, I mean, that's serious making connections knowledge.
00:54:40.440
In Japan, they actually have a term called bansho that means the type of writing on the blackboard
00:54:47.680
that tracks all these different approaches to the same problem, sort of what it sounds like your
00:54:51.780
teacher was doing. But I want to get to the derivation point because there was some research
00:54:57.720
I wrote only a little bit about in range, but that I read a lot more about that was about what
00:55:01.460
college students understand about math, essentially. And there were some really startling examples where
00:55:07.860
one of the problems was like, I can't remember what the exact numbers were, but let's say it was
00:55:14.020
500 plus 200 equals 700. And the students were asked, how can you check if this was right? And so I'd say,
00:55:19.580
700 minus 200 equals 500. That's right. What's another way you can check if it's right? And they
00:55:25.440
wouldn't come up with 700 minus 500 equals 200 because they were taught to subtract the number
00:55:30.060
on the right of the addition sign. And when their professors were shown this sort of stuff. So this
00:55:34.540
is wicked feedback. So you get the feedback that the student understands because they know one way
00:55:37.880
to do it, but they actually don't understand it all. And the professors would say, oh my gosh.
00:55:43.940
And the students would, in interviews, they'd say like math is a system of rules and executed
00:55:47.680
procedures. Professors would say like, I went into math because I didn't have to memorize stuff
00:55:51.900
because you could derive it and it makes sense. It's just concepts. And so they were just in a
00:55:55.900
totally different place than the students were. And it sounds like you had some opportunity to
00:56:00.660
avoid that, but I think that's the norm of how math teaching works.
00:56:03.660
Yeah. And it's hard because my daughter who's in sixth grade, I'm doing this thing and it's really
00:56:08.340
hard. I mean, I can't imagine I'm the only parent that struggles with this, but I want her to love
00:56:12.380
math. I don't want her to view it as a subject. I want her to view it as math is more fun than
00:56:18.600
playing video games. Math is the most beautiful thing in the world. I want her to look out the
00:56:24.580
window and see math and see that math is a beautiful tool that we have to explain the world around us
00:56:31.520
through this thing. And yet every time as a parent, I try to ask her a question to ask her to think a
00:56:37.760
certain way. I end up sort of putting her on the spot. And so I'm struggling with this thing of
00:56:41.760
one, is it just that I'm a bad parent and I don't know how to do this correctly?
00:56:46.980
Definitely that you're a bad parent. I didn't want to say anything, but since you brought it up.
00:56:49.880
Or is it that a child needs a certain base of facts? Like they have to know a handful of things
00:56:56.980
and be confident with the language, like the times tables and all these other things before you can
00:57:02.080
even get them to start thinking beyond the problem. Like I think a lot about this actually,
00:57:07.260
because I feel like I'm underperforming on this actually.
00:57:10.460
It's a good point though. And I should say, so again, in research, these are called using
00:57:13.620
procedures knowledge, which is kind of the knowing stuff and making connections knowledge,
00:57:16.600
which is derivation, understanding concepts. And they're both important. It's just that like in
00:57:21.540
some of these famous studies in the United States, almost a hundred percent, sometimes literally a
00:57:26.180
hundred percent in classrooms would be the using procedures knowledge and not the making
00:57:29.920
connections. But I think that is a tricky thing. There's a study that came out after a range,
00:57:34.840
so I couldn't include it, but was on the topic of desirable difficulties. And it was about
00:57:41.160
interleaving, which is, well, I'll explain the study. Seventh grade math classrooms were randomly
00:57:46.320
assigned to different types of math teaching. Some of them got what's called blocked practice,
00:57:50.720
where you get problem type A, A, A, A, A, B, B, B, B, B, and so on. And the students get better
00:57:55.840
really quickly and they rate their teachers well and they rate their own learning well. Other classrooms got
00:58:00.320
interleaved practice where it's like as if you threw all the problem types in a hat and you pick
00:58:04.040
out randomly. And in that condition, the students are frustrated at first. They rate their own
00:58:08.360
learning low. They rate their teachers poorly. But again, they're learning how to match a strategy to
00:58:13.100
a type of problem instead of just do the same thing over and over. And come test time, they all took the
00:58:16.540
same test. The interleaving students who had interleaved practice blew the blocked practice
00:58:21.560
students away. It was, I think, like the largest effect size I've ever seen in an education study
00:58:25.680
that was randomized, 0.83 standard deviations. It was like taking a kid from the 50th percentile
00:58:30.840
and moving them to the 80th percentile. But they didn't like it early on. They don't feel like
00:58:35.260
they're learning. And so I'm not sure what the balance is as a parent where you know some of
00:58:39.720
this desirable difficulty is in the long-term desirable, but you also don't want to turn someone
00:58:44.320
off from the subject. So what's that delicate balance? I think that's sort of kind of the art of
00:58:49.640
coaching in everything we do, whether that's someone in sport trying to develop someone for the long-term
00:58:53.740
or a parent is like, how do you balance maintaining enthusiasm with optimal development and helping
00:59:00.060
someone have that vision of their future self, like your professor did for you without having
00:59:04.960
them be burned out? I don't know. I really think that's why there's what like great coaches kind
00:59:09.720
of do is they figure out how to balance these things, when to make things difficult and when to
00:59:14.380
allow things to be easy and sort of more easily inspirational. But I think that's an art as well
00:59:18.660
as a science. So what was sort of the takeaway of the idea that, and I don't like using the extreme
00:59:27.080
examples because they're sort of silly and that's the problem with them. But if you look at a high
00:59:33.240
school track team, okay, and you look at, you pick a big division one school and you look at their
00:59:39.600
sprinters, are they genetically predisposed to be sprinters, but without a certain degree of training
00:59:48.600
could never appreciate it? Or could a certain amount of training overcome a lack of genetic
00:59:53.960
predisposition? I mean, how do you feel about that today versus when you wrote the book versus when you
00:59:59.660
wrote the article? Because again, you're getting smarter as we go. Yeah. When I wrote the article,
01:00:04.000
I was more convinced than I had been before the article that genes were unimportant, completely
01:00:10.720
unimportant. And by the time I wrote the book, I came to feel that there were sort of two extreme
01:00:15.800
camps, one that felt genes have no influence on performance. And another that I'd say the other
01:00:22.440
extreme wasn't that practice has no influence. I don't think anybody thought that's uncontroversial.
01:00:28.500
So I think one extreme was only practice matters. And the other extreme was practice and genes
01:00:33.660
matter. I think that is not as extreme saying they both matter. Which, and my bias is the latter.
01:00:38.800
My bias is just that. I mean, that's what the evidence shows. Yeah. And it's like people don't
01:00:43.660
randomly pick to train for the marathon to the hundred meters if they're trying to get to the top
01:00:47.240
level because there's some zero sum physiology going on there. And so I think to be a sprinter,
01:00:53.180
you're not turning a cart horse into a racehorse as the saying goes. Like you have to have some
01:00:57.180
predisposition to being fast and being explosive. And there's a reason why those people are particularly bad.
01:01:03.660
Usain Bolt would be a worse marathon runner than a random person picked off the street
01:01:07.200
because it's different physiology. But, but I also think it's important to note that at the
01:01:12.340
beginning of the season and six months later, someone like him are very different in how fast
01:01:16.300
they are. Even over the course of one season, they change how fast they are. So I think the
01:01:19.400
practice is, is incredibly important, but you also need talent.
01:01:23.680
Now, which is maybe a reasonable segue into a story that I know you just get asked about all the
01:01:28.100
time. So, but I also feel like for the sake of the listener, if they haven't heard you on
01:01:31.300
another podcast, it's worth them hearing you explain the difference between Roger Federer and
01:01:36.880
Tiger Woods. But of course I, once you're done with this, I want to kind of go down more extreme
01:01:40.680
examples and stuff. So is it safe to say that the contrast between Tiger and Roger are elite
01:01:49.480
Yeah, yeah, definitely. And it's sort of interesting because, well, I'll give the quick versions of the
01:01:53.540
story first before I criticize myself. The Tiger Woods story, I think even if people don't know
01:01:58.040
the details, they probably kind of absorb the gist. Seven months old, father gives him a putter.
01:02:01.660
Not trying to turn him into a golfer, by the way. Oh, this reminds me, we should talk about how the
01:02:04.520
Tiger and Mozart stories I think are told wrong after this. So I'm just putting that on our cork
01:02:08.560
board here. Ten months, he starts imitating his father's swing. Two years old, you can go on
01:02:13.660
YouTube and see him on national television demonstrating his swing on the Mike Douglas show.
01:02:17.560
At three or four, he starts saying, I'm going to be the next Jack Nicklaus. Fast forward to age 21,
01:02:22.240
he's the greatest golfer in the world. And that's sort of the quintessential, I think that story has
01:02:25.840
seeped into culture so much that people who don't even follow golf ever kind of know it.
01:02:30.440
Federer, on the other hand, every bit as famous as an adult, but obscure.
01:02:36.060
Every bit as dominant, more so over a longer time.
01:02:39.080
And when he was a kid, he played some basketball, badminton, tennis. His mother was a tennis coach,
01:02:44.640
refused to coach him because he wouldn't return balls normally. He continued on to do skateboarding,
01:02:49.020
swimming, wrestling, soccer. When his coaches wanted to move him up a level, he declined because he
01:02:54.680
wanted to talk about pro wrestling with his friends after practice. He went on to play handball. Maybe
01:02:59.520
I said volleyball already. I'm not sure. Some rugby.
01:03:01.960
Do we know how good he was at these other sports, by the way?
01:03:03.980
He was good at soccer, for sure. Most of the other sports, I'm not really sure. But he kept playing
01:03:08.420
badminton, basketball, soccer longer than some of the others. And then soccer was the one that he
01:03:13.260
finally decided he had to choose between soccer and tennis.
01:03:16.820
And what age is that when he's having to make that decision?
01:03:19.300
I think he was starting to think about that as he was entering his teens, basically.
01:03:22.180
And he wasn't focused. Tiger's saying, I'm gonna be the Jack Nicklaus when I'm four. Roger was
01:03:27.540
actually, when he first got good enough to get interviewed by a local paper, the reporter asked
01:03:33.220
him if he ever became a pro, what would he buy with his first hypothetical paycheck? And he says,
01:03:36.920
a Mercedes. His mother doesn't want him putting all his eggs in this basket. It's like appalled.
01:03:40.600
And I asked the reporter if she can hear the interview recording. And the reporter obliges. It turns
01:03:44.260
out Roger said Mercedes in Swiss Germany. He just wanted more CDs, not a Mercedes. And so his mom's like,
01:03:48.700
all right, fine. But it's just very different in every way from the Tiger story. And the way I sort
01:03:54.120
of used these is as a device to start range, first to set up just the concept going forward. The book
01:03:59.680
proposal was titled Roger versus Tiger. And it was going to be like, when should you be a Roger? And
01:04:02.940
when should you be a Tiger? But they felt everyone would think it was a biography of those two guys,
01:04:08.000
my publisher. And I thought it was telling that we only know, only hear one of those stories.
01:04:12.720
And my question was, which of these is the norm? Obviously, they both worked for these
01:04:16.240
individuals. And I think there's many paths to the top as there are people. But what was the norm?
01:04:20.260
And it turns out that the norm when scientists track athletes en route to becoming elite is that
01:04:25.100
early on, they tend to have what they call a sampling period, where they try a wide variety
01:04:28.420
of activities. That often includes things like martial arts and dance and doesn't just have to be
01:04:32.880
other sports, gymnastics. And they learn these broad general, these physical skills. And they learn
01:04:39.560
about their interests and their abilities, importantly, and delay specializing until later than peers who
01:04:43.880
plateau at lower levels. And that turns out to be the norm. And so I sort of felt we should let people
01:04:50.180
know what the norm is, instead of always focusing on these very few exceptions that happen to be in
01:04:55.720
like the most kind learning environment, sports, and that aren't that good to extrapolate to everything
01:04:59.900
Now, how much of that do you think is the psychology of it and the neuromuscular physiology of it? So
01:05:09.580
looking at Roger, for example, who I know very little about Roger Federer, that's not the obvious
01:05:14.760
stuff that most people who are not, I'm not a tennis fan or anything like that. But part of his
01:05:19.240
longevity, is it possible to be explained by the fact that he never burnt out versus just sort of
01:05:25.200
slowly acquired a love for this thing versus had it shoved down his throat? I'm sure like there's lots
01:05:31.060
of stories of trying to create these tennis prodigies where it probably backfires because by the time the
01:05:35.900
kid is 16, they're great, but they've lost the desire. So it's more of a above the neck phenomenon
01:05:42.300
than a below the like environment. How much of it do you think is that versus in playing all those
01:05:47.420
other sports, Roger actually developed synaptic connections that served him better in tennis?
01:05:56.840
He basically created a bigger foundation across his neuromuscular system that ultimately came to
01:06:04.240
serve him when he specialized. So there are a couple points. So this will be a sort of a longer
01:06:08.680
point for us because you bring up a couple of good things. Initially, I thought that most of the
01:06:12.860
effect was going to be accounted for by the fact that if you allow people to delay selection, it's
01:06:17.520
more likely you get them in the sport that they're the best at. Whereas we know the earlier you force
01:06:21.940
selection, the more likely you put the wrong person in the wrong sport. And when selection occurs
01:06:25.340
really early, you end up seeing this huge relative age effect where coaches just pick for kids who are
01:06:29.180
born early in the selection year because they're seven or eight or nine or 10 months older than their
01:06:33.640
cohort. And so they're at young ages, that's a huge difference. And so coaches mistake biological
01:06:38.800
maturation for talent. So I thought most of it was just going to be the fact that if you delay
01:06:42.580
selection more, you'll get the right people in the right sport more. But then I started coming across
01:06:46.680
these studies of German national soccer players or people in the national development pipeline,
01:06:51.420
where they were matched for ability at a certain age, tracked for several years, and they see who
01:06:56.220
improves more. And at certain ages, you have to focus eventually, but at certain ages, like in the early and
01:07:00.860
mid-teen years, it was those who did a wider variety of activities. And so then I started to think maybe
01:07:05.580
there really is something to the skill benefit, which didn't surprise me intuitively, but to see
01:07:10.800
it empirically was interesting. And then I spent some time with, I should say, by the way, my colleague
01:07:15.740
John Wertheim asked Roger Federer about this, one of the questions you asked on the Tennis Channel
01:07:19.340
recently, and Roger Federer said it contributed to his not burning out. You know, you never know how much
01:07:23.440
to trust someone's own story, but it's worth noting that that's what he said. I spent some time with
01:07:28.200
this physiologist for Cirque du Soleil, and he noted that they started implementing this program
01:07:33.980
where, because some of the performers are former Olympians and things like that too, where they
01:07:38.600
would have performers learn the basics of three other performers' disciplines. Not because they
01:07:42.300
were ever going to perform them, but let's see if it would vary up what they were doing, maybe reduce
01:07:46.500
stress-related injuries and stuff like that. And they track their injuries next to Canadian
0.93
01:07:51.280
Gymnastics. I guess it's a Canadian company. And he said it reduced their injuries by like a third.
01:07:55.800
So they implemented it. They must feel really strongly about it if they're taking away from
01:08:00.400
practice time for those performers their main discipline. There seems to be something. This
01:08:04.340
showed up in another longitudinal study of young athletes where the best predictor of suffering
01:08:08.800
what they called an adult-style overuse injury was how specialized the athlete was. And it wasn't
01:08:15.380
necessarily their total time spent in physical activity. It was if it was just the same thing over
01:08:19.740
and over. So there was like some protective effect from diversifying. We can guess at what that is. I'm sure
01:08:24.580
your guesses would be better than mine. But ultimately, my feeling is the Roger pattern is
01:08:30.080
more prevalent. One, because you have that breadth of training that predicts breadth of transfer. You're
01:08:34.800
exposed to much more neuromuscular stuff, much more perceptual stuff. And when the challenge gets
01:08:39.440
harder as you go up, you need to draw on those. There's a funny book called Extraordinary Tennis for
01:08:45.520
the Ordinary Player. I think by this guy, Cy Ramo, who's better known as the father of intercontinental
01:08:50.440
ballistic missiles, but also wrote some books about tennis and a couple other things. And in it,
01:08:56.560
one of the interesting things in it was that he shows, he does some like serious analysis of
01:09:01.680
gameplay at different levels and shows that even for good amateur players, something like 80 or 90%
01:09:08.100
of the points are scored by just keeping the ball in play and someone making an error. And then when
01:09:12.080
you get to the elite level, it's totally exactly the opposite. It's like 80, 90% of points have to be
01:09:16.440
earned. And that completely changes the kind of game that you're seeing. So I think the challenge
01:09:21.460
that a lot of these athletes are facing really changes a lot as they go up in levels. And so
01:09:25.760
they really want to have that kind of breadth of training in this experience, responding to
01:09:30.320
different types of... Do you think this overlaps with the Air Force Academy example where having the
01:09:34.960
harder, more orthogonal education in calculus prepares you for more real world problem solving,
01:09:43.120
which is what's happening as you go from calc one to two to three?
01:09:45.720
I think so. I think so. And I mean, again, that's why I think the theme of the book is
01:09:49.060
the things that'll cause you to be the best today might not be the best for five or 10 years from
01:09:52.820
now, or the best way to develop a 10 year old might not be the best way to develop a 20 year old
01:09:56.800
or certainly isn't. And it's also, I think the specialization model may well, there's a surprising
01:10:01.900
dearth of research in golf for how popular sport it is. But I think the specialization model may well
01:10:07.260
work for golf because you're not facing some of that same stuff. It is a very kind learning environment.
01:10:12.100
And I mean, I guess the best guy in the world right now, Brooks Koepka didn't come until later.
01:10:16.080
And it's unclear if he even likes golf, but I could see, it makes sense to me that the
01:10:20.880
specialization model would work or at least not be deleterious in golf. Whereas in the other sports,
01:10:26.320
What about the sports where physiology is undeniably huge? So the big three being swimming,
01:10:32.080
cycling, and running. Cycling is hard to talk about because people tend to conflate the use of
01:10:37.300
drugs with somehow discounting the remarkable physiology of these guys. But if you take a
01:10:42.420
Chris Froome, for example, four time Tour de France champion, grows up in Kenya, we can speak to what
01:10:48.240
the importance of early exposure to hypoxia could have been. What is our belief about the training
01:10:56.540
effect and the duration of the training effect necessary to produce world-class athletes at that
01:11:00.880
level? Because to me, that's as foreign... Like if you said to me, Peter, I'm going to put you in a
1.00
01:11:07.120
time capsule. You're going to be 16 or 14 years old again. Knowing everything you know today, if you
01:11:12.660
have to become a professional athlete, which sport would it be in? The answer is none. I positively know
01:11:18.440
there's nothing I could ever be good enough in. And that includes if I was willing to do everything
01:11:24.720
that was necessary to become the best cyclist, runner, swimmer, I just couldn't do it.
01:11:28.460
You'd have to do what some countries host the Olympics. What they focus on is just recruiting
01:11:32.460
more people in the much less competitive sports. If there's a basket weaving... I have a friend who
01:11:37.080
joked about this because my interests are so diverse. He goes, Peter, do you realize that if
01:11:41.580
someone comes up with an Olympic sport that requires solving a differential equation, driving a car fast,
01:11:48.300
shooting a bow and arrow, and doing a deadlift, you could be one of the best? That's basically
01:11:53.180
modern pentathlon. You're pretty much there. And he listed off 10 other really stupid esoteric
01:11:58.200
things I do. And I'm like, yep, that's great. That's my claim to fame.
01:12:01.380
Modern pentathlon is like fencing, horse riding, swimming, running. It's like, we should have that.
01:12:06.660
I think there was a time when chess and fiction writing were in the Olympics. So there's hope for
01:12:13.800
Or like the Brits, I think in the winter sports when skeleton got introduced, which is where you
01:12:20.160
And there's a great innovation story about that if you want to get to that. But one of the guys who I
01:12:23.920
talked to in their program said, we've got this down like 80% to a science. We make like an open
01:12:27.540
call for women. We like do some measurements. We know what size they need to be. We know what kind
1.00
01:12:32.140
of explosion they need to have. We pick the gold medalist. And they've done that. So that stuff's
01:12:38.280
But do you think that for these super physiologic things where presumably mitochondrial density,
01:12:44.480
mitochondrial efficiency, fiber distribution matter the most, is that more of a golf? Is that more
01:12:51.080
tiger? Is that more Roger? Notwithstanding the psychological component, which is obviously enormous.
01:12:56.740
So I think in sports in general, more people, a hundred years ago, you could have come to the
01:13:01.200
Olympics and been the only person who knew anything about training or the only person who was really
01:13:04.280
talented and win. Now I think in every sport, many more people are ruled out by either their nature
01:13:09.300
or their nurture, no matter what the sport is. But I think in those-
01:13:12.340
Meaning they're not willing to train hard enough, no matter how much their ability. So that rules
01:13:15.780
Or they don't have the opportunities. I mean, a huge portion of people in the world don't have an
01:13:18.780
opportunity to be exposed to most sports. So they don't have the opportunity. I mean, I think one
01:13:21.820
thing, the impact of Title IX in the U.S. is showing in how dominant we are in some women's
1.00
01:13:26.540
sports. Where I think I just saw, I think Ross Tucker, he's at Science of Sport, a prominent
01:13:30.700
sports scientist. He tweeted that the United States has something like 40% of all the women's
01:13:35.660
registered soccer players in the world. So like, of course we're awesome because we're giving more
01:13:39.220
opportunities. So I think a lot of people, either they're not willing to train, they don't have
01:13:43.500
access to training, one of those, or they don't have the nature for it. And the more competitive
01:13:48.160
the sport is, the more important that is, right? Because obviously if we had everyone do identical
01:13:53.040
training, only genes would separate them. And if we had everyone be identical twins,
01:13:56.160
only training would separate them. But I think people are more quickly filtered out by their
01:14:04.980
38. So I'm 10 years older than you, but directionally, like we're both clearly past our
01:14:11.280
Sports-wise, yeah. I think I'm past my prime in everything, but clearly athletically. Is there
01:14:15.900
a reason that I, let's assume I'm a decent athlete, which I'm actually not, but let's assume
01:14:21.060
I was. Could I, if I decided tomorrow, like I want to play tennis, I don't think anybody would
01:14:28.000
ever assume I could become a good tennis player. But is it because the deliberate practice argument
01:14:33.060
would be there aren't enough hours left for you to devote to this? Another argument would be, no,
01:14:38.560
you've missed a critical window. Just as we say, by the way, this might be totally BS. I'd like to
01:14:42.740
hear your view on it. This view that we learn language is best at a certain window. And once
01:14:46.540
that window closes, it's sort of like a growth plate closing over a bone. It becomes really hard
01:14:51.200
to learn languages thereafter. Is there something about this critical window of exposure? I guess
01:14:56.340
is really the thing I'm trying to get at with this question when it comes to physical talent.
01:15:00.500
That's a tough question. And there's this book by a neurologist called Why Michael Couldn't Hit.
01:15:05.220
I love this book. It was one of my favorite books.
01:15:07.620
So he was saying Michael Jordan kind of missed the critical window for developing the perceptual
01:15:11.940
anticipation skill that you need to see things that are coming because your reflexes are too slow.
01:15:16.900
Right. Why the greatest athlete we'd ever seen of a generation was a 188 hitter in triple A ball.
01:15:23.300
Yeah. I'm a little bit of a gadfly about that though, because I think that was a great book. I
01:15:27.260
I love the Wayne Gretzky story, by the way, but we'll come back to it.
01:15:29.520
Great. Yeah. And one season, I think Michael hit like 220 or something like that in minors,
01:15:33.500
which I think if we went down and picked a random person off the street, they would hit zero
01:15:36.660
in AA. These are people who are stars of college and high school teams or foreign teams. So did he
01:15:42.100
do well or poorly? I don't know. If he had hit 10, you know, I wouldn't have been surprised because
01:15:46.560
he hadn't been playing in a long time. So I'm kind of impressed with what he did. But I also think
01:15:51.440
I mean, I think the point though was the expectation. It's not that hitting 288 or whatever
01:15:55.440
in triple A ball is horrible. No, it's just, why isn't the guy that seemingly has the best
01:15:59.920
hand-eye coordination in the world immediately able to absorb it?
01:16:03.340
Right. And in that sense, I do think there was probably something to the critical period.
01:16:06.400
And there are always people, there are always exceptions to everything. One of the most dynamic
01:16:10.160
players in baseball now is Lorenzo Cain. And he did not play a game of baseball until age 16.
01:16:16.320
That surprises me. He did not know how to play. I think most people would need to have some
01:16:21.460
exposure, not necessarily specialized, but have some exposure at that age. So there's always exceptions.
01:16:25.380
But I do think you want some of that early exposure, partly just because you run out of time,
01:16:30.400
because you want your perceptual expertise to coincide with your physical, right? So you're
01:16:35.520
just under a serious time limit. And in relating that to language, I actually do think, and you
01:16:40.000
know, there was a guy who tried, dropped everything when he read about the 10,000 hour rule and decided
01:16:43.700
to try to become a pro golfer by doing 10,000 hours exactly. And he got Erickson to consult with him
01:16:50.500
He got to something like 7,000 hours or something like that. And then he, he stopped, he was having
01:16:56.600
injuries. And what happened was, I think he didn't make it and he didn't nearly make it,
01:17:02.460
but he got really good. So he got better than like 90% of amateurs or something, but wasn't nearly
01:17:07.380
going to get into Q school qualifying for a professional tour. And so what I think,
01:17:12.920
and I didn't know if he was going to make it or not, because my point has been like,
01:17:15.260
people were saying, Oh, you were right. He didn't make it. I wrote a little bit about him. I'm like,
01:17:17.920
that's not what I said. I said, there's huge individual variation. If he's going to make it,
01:17:21.260
it's not going to be at exactly 10,000 hours. And so he didn't make it.
01:17:25.340
By the way, do you think there's enough variation that it almost is uncoupled? Like what would be
01:17:28.680
your 90% confidence interval on that? Or does it even matter? I mean, I think there has to be a
01:17:36.260
90% confidence interval, right? If you think about it, is it a thousand to 40,000? If you had to say
01:17:41.500
90% of people that become, that achieve mastery do so in a certain amount of deliberate practice.
01:17:45.820
I think it really depends on the sport. I listed in the sports team, I listed some hours and it
01:17:49.680
varied a lot by sport. And so I think it sort of depends what it is. Most of them were in sports
01:17:54.480
were lower than 10,000 hours, significantly four to 6,000 hours kinds of things. And again,
01:17:58.320
these are averages in chess. It was higher than that. So I think it depends. I think it's sport
01:18:03.400
dependent. And again, something like skeleton, there's a great paper called ice novice to winter
01:18:07.720
Olympian in 14 months, where it's basically just pick somebody and then they can go to the Olympics.
01:18:11.540
So I think it depends on what you're doing. And also when I sat in on a Harvard Business School
01:18:16.120
class for some reporting I was doing for range, you just reminded me of something where the
01:18:21.000
professor asks the students, he asked them all these things like, how many Subway sandwich shops do
01:18:26.340
you think there are in America? Give your 90% confidence interval. And basically, we can't do it
01:18:31.960
because if you're asked that question, if you're asked 20 of those questions, you should be able to
01:18:36.260
get 18 correctly in a reference range. I've played this game myself and with people. I've never seen
01:18:41.920
anybody come close to it. People don't go big enough. Give your 90% confidence interval and
01:18:45.660
you'd be better off going like, well, I know there's 10, you know, to like a million. And
01:18:50.820
instead they go much narrower and they end up missing almost all of them. So what would my 90%
01:18:55.860
confidence interval be? And it's sort of, it depends what counts too, because there's some accounts
01:19:01.040
of athletes who have done a bunch of different sports. And so there are studies that show that
01:19:05.920
invasion sports are the ones that require anticipatory skills. People can't see me doing
01:19:11.120
air quotes. I guess we're on a podcast, but that's the term that they use in the invasion sports where
01:19:16.240
you have to anticipate things that are happening faster than you can react to. Boxing, soccer,
01:19:21.680
whatever, baseball, things are flying, trying to get past you. There's some studies that show that
01:19:26.480
people who have done a variety of invasion sports will then pick up any subsequent invasion sport
01:19:32.520
more rapidly. And so I think there was a case of one woman who had played a variety of sports and
01:19:39.520
then it only took her like 500 hours to become one of the best basketball players in the world,
01:19:43.100
but she'd played netball and she'd played a whole bunch of other sports, volleyball and all this
01:19:47.580
stuff. So it sort of depends. What do you count as deliberate? Like Erickson wouldn't count that as
01:19:51.180
deliberate practice because it's not the same sport, but clearly it is like lowering the threshold.
01:19:55.240
Well, and that's really the Federer point, isn't it? It's that all those other sports,
01:19:59.260
he's doing soccer, badminton, et cetera. I mean, they're still training in a more diffuse way,
01:20:05.420
a set of skills that obviously have gone on to serve him greatly in tennis.
01:20:08.440
Yeah. And I think this relates to language. I want to segue to language a little bit, which is
01:20:11.460
I wanted to write about language in the book. As I was going through all the research,
01:20:17.480
I found so much of it contradictory and confusing that I decided to kind of stay away from it largely
01:20:23.560
because I just couldn't figure out. I was hoping there'd be, in my proposal I wrote about this,
01:20:27.520
I'd seen this really cool study and I had video for it where infants who were being raised bilingual,
01:20:33.220
they were given like this lucite box sort of thing and plexiglass or whatever it was.
01:20:39.500
And there was some object and they had to find the opening in this clear box and get an object out
01:20:44.200
of it and then put some other object in it. And the ones who were bilingual would try more different
0.99
01:20:49.240
strategies. And the researchers were saying, well, they think differently and they have more
01:20:53.060
executive function. And I thought that was tantalizing. And I loved the video, but I just,
01:20:58.040
the research was all over. And my conclusion was kind of, there's a lot of tantalizing stuff,
01:21:01.700
but nobody's quite sure really for a lot of it. But one that I did think was pretty strong was the
01:21:06.480
idea that people who grew up bilingual had an advantage for then learning a third language without
01:21:12.380
being taught it formally. So there were studies where they'll be given like a fake made up language and fake
01:21:16.920
grammar and just have to learn it by immersion. And they seem to do that better. And I think that's
01:21:21.320
sort of akin to what we see in sports. And with regard to the sensitive period, I do think there
01:21:26.920
is a real sensitive period in language where I think about after like age 12, you're not going to make
01:21:32.360
something your native language anymore. And I think there are cases where kids, feral children cases,
01:21:37.560
these rare cases where a kid like grows up in the woods or isolated from people. And if they haven't
01:21:41.260
learned some, if they haven't had exposure to language by age 12, they never learn it basically.
01:21:45.240
And that also happens to be about the age you have to start. If you don't start studying chess
01:21:49.160
patterns by age 12, your chances of reaching international master status drop. International
01:21:53.280
master status, again, one down from grandmaster. They drop from like one in four to one in 55.
01:21:57.920
So I think there are some critical periods, but I don't think for most things, maybe for these feral
01:22:03.800
children, but for most things, I don't think it's nearly the expiration date that people think it is.
01:22:08.240
I think most people can get better at most things than they think they can.
01:22:12.020
And they can get better at most things than they think they can at older ages than they think they
01:22:16.780
can too. Yeah. It's funny you say that that's kind of where I wanted to pivot for a second,
01:22:20.740
which was all of this discussion is interesting through the lens of being the absolute best
01:22:25.180
tennis player or the absolute best golfer on the planet. But isn't that really besides the point
01:22:30.400
for most of us? Because if there's 7 billion of us on this planet, 6.9999999 billion of us are never
01:22:37.000
going to be good enough at anything to make a living at it outside of our day jobs. Anyway,
01:22:41.380
I was asked on a podcast recently why I love archery and driving a race car so much. And part of it is
01:22:50.840
there is still every six months, I'm still able to look back and appreciate the progress I've made.
01:22:57.940
In other words, I'm coming from a place of being so not expert at these things that the joy
01:23:05.400
is actually in the monotonic increase in skill. That is actually the joy to me. It's the, I don't
01:23:13.680
want to say mastery because that implies you are mastering it, but it's the path towards mastery that
01:23:19.220
is more joyous. And I don't know, it's almost like on some levels it must, maybe it's not that much fun
01:23:26.120
to be the best in the world at something because by definition, you only have one way to go at some
01:23:31.220
point. And that's probably a lot less enjoyable than working your way up the curve. And I guess
01:23:36.780
generalists have the ability to, I don't know, this gets more into the psychology of it again,
01:23:41.820
but you don't have to tether your identity to just this one thing. I always feel bad actually for
01:23:45.960
athletes who it's a brutal, brutal way to make a living in the sense that you have a far narrower
01:23:52.000
window in which you can be the best at something versus like say any sort of normal career.
01:23:57.020
Yeah. And if you interact with a lot of athletes, you hear a lot of them say,
01:23:59.100
now it's just a job and it was something that they loved at a certain point. I think we were
01:24:02.920
talking about Ayrton Senna earlier. I seem to recall him saying something like the times of
01:24:09.500
the sport that he loved the most were not when he was necessarily on the top of the world. It was
01:24:13.380
earlier. It was actually during his last two seasons in karting. It was racing this British
01:24:17.740
guy named Fullerton. Everything he did that karting was his favorite time, right? Absolutely. It was
01:24:23.300
pure bliss, no politics, as he said, just pure racing. I just actually interviewed a friend of
01:24:30.080
mine the other day. This podcast, it'll come out at some point in relation to this one. I'm not sure
01:24:34.160
when, but same question I asked her. She's an Olympian. And it was like, okay, you were the
01:24:39.160
second best in the world on this day. You got a silver medal. When was the sport the most fun? And
01:24:43.940
it's like, oh yeah, two years before I went to my first Olympics was when it was its most fun.
01:24:48.140
Yeah. Yeah. It's amazing. I mean, this makes me think of so many things. One, I think people that
01:24:53.860
are performers need other stuff to do. There was a study I mentioned in range where Nobel laureates
01:24:57.880
are 22 times more likely than a typical scientist to have like a serious aesthetic hobby, even though
01:25:01.940
they're certainly not as good at it as they are at their day job. For me, I noticed while I was
01:25:06.540
writing this book, somewhere along the line, I sort of started to forget what I'd loved about writing,
01:25:12.580
I think. And I keep this thing I call my little book of small experiments, where at least every other
01:25:17.320
month, I think of some skill I'd like to learn a little bit about, or some interest I'd like to
01:25:22.220
explore a little bit. And I put a hypothesis of, well, what could I try to, almost like my grad
01:25:26.720
student notebook, what could I try to get some insight into this? And it forces me to try something
01:25:31.860
new every other month. It doesn't have to be a big deal. Maybe it's some job that I don't know about,
01:25:35.520
and I just have to find somebody to talk to about it. But when I was sort of losing my enthusiasm for
01:25:42.160
the kind of writing I was doing and starting to feel more pressure, because my first book was a
01:25:45.660
surprise success. And then all of a sudden, you get a lot more pressure after that. I took an online
01:25:50.260
beginner's fiction writing course. I've been reading this book about the Zen concept of beginner's mind,
01:25:54.860
where you just always keep your mindset as a beginner, never as I've arrived. And in this class,
01:26:00.900
it's like, nobody cares who you are, nobody cares what you've done. You get back into that feeling of
01:26:05.820
being uncomfortable. And I loved it. I mean, it reminded me what I loved about doing this. It made me
01:26:10.720
totally uncomfortable, because it's still writing, but it's very, very different. I think it had these huge
01:26:15.120
benefits. One of the exercises was you had to write a story using no dialogue whatsoever. And
01:26:20.320
after I did that, I went back to my book manuscript that I had and was like, I've been leaning on quotes
01:26:24.040
in a lazy way when I don't understand stuff. If I don't understand it, the reader's not going to
01:26:27.060
understand it. So I need to learn it better and clarify with narrative writing instead of people's
01:26:31.500
voices. And so in every way, it refreshed me. And so now it's like something I really want to do.
01:26:37.320
And one of the, kind of share this, I'll attack on another story here, but this is one of the
01:26:40.620
greatest things I've ever seen in sports live. It has to do a little bit with this, having something else
01:26:44.360
going on in your identity, which was at the Vancouver Winter Olympics in 2010. Yeah, 2010.
01:26:51.660
I was up at the women's 1.6K cross-country sprint. They say sprint, but you go like way up a big hill
01:26:57.620
and come back down. And there's like four rounds. They're all in a day from the prelims to the medal
01:27:02.560
round. And this woman named Petra Majdic, Slovenian skier, had been one of the top ranked people in the
01:27:08.160
world for years and never medaled at world championships or Olympics. Totally snakebitten. Something would
01:27:13.080
always go wrong. They didn't bring the right skis. Oh, the technician didn't have the right wax,
01:27:17.340
ski brakes, like just freak stuff. And here she's favored to get silver, I think, in Vancouver. And
01:27:24.080
in the warmup, right before the first round, she slides off a curve, falls into a frozen creek bed
01:27:29.560
and bruises up all of her side. And they take her to do quick examination because she has to go to the
0.98
01:27:34.140
first round and say, okay, nothing's broken. It's just pain. Like if you're okay, you can go. And she goes to the
01:27:37.900
first round, qualifies on time when she was the favorite in that round, barely makes it through.
1.00
01:27:43.020
Second round, similar thing. They examine her. It's just pain. You know, if you can do it, you can go.
01:27:47.000
Third round, she falls down after the finish line, screaming. They have to carry her away and examine
0.99
01:27:52.040
her again and say, if anything was really wrong, we'd tell you you couldn't go. But if you can go,
01:27:55.940
you can. Final round, you hear her screaming every time she's like pulling the ground, gets the bronze
1.00
01:28:00.780
medal, just nips in there. Then they have time to examine her and find she broke a whole bunch of ribs
1.00
01:28:05.200
on her side. One of them broke off and punctured her lung. And so she came to the medal ceremony
01:28:09.980
with a tube sticking out of her chest in a wheelchair. And I remember she was, I talked to
01:28:15.540
her sports psychologist and they were saying, if we had known that she had broken all these ribs or
01:28:19.300
And had a freaking pneumothorax. Yeah. They weren't going to let her go to the medal ceremony. She was
01:28:23.660
like, I will die in the medal. I'm going, you know? And so they brought, wheeled her and they all said,
01:28:29.600
well, first of all, it's a kind of a testament to the mentality that if, if they told her it was an injury,
01:28:33.560
she wouldn't have done it. Right. But it's just pain. And I was talking to her sports psychologist
01:28:36.600
about what got her here. Like, what's the journey been like, especially after she's always having
01:28:40.360
this stuff going wrong. This must've been like, Oh, again. And he said, one of the most important
01:28:44.480
things was like diversifying her identity. She was getting so fixated on, and so much pressure.
01:28:49.580
He was like, you need to do something else. So he forced her to start building a house basically.
01:28:53.520
And that became like a task for her to do and a whole new thing and a new skill. And he felt like,
01:28:58.240
I thought maybe he was going to talk about some new type of cross training. He was like, no,
01:29:01.600
the building, the house took the pressure off. It gave her some other part of her identity. So
01:29:05.920
it wasn't just as the person who's like always having something go wrong. And I just thought
01:29:09.220
that was so interesting that his, what he felt was his main contribution was giving her a hobby
01:29:13.400
essentially. And that he thought that really allowed her not to feel like the pressure that
01:29:17.920
would break her in some way. You sort of alluded to it earlier with the story of the Nobel laureates as
01:29:22.480
well. I can't remember if it was, I think it was Francis Crick who said this, I could be wrong
01:29:26.420
that, and it might've been Watson, but I think it was Crick who said the key to doing great science
01:29:32.540
is always being a little bit unemployed. And I'm also probably paraphrasing that and bastardizing
01:29:37.620
it. It must've been said much more eloquently, but you get the point. The gist of it is great
01:29:42.700
insight in science comes from having time to wander in your mind. You said something a while ago about,
01:29:51.820
which made me very jealous by the way, and kind of pissed me off. You would read 10 papers a day
01:29:56.080
in the exploration phase of writing. And it's like, I'd give anything to read 10 papers a day today.
01:30:03.100
Instead, I feel fortunate at least to have a team that can read 10 papers a day for me.
01:30:07.260
I remember that bliss of, you just get to read the paper all day, every day, highlight it, take notes,
01:30:12.600
call the author, go to journal club, like, boo, like that was unbelievable. And we don't,
01:30:20.820
I mean, it's very difficult to be a scientist today because nobody's paying you to be just
01:30:27.640
thinking. Nobody's really rewarding you. Nobody's promoting you based on that. So we've created this
01:30:34.400
very perverse set of incentives. And in some ways, honestly, I consider it a miracle that there are
01:30:39.260
still really good science being done. Most science being done, by the way, just sucks. I mean, if we're
01:30:43.300
going to be brutally honest, if you pull up PubMed and you look at every one of those hundred thousand
01:30:48.920
papers every month that makes their way on the PubMed, I think 90 to 95% of them are absolutely
01:30:56.140
useless. Serve absolutely no purpose to our civilization. Do not advance natural knowledge.
01:31:04.900
They increase the publication count of the person doing them, which is why they're doing them.
01:31:08.480
That's right. It's an economic tool of the journals and it's a promotional tool. So you don't
01:31:13.300
have any absolutely nefarious actors in the situation. You just have a system with such
01:31:18.120
perverse incentives that nothing good. Some of the predatory journals, but those are.
01:31:21.900
Yeah. Yeah. Yeah. Yeah. And I think a lot of the science is bad. I confess in range that I think my
01:31:26.800
own master's thesis was not good science and wouldn't replicate, but I didn't know, like I was rushed into
01:31:31.800
studying the specifics of Arctic plant physiology really quickly without learning what was actually
01:31:36.620
happening when I hit a button on the statistics program and how science has to be set up to make
01:31:41.240
conclusions. And I think that's kind of the norm for a lot of scientists. And I think there's 2005
01:31:46.020
paper by John Ioannidis that was titled why most published research is false that people kind of
01:31:50.200
wrote off. Now it looks like he's a genius, right? Oh, and now I hope I'm not saying something John
01:31:54.540
wouldn't want me to repeat, but I think John's been pretty vocal about this. Probably like seven or
01:31:58.660
eight years ago, I was having dinner with John and I said, John, I want to know bullshit answer on this.
01:32:03.320
What percentage of people who do science for a living, so they apply for grants, they get the money,
01:32:08.680
they do the thing. What percentage of those people shouldn't be doing that? Which doesn't
01:32:14.440
mean they can't work in a lab, but they can't be principal investigators. I mean, he said something
01:32:19.840
to the tune of 95. He's like 19 out of 20 people who basically for a living are in the business of
01:32:26.220
generating hypotheses, testing them experimentally and evaluating the results of those experiments.
01:32:31.520
That's the scientific method. 19 out of 20 people who do that can't do it and probably should not be
01:32:37.060
doing it. That's scary. But also I would guess that we don't want to try to narrow it down to
01:32:42.460
just the people that should be doing it because you'd have this purifying form of selection where
01:32:47.580
you have to like allow some failure. So this is kind of where I want to go with this thinking,
01:32:51.660
right? So why are we going down this tangent? So you've obviously written a lot about the importance
01:32:56.940
of even generalists within science. And you've given a couple of examples, which we should go into
01:33:01.600
about the hard problem that gets solved by somebody whose native scientific tongue is not
01:33:09.020
the one that is being addressed. So I want to talk about that, but I want to contrast it with this
01:33:15.380
other thing, which is I have this thesis that I harp on all the time, which is mostly my way of
01:33:21.680
communicating with myself to not get so upset at the lack of scientific insight in the world. And the
01:33:27.600
idea is genetics and evolution have never prepared us for science. So the scientific method is less
01:33:35.080
than 400 years old. Even the earliest signs of formal logic as a construct to describe the way we
01:33:41.680
think represents less than 0.1% of our genetic existence. So Atiyah, why would you ever get upset at
01:33:49.600
somebody who can't think logically? Why would you ever get upset when you pull up a story on Goop
01:33:55.840
that is written like the most insulting thing you've ever seen in your life with respect to
01:34:00.980
science? Why would you let that upset you, Peter? It's like you're expecting something that is
01:34:05.760
simply too much. And you might be assuming that the people writing for Goop are trying to get things
01:34:10.960
right. So that might be the assumption. That's part of the assumption. I would love to hear you hold
01:34:14.580
forth about Goop, to be honest. So I contrast this with there has to be some degree of rigidity and
01:34:21.780
formality in the training. I like to think of myself as a pretty good critic of science. I have
01:34:26.700
the ability to read papers and immediately, most of the time, figure out why these are total crap and
01:34:32.720
what all the biases are and all these other things. But to take any credit for that would be ridiculous.
01:34:37.860
I can't take any credit for that. That's simply because I was mentored by people and I went through
01:34:42.920
a formal type of training or informal type of training. Really, it wasn't formal and codified,
01:34:47.320
but it was informal. It's going to journal club. It's doing the experiments yourself,
01:34:52.300
putting something together, thinking you're slick and having people tell you,
01:34:55.700
hey, numbnuts, did you realize how many ways you screwed this up and how you've drawn the wrong
01:35:00.280
conclusion? So how do you balance that you have to go through that type of training with,
01:35:07.360
but sometimes you have to be an outsider? Yeah. And by the way, once you mentioned informal
01:35:11.560
training, I think we underestimate the importance of informal training and you have to kind of set up
01:35:16.220
cultures for it and things like that. So I have a master's degree in geological sciences and I got
01:35:21.620
a much better education in genetics writing a book than I did in a grad program. I wouldn't know
01:35:26.560
how to run like the equipment in the lab, but I basically kept like a statistician on retainer and
01:35:31.760
just to talk to me about a paper anytime. And that's an amazing way to learn. You're not just
01:35:36.060
being talked at, you have a specific question of why is this right? He's like, no, you can't use
01:35:39.220
this. And so it's an amazing way to have like informal learning. And you're right. I think the way to
01:35:44.340
balance that I think it's difficult because you're right, you do need some formal training in it.
01:35:48.160
Like in other words, the takeaway from your book is not that the person who's going to crack the
01:35:53.600
code on pancreatic cancer is currently working at an investment bank as a finance analyst who's
01:36:01.540
never taken a science course. That's not going to happen. Not even close. And I don't think you're
01:36:06.520
trying to suggest that, but I've heard people try to take your work and paraphrase it as,
01:36:11.160
oh, well, all these scientists working on cancer, you screw it, man. They're not going to figure
01:36:14.680
anything out. We need to, we need to go get the history majors to solve the cancer problem. And
01:36:18.760
I'm like, not a freaking chance without some modicum of scientific training.
01:36:23.800
Yeah. And I mean, I think the scientific community, I would say the tech community in particular
01:36:26.600
would do well to interact with historians. Like I think there are a lot of things they could learn.
01:36:30.200
Sometimes I feel like the Silicon Valley set maybe doesn't respect history quite enough or it'd be
01:36:34.280
useful for them, but that's a side point. My guess is that when people are saying that,
01:36:37.720
that just like go pick some person at random to do science, maybe they're taking that from
01:36:43.440
the chapter where I wrote partly about Innocentive, which was the VP of research and development at
01:36:49.660
Eli Lilly in the past. And this guy named Alf Bingham, who's that? I remember when I first
01:36:53.540
talked to him, he said, look, I'm an organic chemist. It doesn't have a carbon in it. I'm not
01:36:56.560
even supposed to play with it. Okay. I'm specialized. And I guess he realized at a certain point that
01:37:01.260
chemists at Lilly were getting so specialized that there were certain things they were great at,
01:37:04.340
but it also narrowed their view. So he talked a lot about this terminology in some of the business
01:37:08.820
literature, exploration versus exploitation. Exploration meaning essentially going and looking
01:37:13.040
for new ideas and solutions. Exploitation, once you find them, how do you make the most out of them?
01:37:17.240
Both of those incredibly important. And he said, basically the exploration phase is increasingly
01:37:22.080
found outside because people are so specialized. So they're just not covering as much ground.
01:37:26.680
And so he had this idea to just post online some of Lilly's problems in drug development. And at first
01:37:31.520
everyone was like, no way, proprietary information. He said, well, pick stuff. Well, nobody will know
01:37:35.260
what we're doing. And they said, who else is going to be able to solve this? So he posts them online
01:37:39.200
and like a third of them get solved. I remember one of his favorite memories was an attorney who solved
01:37:44.260
some important chemical synthesis project because he had worked on some tear gas copyright case or
01:37:51.000
something. And it reminded him of that. And so a third of those problems get solved, which is amazing.
01:37:58.220
And in those problems, it does tend to be, because they've selected for problems that have
01:38:02.280
stumped the specialist, right? So it does tend to be the more likely the problem is to get solved,
01:38:06.840
And I think my question on that to really double click on it is, did the generalist actually solve
01:38:11.620
the problem or did the generalist just come up with a clue that completely changed how the specialist
01:38:16.720
went about approaching it? Like in the case of that example, the attorney doesn't actually know how to
01:38:22.420
completely synthesize the molecule. What they're basically saying is, you guys are looking at it this way,
01:38:26.800
stop. Rotate 90 degrees over there and turn around. And I think the answer is over here,
01:38:32.880
to which case either a new set of specialists could do it. Is it sort of a bit of that hybrid?
01:38:37.720
Yeah. And actually, Innocent have evolved to where they give different... Now they help other
01:38:42.060
operations post their questions in a way that'll attract what they call solvers. And
01:38:46.420
there are different monetary rewards depending on what kind of contribution it is the person makes.
01:38:51.800
And sometimes he did get people sent in powders and stuff. They synthesize stuff on their own. Other
01:38:56.240
times it was much more like you're taking the wrong approach. And here's another thing to think about.
01:38:59.660
But they were still chemists that had to do this, right?
01:39:02.140
Not all of them. Not all of them. But there was a lot of that. Sometimes they'd be chemists from
01:39:05.800
some other area, but sometimes it was totally random people. But again, you're farming it out to the
01:39:09.880
whole world. People have... Not the whole world. I mean, most people don't know about Innocentive,
01:39:13.640
but a huge number of people. And I think he was surprised sometimes things would come from
01:39:18.380
people who worked with machinery but weren't really formally trained in it, but had a lot
01:39:24.440
of experience. And so I think sometimes there were true outsiders. But most of the problems don't get
01:39:30.080
to the Innocentive stage anyway. They're being handled by the specialists. And I wouldn't extrapolate
01:39:34.420
Innocentive to mean that specialists aren't incredibly important. I mean, my broad view of this is the
01:39:39.140
same as physicist Freeman Dyson where he gave this great speech where he said, we need birds and
01:39:43.160
frogs. The frogs are down in the mud looking at the granular details. The birds are up above. They
01:39:47.160
don't see the detail, but they're integrating the knowledge of the frogs. And he said, the world is
01:39:51.720
wide and deep. It'd be stupid to say one's better than the other. You need both for a healthy ecosystem.
01:39:56.140
His concern was we're telling everybody to be frogs. And so we're not having birds. And that's kind of
01:40:00.280
how I conceive of it. And I think the biggest impact would come from what Arturo Casadoval, who's this kind of
01:40:07.640
one of the prime characters of the last chapter, is trying to do, where adding range to people who
01:40:12.340
are within science already. Like these people are being formally trained. He's just backing up the
01:40:16.800
formal training instead of jumping right into kind of the reductionist, studying the body as a machine
01:40:22.460
sort of thing. It's like the initial classes in the program he's pioneering. And he's like one of the,
01:40:26.900
I think his H index, which is a measure of his productivity as a researcher, surpassed Einstein's
01:40:30.980
recently, which isn't fair because people publish a lot more now, as you alluded to for their careers,
01:40:34.780
but it still puts him in very rare company. And so he's starting people with how do we know what is true
01:40:40.100
and the anatomy of scientific errors and also how errors have sometimes led to breakthroughs. And so he's just
01:40:45.740
like backing up the training into these broader concepts and saying, you can learn the more specific
01:40:50.560
didactic stuff later, but if you don't learn the broader conceptual stuff, you never get it because
01:40:56.360
you're only going to get more and more and more specialized from here. So I think one way we can approach
01:40:59.960
this is just by backing up the training basically. Cause I don't think we have to worry about
01:41:04.360
people will learn the specialized stuff in their field just by doing it and being there,
01:41:08.420
but the other stuff, but that's what we kind of teach them and start them with. But the other
01:41:11.980
stuff like scientific thinking, how does it work? What constitutes evidence? They'll never get that
01:41:16.440
stuff if they don't get it early in training. Yeah. I sort of cite the examples you've given when I
01:41:20.980
get asked a question a lot, which is someone going to college who wants to go to medical school
01:41:25.900
saying, what is the best thing to study in college to which I don't know the answer, but my advice is
01:41:30.480
anything but pre-med. So you couldn't really do anything worse. And I'm sorry, because I know
01:41:34.380
there's somebody listening to this. I'm sure who's doing pre-med, who's going to go into medical
01:41:38.060
school. And my only take for you is, okay, I'm sorry that you're in pre-med right now, but make sure
01:41:43.580
you spend a lot of time doing non pre-med stuff in college. You still have the bandwidth to take other
01:41:48.480
classes. You should be doing so liberally, but you are better off being a history major who goes to
01:41:53.520
medical school than a biochem major who goes to medical school. In my opinion, I could be wrong,
01:41:58.260
but having seen enough people go through it, you're going to learn as much biochemistry as you're
01:42:02.140
going to need to learn when you get there, both interpersonally and frankly, in the breadth of
01:42:06.600
thinking, you'll be better off if you studied something else. I mean, a lot of Arturo's argument
01:42:10.260
too is I saw him make this argument talking about he went from Einstein to Johns Hopkins School of
01:42:15.780
Public Health because they're allowing him to start this new grad program. And I saw him on a panel
01:42:20.520
about the replication crisis in science, this problem with a lot of work basically not being
01:42:24.340
true. And the head editor of the New England Journal of Medicine said, you can't do that.
01:42:28.580
Training is already too long. And Arturo said, it's clearly not working. He said, I'm saying drop the
01:42:33.340
didactic stuff because it's not been working. I think he actually pointed out that the New England
01:42:36.860
Journal of Medicine had the highest retraction rate in some study also. But so I thought that was
01:42:41.360
interesting where he said a lot of that stuff is in one ear and out the other anyway, if it's really
01:42:45.380
didactic, people don't even know if they're going to need it or when they're going to need it.
01:42:48.420
And so I thought that was an interesting take that he said, you can just drop some of that other
01:42:52.060
stuff. But to your point about telling people not to do pre-med, when I was at Sports Illustrated,
01:42:57.300
not so much anymore, but when I was there, I would get asked by a young aspiring journalist,
01:43:01.780
what should I do if I want to work as a sports writer? Should I major in English or journalism?
01:43:06.240
And my first instinct was to say journalism. If you know what you want to do, get a head start.
01:43:10.900
Second instinct, English. And then if I thought about it, I'd be like, well, I majored in geology and
01:43:14.420
astronomy, so I have no idea what to tell you. But stats course, biology course,
01:43:18.200
never hurt anyone. You should do one of those because you'll learn the job by doing the job.
01:43:22.740
And that's the only way you'll learn the job. That is the challenge of giving advice, isn't it?
01:43:26.200
Because I don't feel this way at all anymore. I'm totally comfortable with my nonlinear path to
01:43:31.200
doing what I do. But I spent a great deal of time frustrated that I couldn't figure out sooner in
01:43:38.100
life what I wanted to be when I grew up. And I thought of all the time squandered. But again,
01:43:43.020
that was through the paradigm of, you only had one to two 10,000 hour windows. You didn't take
01:43:49.660
them. You spent them doing something you will never do again. I had my 10,000 hour shot and I
01:43:53.880
put it in the wrong thing. And now I never do it again. But I think that speaks to probably the
01:43:58.940
insights of your book, which is you're discounting a bunch of things you learned in doing that.
01:44:03.840
And also, sorry, I didn't mean to interrupt you. Were you going to? No, no, no. Yeah. And also I
01:44:07.000
think your insight into yourself, your skills and interests in the world are constrained by your
01:44:11.920
roster of previous experiences. As Herminia Ibarra, who studies how people find what's called match
01:44:16.620
quality, the degree of fit between their interests and abilities in the work that they do, which turns
01:44:20.440
out to be really important for how likely they are to burn out, for their performance, for all these
01:44:25.160
sorts of things. And we really underestimate it. She studies basically how people seek this out in
01:44:30.320
transition careers. And she said, we learn who we are in practice, not in theory, which means
01:44:35.820
there's this kind of cultural idea and lots of career gurus and personality quizzes that kind of
01:44:41.960
seek to convince you that you can just introspect and know what you should do putting in that time.
01:44:46.020
But in fact, the way we learn about what we want to do is we have to do stuff, act and then think.
01:44:50.680
You have to do stuff and then reflect on it. And that's the only way you figure it out. And match
01:44:55.000
quality seems to be so important that spending some time in that experimentation is worth it.
01:45:00.140
So one of the, that I think is sort of representative of that, this economist who found a natural
01:45:04.980
experiment in the higher ed systems of England and Scotland, where in the period he studied,
01:45:08.980
students in England had to pick a specialty in their mid-teen years to apply for a certain
01:45:12.900
program in college. The Scottish students could keep sampling throughout university. And he said,
01:45:17.000
who wins the trade-off? Otherwise, the systems were very similar. Who wins the earlier late
01:45:20.700
specializers? And what he found was the early specializers do in fact jump out to an income lead
01:45:25.040
because they have more domain-specific skills. But the late specializers sample more things.
01:45:30.020
And when they do pick, they have better match quality. And so they have higher growth rates.
01:45:34.220
So by year six out, they fly by the early specializers. Meanwhile, the early specializers-
01:45:40.340
What about when you look at things that probably matter even more, such as happiness and
01:45:44.160
He was only looking at finance and career switching. So, because he was looking at huge numbers of
01:45:47.940
people. But we can talk about fulfillment in a sec. So the early specializers then start
01:45:51.640
leaving their career tracks in much higher numbers, even though they have much more
01:45:54.160
disincentive from doing so. They're made to pick so early that they more often make a wrong choice.
01:45:58.640
So the return to match quality was higher than the return to getting a head start in domain-specific
01:46:03.940
skills. The Dark Horse project, which I wanted to get around to anyway, has to do with fulfillment
01:46:08.460
because I think you should tell more of your story because it sounded really interesting and
01:46:12.120
I want to hear more of it. But that project, the dependent variable was fulfillment and it
01:46:17.840
Yeah. Well, before we started the podcast, I said there's this thing I've always tried to
01:46:21.300
explain when I've told my story to high school kids or something like that. It doesn't really
01:46:26.380
make sense, which is growing up, all of my energy went into boxing and martial arts and
01:46:31.320
I didn't do anything in school. I was super mediocre. And then I had this awesome teacher
01:46:37.500
who, when I was in grade 12, in Canada, you say grade 12, not 12th grade. Sounds stupid.
01:46:44.080
So weird. I can't believe we can even get along with you guys.
01:46:45.780
It's hard that we can even have a discussion. And he called me in one morning and he said,
01:46:49.040
hey, I heard you're not applying to university and stuff. And I said, that's right.
01:46:52.220
And he certainly didn't bust my chops. In fact, I wrote about him after he died and how amazing
01:46:57.260
it was that he just knew what to say. He knew the right thing to say at the right time, which was,
01:47:01.340
hey, I totally get it. When I was your age, all I wanted to do is play in the NHL. And it was the
01:47:04.900
only thing that mattered to me. And you really ought to, don't let anybody tell you that your
01:47:08.780
dream of being middleweight champion in the world is a dumb idea. It's not. But he said, but it was
01:47:13.200
almost like a Steve Jobs moment. Like one more thing. I think you have a gift for mathematics and
01:47:18.740
you should at least entertain the idea that maybe that's your calling is more in terms of math than
01:47:24.660
it is in fighting. And I remember that day as clear as, I mean, that's so long ago. It's more
01:47:29.900
than half my life ago was that moment, but it did change the course of my life completely. And then I
01:47:35.140
did come back to high school to finish and did better than anybody expected I could ever do. And
01:47:40.240
I've always assumed the reason I was able to do that is I simply took the work ethic of exercising
01:47:46.800
six hours a day, which was sort of what I did in high school. I was, I would run five to 13 miles
01:47:51.720
every morning, 400 pushups before bed every night. And everything in between was training around that.
01:47:56.620
And I just applied that to calculus, algebra, physics, geometry, et cetera. So that sort of gets
01:48:01.720
into the Duckworth grit stuff. The question I guess I have in that is, had I taken the grit of age 13 to 18
01:48:09.540
and basically with no other cognitive capacity turned it into then doing well in school?
01:48:15.480
I definitely wouldn't say no other cognitive capacity because, well, I think those things
01:48:20.080
take a different certain cognitive capacity, that kind of discipline. But clearly the teacher
01:48:23.900
recognized something in you that you did not recognize in yourself. It didn't just pick you
01:48:27.640
out randomly. And I assumed. Well, especially because I wasn't even the top student in mathematics
01:48:31.380
at the time. I wasn't even near the top. So yeah. So obviously you saw something that you didn't
01:48:36.200
yourself see. And so it seems to me like you had this training, whether that was something that
01:48:40.400
was part of who you are naturally or something that motivated you that you could take that and
01:48:44.700
transfer that to then something that had better match quality for you. And so it's a combination
01:48:48.420
of you using certain skills and approaches that you had learned and somebody helping you find
01:48:52.500
better match quality, basically. I think that's like an explosive combination in a good way.
01:48:57.840
But it is interesting. I wonder what he saw because he was right. But did you have any inkling that that
01:49:03.260
was the case at the time? Or was that total news to you that he thought you might have math?
01:49:06.680
No. In fact, I found math incredibly frustrating because it wasn't something you could BS your way
01:49:11.880
through. At least in English class, I remember this well because I'm actually still very close
01:49:16.140
to my English teacher from high school. I always managed to find a way to weasel through by writing
01:49:21.060
every essay I wrote was on Muhammad Ali or Mike Tyson or Marvin Hagler or Jimi Hendrix. I basically
01:49:27.260
screwed my way through English by always figuring out a way to read a book that I was interested in
01:49:32.500
and figuring out a way to read. But you couldn't do that in math. You sort of had to do it. So
01:49:36.460
what I remember is that math frustrated me more than anything. But I wish Woody was still alive
01:49:41.540
for many reasons. But one of them being, I wish I could ask him why he said that.
01:49:45.820
Yeah. No, it's curious. I mean, and I think a lot of people find math more frustrating in English
01:49:49.760
class. It's like English class is more subjective and you can kind of get through even if you don't,
01:49:54.160
a lot of people, even if you don't know what you're doing. But that is, that is interesting. I wonder
01:49:57.380
what he saw. And I think that's the reason I said, I think it resonates with the Dark Horse project,
01:50:01.920
which was this project by these two Harvard researchers to sort of figure out how people
01:50:06.360
who find fulfillment in their work go about it in a wide range of careers. Essentially,
01:50:10.260
there was a huge variety. But most of the people did not stick on their first sort of dream,
01:50:15.700
basically. There were some, but it was a small minority. Most of them had this, they actually
01:50:19.880
called it the Dark Horse project because people would come in and say, well, don't tell anybody to
01:50:23.580
do what I did because I started this other thing and then I, something else came up or something
01:50:28.360
random happened or I realized there wasn't what I want to do. So I had to start my own thing.
01:50:32.360
So they also felt sort of sheepish about their non-linear path to get there.
01:50:36.740
Yeah. And they saw themselves as having gotten lucky and come out of nowhere, which you do have
01:50:39.320
to get lucky. Luck is important, but they all saw themselves as having come out of nowhere,
01:50:43.020
which is why they called it the Dark Horse project. What they kind of had in common was this,
01:50:46.980
they would sort of respond instead of sticking to like an ironclad long-term plan,
01:50:51.440
they would respond to their lived experience by zigging and zagging and kind of finding what they
01:50:54.740
were good at, whether that was someone helping them figure that out, which I think is often the case for a
01:50:59.940
younger person or them being older and maturing and sort of realizing that. And it sounds like that
01:51:04.240
kind of happened to you in some way. You view yourself as coming out of nowhere because you had
01:51:08.580
a talent and also some transferable skills that could come together in a way that you hadn't
01:51:12.920
conceived before. And it worked really well. So I think you'd be kind of the type for the Dark Horse
01:51:18.260
I mean, to take something you said a moment ago and couple it to this. So let's say we fast forward
01:51:24.180
whatever 18 years and your son says, dad, I don't want to go to college. I'm going to learn a bunch
01:51:28.080
of stuff that A, I don't need to learn because I could teach it on my own. I'm going to get a degree
01:51:33.280
in something that doesn't necessarily imply what I'm going to do with myself thereafter. The letters
01:51:40.460
don't really matter after my name. And by the way, notwithstanding the fact that maybe by the time
01:51:45.480
our kids are going to college, the debt that they'd incur to do so is itself more debilitating
01:51:51.600
than anything else. So can you make a case that one does not need formal education at that level
01:51:59.200
to go far? I mean, notwithstanding the fact that sometimes you need it from a professional
01:52:02.420
standpoint, like you can't become a lawyer without going to school. I don't see that changing and
01:52:06.980
At least in California, you just have to pass the bar.
01:52:08.740
That's a great point. You can't become a doctor, I guess, without going to school. And
01:52:12.500
so does this change the way you think about higher education?
01:52:16.200
Yeah. And gosh, I don't even know where to start with this question. I hope that college
01:52:19.540
looks different 18 years from now than it does now, because if we keep ramping up people's debt,
01:52:23.220
then we will make sure that they fall prey to the sunk cost fallacy, where the more you invest in
01:52:27.840
something, one of my favorite writers, Maria Konnikova, wrote a book about con men.
01:52:31.940
And one of their strategies is they start with asking for small things.
01:52:37.500
Oh, no, no, not con men. No, no. Con men, playing confidence games. Yeah,
01:52:42.180
the book's called The Confidence Game. And she's a psychology PhD and a great writer. And
01:52:47.160
she notes that they'll start with these small, lots of small asks, because the more you invest,
01:52:52.360
the more likely you are to fall prey to the sunk cost fallacy of then saying like, well,
01:52:55.180
I've already put some in, so I should keep going. Even when to an outsider, it's like clear that it's
01:52:58.580
a disaster. And I think the more debt we saddle people with, like that study we were just talking
01:53:03.680
about with the higher ed systems in England and Scotland, the English students who specialized
01:53:06.800
earlier have more disincentive from quitting, even though they should. When they do quit,
01:53:10.720
their growth rates are then higher because they're quitting in response to information
01:53:13.940
about themselves that they've learned. And I think the more time and debt we saddle people
01:53:19.280
with, the more we make sure they will not respond to match quality information. And instead,
01:53:24.600
Yeah, you blunt their receptivity to the signal.
01:53:26.620
That's right. And I think we want to, Steve Levitt, the economics economist, did this interesting
01:53:30.640
study where he had people flip a coin to determine major life decisions. And the most commonly asked
01:53:35.080
question was, should I quit my job? And what he found was the people who flipped, I think it was
01:53:39.220
heads and changed their job were better off when he checked in with them later. And so I think you
01:53:43.580
want like as little friction as possible to people job changing. In fact, when I was watching one of
01:53:47.920
the Democratic primary debates recently, and people were talking about universal healthcare,
01:53:52.380
I would think one of the advantages might be that it would lower friction to job changing because
01:53:56.080
you're not as worried about, so that maybe people can shuffle around more and have better match
01:53:59.680
quality. So I think something has to be done about the debt situation. I think there's plenty of
01:54:04.740
evidence that for a lot of students- So the economist Brian Kaplan wrote a book called
01:54:08.640
The Case Against Education. I certainly don't agree with- And it's higher education specifically.
01:54:12.540
I certainly don't agree with everything in the book, but I think it's provocative and a rigorous
01:54:16.060
take. And his argument- So we know that some part of college education is signaling to the job world
01:54:22.060
that is not about anything that you've learned. It's just about, I am smart enough and-
01:54:27.340
It's like the minor leagues for the job world. So we're doing them a favor because they don't
01:54:30.440
have to be good scouts. And basically what he was saying is nobody says that either signaling
01:54:37.660
or learning is all of the effect of college. But his argument was that he thinks signaling is like
01:54:41.520
80% of it, whereas other people would say, oh, maybe it's 20%. So he thinks most of it is just
01:54:45.820
you need this credential to signal to the work world that I'm okay. And I don't know if he's right
01:54:51.160
about how much it is, but I think it's probably more than people intuit because research seems to
01:54:56.260
suggest that it doesn't change people as much as we might think in some ways. What I do think is
01:55:00.960
important about it though, is that it does give that kind of sampling ability. Like I didn't know
01:55:04.840
about it. So the Scottish students in that study also much more often the late specializers end up
01:55:09.940
studying something that wasn't offered in their high school because they didn't know about it. I
01:55:13.400
didn't know about the stuff I studied until I got to college. And so without it, I would want there
01:55:19.140
to be some other mechanism for sampling. But I think that kind of communication technology that we have
01:55:25.240
now and the internet may, if we use it smartly, it can expose you to a lot more stuff. And I think
01:55:30.720
there's huge potential of online courses. I love some of these online courses. So I do think while I
01:55:37.620
would want him to be able to have a sampling period, my kid, I think I don't know that the same kind of
01:55:42.500
college model that we have now will be the answer. And I think there are other things that could expose
01:55:46.480
him to more other things. But if society forces the signaling to continue, then what can you do?
01:55:51.540
Then it's just like, you have to pay your dues because you have to pay your dues. The way I
01:55:54.920
see my role as a parent, we mentioned Angela Duckworth, by the way, I should mention the
01:55:58.760
week that my book came out, I subscribed to her newsletter. Her newsletter was titled Summer is
01:56:02.660
for Sampling. And she said, kids shouldn't be too gritty until they figure out what to be gritty in.
01:56:07.520
And she says, it took me a decade of trying stuff to figure out. So it really speaks to a broader
01:56:12.420
point here, which is a lot of these insights that we sort of latch onto are slightly out of context.
01:56:19.020
Yeah, definitely. Definitely. And I mean, so now if her point is, you should be gritty when you
01:56:24.020
should be gritty. I'm totally on board with that. I view my roles, I write a little bit in that section
01:56:29.060
about grit, about something I should have written more about, about the way the army adjusted when
01:56:33.740
they realized in an industrial economy, and they had this strict up or out structure, it was great
01:56:37.460
because you did want to be specialized because work next year did look like work last year. And there
01:56:42.700
were huge barriers to lateral mobility, but knowledge economy comes along. And now there's tons of
01:56:46.700
lateral mobility for people who can engage in knowledge creation and creative problem solving.
01:56:51.100
So their highest potential officers started quitting if they didn't have any agency over
01:56:56.040
their career matching. And so first they tried to throw money at people to retain them and people
01:57:00.440
were going to stay, took it. People were going to leave left anyway, half a billion dollars of
01:57:03.940
taxpayer money down the drain. Then they started programs like one they call talent-based branching,
01:57:08.580
where instead of saying, here's your career track, go up or out, they say, we're going to pair you with
01:57:12.160
a coach and try this one career track and reflect on how it fits you. And then try these other two
01:57:16.940
and these other two and we'll triangulate a better fit for you. And that improved retention more than
01:57:20.480
throwing money at people. They've basically built in a match quality sampling system. And so maybe we
01:57:25.460
could do stuff. That's how, frankly, how I view right now my parenting role as being the coach in
01:57:29.740
the math talent-based branching system for my kid. Facilitate, help him know that a lot of things are
01:57:34.160
available and get the maximum amount of signal about himself from each one. And I think there are ways
01:57:38.680
that that can be done possibly more effectively and a lot more cheaply than the formal education
01:57:45.700
structure. How do you know how long to push? So give you two examples with my daughter. And I feel
01:57:50.760
so bad sometimes telling these stories about her because one day she'll listen to this and she'll
01:57:54.300
be like, dad, I can't believe you embarrassed me. But when she was five, she said, I want to play the
01:57:58.920
drums. And we've had lots of parents who have interacted with us who said, are you crazy? How did you
01:58:03.880
listen to her? But we were like, oh, we just did. So we got her like a set of cheapo little toy drums
0.98
01:58:07.640
just to see if would she actually do anything. And she did. She wouldn't stop wailing on them.
0.99
01:58:11.620
But no, she was four when she said that. Then when she was five, she said, no, I really want to keep
01:58:14.940
playing. So I was like, okay, fine. So we got a drum teacher, got her a real set of drums and away
01:58:20.520
she went. And here she is now. She's 11. She still drums. She loves it. She's, I mean, she's really
01:58:26.520
good. I think I can say that without too much bias, just objectively based on what her teacher tells
01:58:30.640
me, which is like, she drums better than most anyone. And she's only 11 and we never pushed her.
01:58:35.680
Right. So it was just, she just wanted to do this. There was one time when she kind of wanted to quit
01:58:41.060
when she was about seven. And we talked to her teacher and said, Hey, let's spend way more time
01:58:48.860
just letting her play Taylor Swift songs than doing scales for a while and see what happens. And then
01:58:54.600
that was great. Like it all came back into the mix year ago. She starts taking tennis lessons.
01:58:59.000
I think her tennis teacher is the most awesome guy. He's like this young Russian kid. He's so fun. He's
01:59:05.240
so smart. I've, I've watched them. I mean, he's just has a beautiful way of explaining things to
01:59:11.000
her. She never feels bad. Like he never hammers her, but he's strict. If she's screwing around,
01:59:17.620
he tells her, she's like, I don't want to play tennis anymore. And I'm like, Olivia, are you
01:59:22.500
freaking crazy? Do you know what I'd give to have played tennis when I was a kid? And I don't get into
01:59:27.100
the sob story of like, we didn't have the opportunity for private tennis lessons or whatever,
01:59:30.580
but it's more the tennis is such a beautiful sport. You will be able to play this forever.
01:59:36.340
How can you not want this? And I'm really torn. Do I push her to continue taking lessons? And I'm
01:59:43.180
not saying like you have to go and even compete. It's just sit here and play tennis for two hours
01:59:47.840
a week. You and mom play. It's fun. Why wouldn't you want to do this? Or do I just say, well, she only
01:59:54.480
wants to play basketball, which is the only sport she wants to play right now. Should I just, I don't
01:59:57.640
know if this is a great example, but I think you get the point, right? It's like, there's a part of
02:00:00.420
me that thinks it's really good for her to keep playing tennis. Yeah. Yeah. And she's crazy to
1.00
02:00:04.480
stop. Obviously you're saying she'll regret it. It sounds like it. That's my potentially stupid
02:00:08.940
fear, which is you're going to be 51 day and you're not going to be playing basketball because
02:00:13.360
nobody's playing. No 50 year old woman is running around playing pickup basketball, but you will still
1.00
02:00:18.680
play tennis. So why wouldn't you continue to learn this now? Well, you have this critical window in
02:00:23.660
which you could get good at this sport. Yeah. And she could play tennis at startup at 50
1.00
02:00:27.620
just wouldn't be as good at it. Exactly. Yeah. And you're oriented toward achievement. So she might
02:00:31.860
be a great drummer and a crap tennis player. She starts at 50. She might still like tennis though.
02:00:35.660
Yes. And I'm trying to balance the, yes, I think that's the part of it. I can't let go of this idea
02:00:40.420
that I'm not great at anything. It would be really cool if my kids had the potential to be great at
02:00:46.760
something world-class. Like, wouldn't it be cool if she could be a world-class drummer one day? I have no
02:00:51.820
delusion. She won't just the interest or even the talent to be a world-class tennis player,
0.78
02:00:56.480
but I still think, why wouldn't you? You have this wind, I think I'm still stuck to this idea
02:01:01.060
that there's a window in which you can assimilate skill, be it language, music, sports, that to go
02:01:08.280
a little further. If she said, I don't know, anyway, that's sort of. And when she's younger,
02:01:12.280
also you have more time to put into it and you're a lot less concerned about making mistakes. So you'll
02:01:15.940
throw yourself in and practice in a way that you probably won't when you're older in most things.
02:01:20.000
I mean, that's a great question. It sounds like in drums, you found a way to sort of,
02:01:23.860
when she was saying, I don't really want to do it anymore to keep her foot in by sort of changing
02:01:27.060
what she was doing. Right. And it was just this one little audible called on the line of scrimmage,
02:01:30.820
everything was fine. But also it would have never even occurred to me to put a kid in drums. Like
02:01:35.200
this was 100% her insisting on it. And there was no resistance from us. I was like, great. But if
02:01:40.860
she'd said piano, violin, fill in the blank, we would have been equally interested in letting her pursue
02:01:46.040
that. So maybe it just comes back to this broader issue of, is there an age at which parents
02:01:51.520
should force some of the sampling? Is there an age at which parents say enough is enough? You've
02:01:57.500
sampled enough. If you don't want to play tennis anymore, don't play tennis. I should make clear,
02:02:01.320
I don't want to prescribe diversification any more than I want to prescribe specialization. Right. And
02:02:06.680
this gets to something I mentioned before, which is I think we tell the tiger and the Mozart stories a
02:02:10.520
little wrong. Yeah. Let's do that story. Okay. So tiger said in 2000, his father never asked him to play
02:02:16.120
golf. So his father did put a putter in his hand when he was seven months old, but he wasn't attempting to make
02:02:19.680
him a golfer. He was just giving it to him as a toy. And he responded. So he said in 2000, my father
02:02:25.500
never once asked me to play golf. It was always me asking him. It's the child's desire to play,
02:02:30.860
not the parent's desire to have the child play that matters. That resonates with the work of this woman,
02:02:35.080
Ellen Winner, who's maybe the world's authority on, on prodigies of that nature, that they're usually
0.98
02:02:41.000
driving their parents crazy, not the reverse. And that there's not really. Yeah. I mean, Wayne Gretzky is a
02:02:46.680
great example of that. You listen to these interviews with his parents, like they couldn't
02:02:49.940
get this kid to come in for dinner. And what Ellen Winner, I think she alludes to some research.
1.00
02:02:54.560
I don't think this research was exactly hers, but it's really a problem when someone's parents,
02:02:59.560
if they're low socioeconomic status and they have a prodigy and the person has this incredible drive,
02:03:04.300
a master, whatever it is they're doing. And the parent can't accommodate that because it really is
02:03:07.960
hard for the parents. Obviously tiger's father responded to his very unusual display of interest
02:03:13.420
and prowess. Mozart, probably the second most famous example. Tell people just what the,
02:03:18.180
what's the mythology around Mozart that, Oh, that his father basically was like Tiger
02:03:22.620
Wood's father, except for music that he started a very young age. Shoved a violin into the crib and.
02:03:26.680
Yeah, exactly. And so I was going through these letters and one that I remember really well
02:03:31.760
about Mozart's early life was a musician who would come over to play with Mozart's father,
02:03:35.300
who was a musician. And he recalls young Mozart coming in with the group of adults and saying,
02:03:42.380
I want to play the second violin part. And Mozart's father says, go away. You haven't
02:03:47.600
any lessons. You obviously can't play violin. And then the letter writer, his name was Andreas
02:03:53.140
something. I can't remember the last name says little Wolfgang started crying. And so I said,
02:03:58.320
okay, I'll go play with him in the other room. And his father says, but play quietly. Don't disturb
02:04:01.900
us. Next thing you know, they hear the second violin part coming from the other room. And so they
02:04:05.440
walk in and look and young Wolfgang Mozart's playing the second violin part with made up fingering
02:04:11.100
because nobody's taught him the fingering. And then the letter, this part I remember verbatim,
02:04:14.660
he says, young Wolfgang was emboldened by our applause to insist that he could also play the
02:04:19.100
first violin part. And so then he goes and does that. And that's when his father says, holy crap.
02:04:23.580
Yeah. And responds to it. So neither of those cases were they like manufactured the way we tell
02:04:28.180
that story. So I don't think we should be scared about missing a tiger or Mozart because the best way
02:04:32.480
to find one of those people is probably still to expose them to a bunch of things and see if something
02:04:36.580
lights their fire that way. I mean, I think of Mozart. That's a great point. That's a great point.
02:04:40.780
Yeah. I think those, I'm sure there's a lot of those people who never got exposed to the thing
02:04:44.260
that would have ignited what Ellen Winner calls that rage to master. And most people, you're not
02:04:49.080
gonna have a lot of tigers and Mozarts no matter what. And obviously those are exceptions. But I think
02:04:52.280
that's important to keep in mind. To go back to when do you allow your kid to quit? This is something
02:04:57.040
I've seen Angela Duckworth has tried to respond to a number of times. It's very difficult. She'll say things
02:05:01.160
like, don't quit on a bad day, which I think is sensible. But also, should you quit on a good day?
02:05:07.160
It's kind of hard to know what is the calculus for when you should quit. Like if you're having tons
02:05:11.400
of bad days, maybe you should quit on a bad day. And Levitt and Dubner have written about this,
02:05:15.980
right? I think it's in one of their, maybe their third book. Well, Levitt is always saying my best
02:05:20.000
thing is I know when to quit. Like everything, like fields of study, projects, whatever. Yeah. By the way,
02:05:24.960
as a funny aside, you know, Steve has tried very hard to get me to take up golf.
02:05:28.660
No, really? Yeah. So he's a very good golfer. A lot of people don't know how good a golfer Steve
02:05:33.220
is. Incredible. And he's convinced that taking sort of a freakonomics approach to golf, you could
02:05:39.640
take a novice and make them really good in a short period of time. We've had very serious discussions
02:05:44.980
about if I would give him one year, he could turn me into a really good golfer as someone who's never
02:05:50.580
even touched a golf club. I don't know if that's true, but I'm curious enough that I'd love to try it
02:05:55.480
if I had the time. Because when he's explained to me the logic behind it, like how many steps you can
02:06:01.920
shortcut if you're purely optimizing around this thing and how he's figured out a bunch of these
02:06:07.240
hacks, I'm like, oh, it's kind of fun. It's not going to happen with me, I don't think. But
0.99
02:06:10.740
yeah, probably don't have time to do that. But if you did take him up on that, like that guy we
02:06:13.760
talked about earlier, Dan McLaughlin, who dropped his job to try to become a pro.
02:06:19.060
I think he got better. So he was getting way better at first, like anything, the learning
02:06:24.080
curve is. But I think how quickly he got better, and he had never golfed before ever, was surprising
02:06:29.500
to most people, how quickly he got better early on. And so I think doing that plus, I mean, he was
02:06:35.120
practicing, that was like his full-time job for the time. But if you did that for a year, plus
02:06:39.780
whatever hacks he's talking about, I bet you'd pass most of the amateur golfers out there. Because
02:06:44.160
most of them are just going and like swatting and it's like stress relief. They're not even really
02:06:46.880
trying to get better a lot of times. But I bet you'd surprise yourself with how good you'd get,
02:06:51.820
but I'm not a huge golf fan. I'm putting all of that energy into the things that I'm currently
02:06:56.540
doing. But this idea of quitting, it is really an underappreciated thing, isn't it? Because
02:07:01.320
sometimes it's time. It really comes down to time and exposure, and that's the most valuable
02:07:06.000
resource we have. But the when to do it is still the million-dollar question.
02:07:11.000
Totally. I mean, I think that's why I like this model of talent-based branching that the Army
02:07:14.800
used so much because they pair someone with a coach to help them make that decision. And it's still
02:07:18.340
not a science. And I also like they call it talent-based branching because basically it's
02:07:22.620
coached quitting, but they use a different term so it doesn't sound bad. But I don't know what's
02:07:27.700
perfect. I mean, I think someone, a mother asked me recently, said her son is really good at violin
02:07:32.380
and now he just wants to quit. And I think he just wants to play tennis. And she was saying,
02:07:36.580
but he's so good and I know he'll love it when he's older. And the best thing I could think of was
02:07:40.940
try to help him keep a foot in. Whether that's playing Taylor Swift songs or whatever, maybe
02:07:46.080
he just needs to back off and try something else for a while. Can you keep a foot in that pool so
02:07:50.540
that he doesn't totally detach from it and when he feels regenerated or whatever, can go back to it.
02:07:55.540
We know that progress comes from alternating stress and rest and things like that. So maybe
02:08:00.120
they just need a break or maybe they need to try some other type of training. I think that's
02:08:03.040
undervalued. If someone wants to quit and say, oh, either you have to stick with it or quit.
02:08:07.400
But the approach you took was, let's try varying what you're doing. I think that's incredibly
02:08:12.320
undervalued. We act as if it's a binary choice instead of why don't we see what else this area
02:08:17.600
has to offer? Maybe you just need to get on a different track. And again, I think that's the
02:08:21.280
brilliance of good coaches is they help personalize that environment so that the person continues to
02:08:25.460
be interested and continues to progress. And so the first thing I would try is varying up what
02:08:29.860
they're actually doing. And if they really want to quit, I'd say maybe keep a foot in if you can for a
02:08:33.920
little while. But then ultimately, if they really want to quit, then it defeats the purpose. If some
02:08:38.460
aspiration of life is to find happiness, then yeah. Yeah. And make it. And if they want to come
02:08:43.780
back, maybe they just needed a break, keep it available if possible. But if they quit and they
02:08:47.320
don't regret it, then what are you going to do? The proof's in the pudding. There are a couple other
02:08:50.940
stories in range that I wanted to ask you about. One of them is the story about the space shuttle
02:08:56.680
Challenger. I'll let you tell the story and then I'll bring my question to it.
02:09:00.860
I don't even know how to tell this story quickly. I'll set the stage. Everybody knows what happened.
02:09:05.500
Let's assume everybody knows the following. January 1986, space shuttle Challenger is scheduled
02:09:11.420
to launch, happens to be the first time there's a civilian on board. It also happens to be the first
02:09:16.100
time it's ever launched on a day that's that cold. And everybody knows what happened, which is
02:09:21.120
whatever, 73 seconds after liftoff, the O-ring failed to contain one of the liquid fuels. I can't
02:09:29.320
remember if it was liquid oxygen, but basically there was a spark, an explosion, and the rest is
02:09:34.760
history. You write about, one, the decision to launch that day. Two, the challenges of figuring
02:09:43.900
out what was the cause of that. Talk about both of those, especially the former, actually. And then
02:09:51.540
What I focused on was this emergency conference call the night before the launch when the weather
02:09:57.660
report came in that it was going to be an unusually cold day in Florida. And so engineers at Morton
02:10:04.080
Thiokol, which was the rocket booster contractor, and NASA, they get on this big conference call in
02:10:09.160
three different locations, a group of engineers, and they say, what should we do? Is this a problem?
02:10:13.420
Should we worry about it? The shuttle was supposed to be cleared for cool temperatures, but nobody
02:10:17.660
really knew because they had never launched below 53 degrees. And they were concerned.
02:10:22.120
As an aside, by the way, that O-ring was from the Apollo program. That's a great example of
1.00
02:10:26.620
engineering sort of shortcut, which is they never actually redesigned the O-rings for the shuttle.
02:10:32.600
They literally just took the O-rings from the Apollo project, which had a different spec,
02:10:38.220
Maybe I should describe what O-rings are a little bit. It's like, it's a strip of rubber that runs along.
02:10:42.120
If you can picture the rocket booster, you know, it looks like a missile attached to the shuttle.
02:10:45.360
So the O-rings, it's put together in different vertical segments, and the O-rings run along
02:10:50.000
the perimeter of the missile-like rocket booster and seal the joints between pieces. And they have
02:10:55.620
to stay sealed so that they block the rocket fuel coming down the booster from shooting outside,
02:11:00.220
essentially. And there was concern that the rubber of the O-ring launched. There were forces that
02:11:05.620
moved the O-ring, that moved the metal pieces that were being sealed apart. And the O-ring rubber had
02:11:10.400
to expand immediately to maintain contact so that fuel didn't come shooting past. And the concern
02:11:15.940
was that the rubber would harden a little when it was cold. And so it wouldn't expand quite as quickly.
02:11:20.660
And so some rocket fuel would basically shoot through the wall of the booster. And that is
02:11:25.980
exactly what happened. And the question was that they were trying to answer is, should we be worried?
02:11:31.480
Because twice before, they had had cases where they saw soot on the wrong side of the O-ring,
02:11:38.860
which meant rocket fuel had gotten past it, but it wasn't catastrophic. One of those was when they
02:11:43.980
launched at 53 degrees, which was the coolest temperature they'd launched at. One was at like
02:11:48.480
75 degrees, which was one of the warmest temperatures they had launched at. And so-
02:11:53.000
And on this day, it was like 30-something, right? It was like 38 or something like that?
02:11:56.580
They were looking at it that it was going to be like 40, but it ended up being colder than they
02:11:59.600
expected even. And I think in retrospect, some of the temperatures of actual components were even
02:12:04.020
colder. There was like ice on there. So it ended up being colder than anybody expected anyway.
02:12:07.960
But their question was, in these temperatures, will the O-ring work or not, basically? And the fact
02:12:12.520
was that they didn't really... There were only two cases of this so-called blow-by when the rocket
02:12:16.600
fuel goes past. Again, one at the coolest temperature, one at one of the warmest temperatures. And the whole
02:12:22.020
shuttle was thought by the project manager to be cleared for lower temperatures anyway.
02:12:26.580
And so all of a sudden, they're having this last-minute meeting where they're saying,
02:12:29.100
like, how do O-rings work and when do they work? And the only real... They didn't have enough data
02:12:34.000
to answer the question. And one of the engineers was saying, we shouldn't do this because I inspected
02:12:39.700
the joints. And in the 53-degree day, there was lots of black soot behind the O-ring. So that means a
02:12:45.900
lot of gas got by and we're lucky it came back. And the 75-degree day, something else wants to happen
02:12:50.660
because only a little bit got past. I don't know what happened, but only a little got past.
02:12:54.220
And so we go colder. So he said, they asked him to quantify this. So what's the relationship between
02:12:59.520
temperature and gas blow-by? And he said, I don't know. I can't quantify it. All I know is colder is
02:13:05.520
away from goodness. That's how he put it. And they kept saying, quantify it, quantify it, quantify it.
02:13:10.180
He said, I can't. I've got photographs. That's it. And I think they're telling a story. And the fact that he
02:13:14.900
couldn't quantify it meant that essentially it was deemed an admissible evidence, basically, because they
02:13:19.680
couldn't quantify what the problem was. And so he made the decision to launch. The rest is history.
02:13:25.380
So the story is tragic on so many levels because it would almost be easier to accept a disaster like
02:13:31.560
that if nobody had seen what could have been done. That's what makes it so painful. But on a second
02:13:37.640
reading, what makes it even more painful is the way the questions are being asked, which is, were they
02:13:44.180
asking for him to assign a probability? Like, I don't even understand what the question was.
02:13:50.300
Yeah. I mean, I think they wanted him to say at what temperature would it fail because the-
02:13:53.900
Well, it clearly had already failed. So really, this is a probabilistic question.
02:13:58.420
Yes. But again, that's not a linear question, right? That's an asymmetry question. That's the
02:14:03.540
question of so-and-so has an actuarial risk of having a heart attack of 5.4% in the next decade
02:14:11.600
should you take preventative measures? I don't know. I mean, it depends on your view of the
02:14:17.220
world. What's the upside? What's the downside? What's the risk of doing something about it
02:14:21.280
versus the risk of not doing something about it? Those are very asymmetric risks.
02:14:25.340
Yeah. And I mean, actually, if you read the Rogers Commission, which investigated the
02:14:28.620
Challenger disaster, Richard Feynman, you know-
02:14:39.220
Oh, okay. Who was also, I'm sure, an exceptional person.
02:14:43.300
There was a point where Feynman was asking questions like this. Like, what were you trying
02:14:47.360
to get him to say? They say, well, he couldn't quantify his case. He didn't have data. And
02:14:50.580
Feynman says, when you don't have data, you have to use reason. And he was giving you reasons.
02:14:54.660
And there is a point at which they're trying to say, well, at this temperature, based on
02:14:58.480
this data, the chances of failure should have been like one in a, I don't know, a
02:15:01.760
fulfilling, some enormous number. And Feynman's like, that's nonsense. You had two cases
02:15:07.000
that had like a small failure here. And you're telling me it's basically impossible.
02:15:13.100
Yeah. Yeah. And so obviously there was a lot of cover your ass stuff going. And they even
02:15:17.160
knew that at the time. So there was this unusual on that conference call. Once Morton
02:15:21.700
Diacol said, well, our engineer is saying, don't launch. We're going to support that.
02:15:25.220
And then there was all this discussion and they went for an offline caucus where they
02:15:28.180
said, where they kept being asked for data, quantify your case, quantify your case, quantify
02:15:32.100
your case. And they said, we can't. Okay. I guess we agree to launch. And then
02:15:35.120
they were required to do a sign off that they didn't have to do in the past. So obviously
02:15:38.540
people were sort of in CYA mode at some level, or they felt protected by the process. But
02:15:43.540
yeah, I don't think they weren't the best questions that they were asking. I mean, I think they
02:15:47.580
wanted to know at what, again, at what temperature will we suffer catastrophic failure? And the
02:15:51.260
answer was that they didn't know, but that things didn't look good. And there was reason
02:15:56.800
Think about that question, even through the lens of the financial crisis, at what loan to
02:16:02.280
value ratio at, do you see a default? Or if you go through all the metrics, it's like,
02:16:07.120
it's a probability distribution. The only way you can really answer these questions
02:16:10.520
is you can't answer them this way, but the only way you can even get estimates at that
02:16:15.120
is to run simulations across distributions, assuming you even know how to predict the probability
02:16:21.880
of failure, which in that case, I would argue they didn't even have that.
02:16:24.900
And spatial, most complicated machine ever made, maybe not as complicated as the credit
02:16:29.440
system, but most complicated machine ever made, not whatever, 24 launches, they'd all
02:16:33.840
come back safely. And you're right, they didn't know. And in fact, when Morton Thiokol gave
02:16:38.840
its first recommendation, their initial recommendation was don't launch below 53 degrees because NASA
02:16:44.740
wanted a temperature. And I think the project manager thought that the whole shuttle was cleared
02:16:50.020
from 33 to 99. So they were putting definite boundaries on it. So they said, don't go below
02:16:54.980
53. And they said, well, what's your reasoning for that? They said, well, we've done 53 before
02:16:58.520
and it came back. And that actually totally backfired. So basically they set the lower
02:17:03.360
bound at what they'd already done and said, don't go below it. And so it backfired in the sense that
02:17:08.120
NASA had this very strong engineering culture, of course, that had worked great up till then.
02:17:13.100
And so he said, that's not science, that's tradition. That's not an answer. You've departed
02:17:17.460
from engineering. Give us an engineering story. Don't say just do what we've done before.
02:17:21.000
And I get that. Like as Mary Schaefer, a NASA engineer later said, perfect safety is for people
02:17:25.400
who don't have the balls to live in the real world. So you can't, it is a probability distribution.
02:17:29.220
You can't have perfect safety. But I think their attempt to be prudent backfired because it was
02:17:34.040
viewed as an emotional rather than a scientific case essentially. But as Feynman said, the data wasn't
02:17:41.140
there. So you have to start thinking about reason. And that doesn't mean maybe they would have
02:17:45.260
gone with the same solution, but they had to start thinking about this problem in a different
02:17:50.080
way than they were used to, because usually they did have the data they needed to make a decision.
02:17:55.040
The other challenge of these case studies, because it's easy to just stop there, but we also don't
02:17:59.220
realize in the 24 launches prior and the God knows how many launches that followed it, including
02:18:05.960
one or more disaster, by the way, on re-entry, what's the denominator? How many times did somebody,
02:18:11.900
first of all, how many disasters were barely avoided? Maybe at least another one on the day
02:18:17.120
that it was 53. And could you ever have had a full consensus on any given day? This is a great case
02:18:23.340
study because it has so much, the richness of the data that follow are there, but we don't know if
02:18:30.420
every time one of these things goes up, there was also somebody in the room that said, and by the
02:18:35.100
way, with perfectly good reason, no way, no way, no way. And here's the reason. And if that's,
02:18:39.720
so is this the price we have to pay to live in an uncertain world? Or in retrospect, was Feynman
02:18:45.980
right? And this one should have been averted using reasonable engineering insight.
02:18:52.120
Yeah, I think, I think, and it's so easy to say in retrospect, of course, these people are under
02:18:56.260
incredible pressure. They've had all successes in the past. The astronauts know they're taking risks.
02:19:01.400
Everyone knows they're taking risks, but I do think there's a case to be made that this one
02:19:05.580
should have been averted, like voices were being raised. And in fact, I think one of the reforms
02:19:10.380
that came, you mentioned narrowly averting crisis before this, the 53 degree launch.
02:19:15.260
I think one of the, I spent a lot of time talking to the head of the rocket booster program while I
02:19:21.460
was reporting the book. And I think he was saying one of the changes that occurred was sharing
02:19:25.400
information like that with the astronauts themselves, because the feeling was, had they known
02:19:29.840
what happened with that O-ring, then they would have said, no, no, no, no, no, we're not ready to go.
02:19:34.720
You guys need to figure this out. And so I don't know whether that would have, or it wouldn't have.
02:19:40.220
But I think maybe, I think it's worth getting a different view when you're assessing that risk.
02:19:44.760
Was it Atlantis that, which was the one that burned upon re-entry, Columbia?
02:19:51.640
That's what I was going to ask you. Was there a cultural similarity in the screw up?
02:19:55.580
Or was it a different, totally different type of miscarriage?
02:19:57.140
Cultural carbon copy. In fact, the investigation commission for the Columbia accident wrote in their
02:20:02.180
conclusions. This is so similar to the Challenger disaster, culturally, that we deem NASA not a
02:20:07.840
learning organization because they didn't learn from that experience. And what I write about is
02:20:11.940
they had this incredibly strong process culture, essentially, that was, they had this sign like
02:20:16.200
on the mission, on one of the rooms that said, in God we trust, all others bring data, which is
02:20:21.020
great. Like they were super rigorous. But when they would get into these situations where you didn't
02:20:26.340
have the data you wanted, then continuing to sort of ask for it and follow these very strict procedures
02:20:31.520
meant they really kind of constrained their thinking. Like with Columbia, there were engineers
02:20:35.920
who said, we'd like photographs of a part of the shuttle we think is damaged. And so they went and
02:20:41.760
asked the Department of Defense for those photos. And their superiors not only blocked them, but
02:20:48.180
apologized to the Department of Defense for going outside of the normal process for trying to
02:20:53.240
acquire things like that. And so in both cases, they kept sticking to this very rigid process.
02:20:57.980
We need an engineer case. We need a quantitative case. Or these concerns like they're not being
02:21:02.420
quantified and you're not going through the proper channels. And so it doesn't count.
02:21:05.600
Evidence and hunches kept being deemed inadmissible because they weren't part of the normal formal
02:21:09.800
process. And it happened in the exact same way. Both times, people suspected what was going to happen.
02:21:15.660
But because their concerns didn't fit into the normal procedural boxes, they were discounted.
02:21:20.420
No, we don't know the denominator. We don't know how many times people had concerns that
02:21:24.220
were completely unwarranted and would have thwarted. So therein lies the challenge.
02:21:28.680
And that's what Alan McDonald, who was the head of the Rocket Booster program, told me. He's like,
02:21:31.840
look, if we called off that launch for Challenger, people would be called, as he said, chicken littles.
02:21:37.080
Because you have to be willing to take risk in the space program and you don't really get credit
02:21:42.180
As I was about to say, let's assume they had not launched that day and they'd waited until the next day
02:21:47.000
and it was warmer and they launched. We wouldn't be having this discussion about it. You're never
02:21:52.640
That's right. And I think there's one sort of thing that I didn't write about, but that I think has
02:21:55.600
been attributed a little wrongly, where some people have said there was pressure on Morton
02:22:00.780
More pressure because there was a civilian and this was more high profile? Or what was the...
02:22:04.220
No, for Diacol, there was more pressure because NASA had said they were going to open up the
02:22:09.160
But, so people have said, oh, that pressure, maybe that pressure was a problem, but Diacol
02:22:13.240
gave the initial recommendation not to launch. So they were okay not to launch. And then they
02:22:17.760
were pressed for the quantitative case. So I don't think that pressure was definitive because
02:22:22.280
they initially came with the recommendation of not to launch.
02:22:25.500
So speaking of stories in the book, this is different, but it's equally perplexing to me,
02:22:29.500
which is the firefighters and these guys who are doing these crazy jump rescue things. It's not that I
02:22:34.700
don't believe the stories. I do, but I can't. I'm trying to be empathetic to that situation and
02:22:40.900
say, where am I making a similar mistake in my life? So spend a moment explaining what that is.
02:22:45.540
Yeah. This comes from the work of a psychologist named Carl Weick, who writes a lot about what he
02:22:48.560
calls sense-making. Like how do people collectively make sense of a dynamic situation? And one of the
02:22:55.280
things he noticed when he was studying wilderness firefighting teams, hotshot firefighters who
02:23:01.080
hike in, try to dig trenches around wilderness fires or smoke jumpers who parachute into them
02:23:05.420
is that they do a great job. They're very reliable, but sometimes something unusual happens. Like a fire
02:23:10.620
jumps from one slope across a gulch to another slope and starts chasing them uphill. And when,
02:23:16.120
when unexpected things happen, sometimes they have trouble and sometimes they die. And when they die,
02:23:21.140
what he noticed was they tend, the ones who die tend to die with their tools, chainsaws,
02:23:26.020
drip torches, axes, whatever, hundreds of pounds of equipment. And the ones who survive or much
02:23:31.980
fewer have dropped their equipment and run. And in many cases, the hotshots or the firefighters will
02:23:38.160
refuse orders to drop their tools. And so I was going through like reports of some of these tragedies
02:23:44.720
and you'd see victim is 100 feet from safety, still carrying chainsaw and drip torch and backpack and
02:23:50.840
things like that. And even accounts of survivors would say they'd be running, they'd be looking for a
02:23:55.080
place to put their, they couldn't believe they were dropping their equipment because it was so
02:23:58.340
central to their identity as a firefighter. Norman McLean, who most famously wrote A River Runs
02:24:03.340
Through It, also wrote a book called The Young Men in Fire. And he wrote that being asked to drop your
02:24:07.720
tools is like being asked to forget that you are a firefighter because that's your whole group
02:24:12.560
identity and all your training is built on never getting rid of your tools. But an unfamiliar
02:24:16.480
situation, holding onto them kills you. And so Wyke used that as kind of a, an allegory for what he saw in
02:24:23.520
other usually highly reliable organizations like commercial airlines, where when things go
02:24:30.160
as expected, these very formal strict procedures work incredibly well. But sometimes having done
02:24:37.960
them so many times makes the organization rigid such that when things change and when it's obvious to an
02:24:42.900
outsider that they should drop their tools and run, they don't do it because they're so used to doing
02:24:46.740
one thing. And so what he was arguing for is how can we make training so that we have those reliable
02:24:51.220
procedures, but also so that people know they have to improvise and we can't train them exactly what
02:24:56.860
to do for improvising necessarily. Although now they do get trained to drop their tools, but who knows
02:25:01.640
How many people had to die to figure that out? And again, the more powerful part of that allegory is
02:25:05.740
the, what's my tool, right? What are the tools that I am lugging around that are probably helping me
02:25:10.920
99% of the time, but 1% of the time, not only are they not helping me, but they could be
02:25:16.560
catastrophically wounding me. Yeah. I mean, have you thought about this in your own life?
02:25:20.780
Oh, for sure. In fact, when I told that, and this is not nearly as, it sounds like it has so little
02:25:25.720
gravity compared to this, but when I was talking before about taking a fiction writing class,
02:25:29.760
I was trying to think about the joy of it and think about new structure, learn new structure for writing.
02:25:34.820
But what really came out of it was this thing where it said to me, I'm using quotes in a stupid way
02:25:38.300
because I've been writing investigative magazine articles for the last couple of years where you and the
02:25:42.520
lawyers really want other people to explain stuff in their voice if they can, but that's not good for
02:25:47.300
this kind of book. And I didn't even think about that. It was not the right way to go about it until
02:25:52.100
I was like knocked out of it by doing something different. Again, that's not, that's not anything
02:25:55.880
on the level of tragedy. But some of the other things Wyke wrote about were doing commercial
02:25:59.660
airlines. They have these incredible, it's incredibly safe. It's pretty remarkable actually.
02:26:04.240
But when there are problems, it was usually the large majority of problems would be caused when
02:26:09.780
a situation would change and the flight crew would do the thing they were used to anyway,
02:26:15.100
even though to like an outsider would become obvious that they had to shift what they were
02:26:19.020
doing. So I think it's this sometimes paradox of expertise where if you haven't learned to do
02:26:24.180
some improvisation, then you kind of get stuck doing similar things over and over. You know,
02:26:27.360
you get like the typical, when all you have is a hammer, everything looks like a nail problem.
02:26:30.780
And I think there's plenty of that in medicine.
02:26:33.300
You could argue medicine is probably has more of that than anything else, given the degree of
02:26:38.880
specialization. But also, I think the tacit kind of, what's the word I'm looking for,
02:26:45.000
sort of the air of invincibility, not invincibility either, is the sort of the, I think part of it
02:26:49.860
stems from the privilege of medicine, which is like you can sit down with, you could meet a person for
02:26:53.700
the very first time in the emergency room, and they'll take their clothes off, and you're going
02:26:57.740
to examine them, and they'll tell you a detail about their life they've never told another human being.
02:27:01.960
There's just something about that that says, well, there's still something about this
02:27:05.260
profession we place so much faith in. And then by extension, those in the profession
02:27:10.740
start to project that faith on their own decisions. So I think that, coupled with the stakes,
02:27:17.720
coupled with the specialization, I think probably creates a fertile environment for exactly that
02:27:21.760
type of thinking. Now, I mean, I guess the last point I want to ask about on this particular issue is,
02:27:26.580
had those firefighters, going back to this particular example, been trained as lifelong firefighters
02:27:34.380
versus they had been sampled across a much broader group of people coming in? Is the point of the
02:27:42.760
story that if you'd come in to that role having been an accountant, working at Subway, just pick a
02:27:49.840
totally random distribution of people, would it be more intuitive to that group to have dropped their
02:27:54.940
tools? That's a suggestion. Yeah, that it would be. And in fact, what Wyke and McLean argued is that
02:28:01.240
in the first of the famous disasters called the Mangulch fire, a few people survived. And the leader of
02:28:08.320
the group, he ordered people to drop their tools. They refused the orders, essentially, except for the
02:28:14.000
two that did survive. And one of the things they pointed out was that he had a much broader training
02:28:19.960
base. He was used to doing lots of other things with tools, not only firefighting. And so they
02:28:25.500
thought that he was, we don't know for sure, but the argument that they made was that he had had a
02:28:30.700
much broader experience with tools. So he didn't think of them as like only these things that he
02:28:34.220
used in a certain way for firefighting. And so in fact, what he did to save himself was, so he's ordering
02:28:40.200
his guys to drop his tools. Most of them aren't. He realized he wasn't going to, he was far down the
02:28:44.840
gulch. He realized he wasn't going to be able to run away from the fire. So he actually lit a fire in
02:28:49.300
front of himself, burned the grass and dove into the ash and the fire burned around him. So he
02:28:55.380
improvised. And now people are trained to do that. The idea that you would stop a fire by lighting a
02:29:00.880
fire in the grass in front of yourself. And that worked. But so they made the argument that he was
02:29:05.220
much better set up to improvise because he was used to improvising with tools.
02:29:10.160
David, I could continue having this discussion for another couple of hours, but I want to be
02:29:14.440
sensitive to your time. And so before we wrap, is there anything that I feel like we've
02:29:19.280
only scratched the surface, frankly, of these two books? I actually thought we'd get through more,
02:29:23.680
but I guess that speaks to how long-winded I am when I ask questions.
02:29:27.060
No, you told me before we started that I could go on and be digressive. And I told you that I'm
02:29:32.860
It was a perfect, perfect, it was match quality at its finest. Anything we didn't talk about in the
02:29:37.480
last few minutes that you want a chance to sort of discuss?
02:29:41.640
Someone who became, that I don't get asked about much in the book, who became sort of a role model for me,
02:29:46.200
works not so far from here, a woman named Frances Hesselbein, who took her first real job at the
02:29:50.360
age of 54. And I'll keep her story short here. But basically, she essentially became, she became
02:29:56.660
a CEO of the Girl Scouts. And when she had one semester of junior college under her belt in her
02:30:02.840
entire life, but now has 23 honorary degrees, as she likes to know. And when she actually interviewed
02:30:08.520
for the CEO position, the people before her had had incredible leadership credentials. Captain Dorothy
02:30:14.460
Stratton was one, she started the Women's Coast Guard Reserve and was university dean. Another
0.99
02:30:18.040
was Cecily Kanin-Selby, prominent scientist and leader in industry and education. Frances Hesselbein,
02:30:23.660
one semester junior college, leader of one of 355 local councils of Girl Scouts. And again,
02:30:30.520
first professional job at age 54. And so she says, no, no, I'm not taking that CEO job. I'm never moving
02:30:35.720
out of Pennsylvania. She grew up in Johnstown. And her husband says, no, I'll drive to New York,
02:30:40.220
you can turn it down in person. And so they asked her, if you took over Girl Scouts, this is late
02:30:43.660
60s. Girl Scouts is in total crisis, free fall of membership and volunteers. And what would you do
02:30:50.080
if you took it over? And she doesn't want the job. She feels fine to say whatever she, to speak her
02:30:54.980
mind freely. And she says, throw out our sacrosanct handbook. I'd replace it with ones that appeal to
02:31:00.360
girls of different ages. I'd start working on diversity. If an indigenous girl near an ice
1.00
02:31:04.080
flow in Alaska opens a book, I want her to see herself in a Girl Scouts uniform. She just goes through
02:31:08.620
all this. I'd sell some of the underused campsites, even though it'd be painful. Get rid of some of this
02:31:13.360
homemaking stuff. Focus on, educate girls about sex and drugs and math and science and all this.
0.99
02:31:18.160
And she's like, well, that was fun, but I'm never going to hear from them again. Of course, she
02:31:21.220
comes back. I mean, this is actually the early 70s when she was interviewing. But so she gets the CEO
02:31:25.820
job and totally transforms the organization. Turns the cookie business into like a third of a billion
02:31:30.360
dollar business. Triples diversity representation, adds 130,000 volunteers, people she's paying in a sense
02:31:36.740
of mission, not in money, and basically saves the Girl Scouts. And she works every week. I'm sure
0.88
02:31:43.420
she's at her office right now because she works every weekday in Manhattan. She's only 103 and a
02:31:47.380
half. So she has a lot of, I'm sure she has a lot of place to go. But I think she meant a lot of
02:31:52.580
things to me. One, people can make an impact when they're older than they think they can. She's now
02:31:56.120
running the Francis Hesselbein Leadership Institute and teaching at West Point. Also, she never expected to
02:32:00.860
do any of the things she did. Every time she got offered an opportunity, she'd say like, no,
02:32:04.060
I'm not doing it. And then they'd tell her, well, then this Girl Scout troop is going to have to be
02:32:08.180
folded. Sorry. And she'd be like, fine, I'll do it for a month and would get to try it and be like,
02:32:12.240
wait, I actually love this. And that's everything she did. So she sort of short-term planned her way
02:32:16.780
through life. And she had two sayings that really stuck with me. One was leadership is a matter of
02:32:22.540
how to be, not a matter of what to do. I think that's a powerful thing to think about. So much about
02:32:27.600
leadership is being a good example, not having to know everything. Sometimes I think we have this
02:32:32.040
George Washington standing up in the boat crossing the Delaware, which I don't think that's an
02:32:35.820
accurate depiction. I think there's a real painting of him somewhere. And obviously he's
02:32:38.520
sitting down in the boat, but it's like this idea that they know everything ahead. They're
02:32:41.940
clairvoyant. It's like, no, they need to be a good example. And part of that is admitting that you
02:32:45.520
don't know stuff. And the other was her saying was, you have to carry a big basket to bring something
02:32:51.180
home. And she told me when she was at one of her first training events, some woman complained she
0.98
02:32:56.460
wasn't learning anything. She already knew all this stuff. And then this other woman told that saying to
0.95
02:33:01.480
Francis, and then it sort of became one of her mantras. And I love that saying, because I realized,
02:33:06.760
again, it was part of this, I don't want to keep coming back to this online beginners fiction
02:33:09.860
writing class I took, but it was, it was sort of the emphasis of hearing her say that they said,
02:33:13.460
sure, I can take a beginner's class. And I realized there's like no amount of beginner's classes I could
02:33:17.920
take that I wouldn't learn something from. Because if you go in open-minded, you'll learn something from
02:33:23.280
it. There was one day in my neighborhood, I live in DC now, where I noticed a bunch of
02:33:26.760
increase in the population of wizards in my neighborhood. And so I walked over to a nearby hotel,
02:33:31.120
noticed they were having like a Japanese conference, animation conference. Yeah.
02:33:34.460
And they had a beginning Japanese comics writing class. So I'm like, I'll sit in on that.
02:33:38.420
Probably not going to write a Japanese comic, but it's structure and it's story and narrative and
02:33:42.000
dialogue and all this stuff. You can't not learn from it. So it's just, just made me realize that if
02:33:47.700
you go into it with that mindset, you're just constantly learning something. And so that's an
02:33:51.740
approach I try to adopt. Two of those phrases really stuck with me.
02:33:54.860
And I am glad you told that story. That is a beautiful story. And I think it dovetails
02:33:59.600
perfectly into this idea of being a lifelong student, which I think, well, frankly, that's
02:34:05.520
sort of one of the things that's fun about a podcast. So basically there's an excuse to learn
02:34:09.160
a whole bunch of stuff. That's what I figured. I mean, you don't have to be doing this for any
02:34:11.580
professional reason. Yeah. Well, David, thank you so much. I really appreciate it. Thanks for coming
02:34:16.140
up to New York today. I appreciate it. Pleasure. I enjoyed it. Thank you for listening to this week's
02:34:20.700
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