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Speaker 1: This is Mesters in Business with Very Redoults on Bloomberg

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Speaker 1: Radio this weekend. On the podcast What Can I Say?

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Speaker 1: Michael Lewis, author of so many amazing books, starting with

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Speaker 1: Liars Poker, which just celebrated its thirty something anniversary and

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Speaker 1: the audio rights reverted back to Lewis. We have a

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Speaker 1: fascinating conversation about that, about expertise about his podcast, Really

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Speaker 1: what can you say? Michael Lewis is just one of

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Speaker 1: a kind's everything he does is just absolutely fascinating. I

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Speaker 1: really enjoyed this conversation and I think you will also,

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Speaker 1: with no further ado, My interview with Michael Lewis. This

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Speaker 1: is Mesters in Business with Very Redhoults on Bloomberg Radio

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Speaker 1: my extra special guests this week. You know him, you

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Speaker 1: love him, You've read all of his books. Best selling

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Speaker 1: author Michael Lewis. He has written so many seminal books,

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Speaker 1: so many seminal tomes on Wall Street, from Liars Poker,

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Speaker 1: The New New Thing, The Big Short, Flashboys, The Premonition,

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Speaker 1: on and on and on it goes. Uh. He is

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Speaker 1: out with season three of his podcast Against the Rules,

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Speaker 1: and he also created a series of short uh discussions

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Speaker 1: about Liars Poker, which celebrated its thirtieth anniversary right before

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Speaker 1: the pandemic. You can get that either as an audio book,

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Speaker 1: the print book, or listen to the audio companion that

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Speaker 1: he's put out on other people's money. Michael Lewis, Welcome

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Speaker 1: back to Bloomberg. Good to hear your voice. Same here,

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Speaker 1: same here. So for for the people who may not

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Speaker 1: be familiar with you, let's let's just do a brief background.

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Speaker 1: You graduate from Princeton and you head to Wall Street

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Speaker 1: to make your fortune, where you were pretty much rejected

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Speaker 1: by everybody, most notably Lehman Brothers. Tell us a little

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Speaker 1: bit about that experience. Well, I was at that point.

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Speaker 1: I was a senior Princeton, and everybody was showing up

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Speaker 1: on odd days of school wearing a suit and going

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Speaker 1: to the career services office and interview with the Wall

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Speaker 1: Street firms. Because that's just what you did. And so

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Speaker 1: this is what one two uh, and it was. It

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Speaker 1: was kind of a new thing that you know, half

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Speaker 1: the class of Princeton wanted to go to Wall Street. Um,

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Speaker 1: but half the class of Princeton want to go to

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Speaker 1: Wall Street. So I thought, well, I must want to

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Speaker 1: go to Wall Street. Too, and I rolled into a

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Speaker 1: few of those interviews, one with Lehman Brothers, uh, not

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Speaker 1: even knowing really what Wall Street was, and um, I

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Speaker 1: didn't really understand why I was supposed to know what

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Speaker 1: Wall Street was. But but it was humiliating, you know,

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Speaker 1: uh like, do you know the difference between the stock

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Speaker 1: and a bond? No, I'm happy to learn the kind

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Speaker 1: of thing. And but but I was doing it not

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Speaker 1: I really, I kind of it's not it's probably too

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Speaker 1: starting to say it was a lark, but I just

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Speaker 1: didn't have anything better to do, so I thought, what

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Speaker 1: the hell, I'll go go to these interviews. And it

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Speaker 1: was only later, so three years later, after I've done

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Speaker 1: a master's at the London School of Economics, that I

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Speaker 1: really accidentally falling into a job at Solomon Brothers. Um

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Speaker 1: and just to slush this out, at Princeton, you're not

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Speaker 1: taking economics of business courses. Was an art history major,

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Speaker 1: you know, I was an art history major. But that

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Speaker 1: that didn't stop anybody. I mean it was I mean,

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Speaker 1: that's the beginning of the world we're still kind of

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Speaker 1: living in today. I may I have a daughter who's

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Speaker 1: a junior in college, and you know, a third of

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Speaker 1: her class wants to go work in financial services. Where

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Speaker 1: in financial services a little different. Back then, it really

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Speaker 1: was very bank centric. It was Morgan, Stanley, Goldman, Sachs,

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Speaker 1: Lehman Brothers, Solomon Brothers, and so on. Uh, but but

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Speaker 1: it was I mean it was strange, right, I mean

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Speaker 1: everybody just takes it for granted. Now, you don't grow

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Speaker 1: up learning the difference between stock and a bond. Uh,

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Speaker 1: you don't grow up knowing what a difference between a

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Speaker 1: commercial banker and an investment banker. That was a question

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Speaker 1: that you had to have the answer to if you

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Speaker 1: were interviewing for investment banks, because they really needed to

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Speaker 1: be flattered that you knew the difference. That investment bankers

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Speaker 1: were like, you know, they're alpha, alpha dogs and the

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Speaker 1: commercial bankers were Nobody's. Uh, you need to be able

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Speaker 1: to explain that difference. So you did. I remember kind

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Speaker 1: of cribbing for the thing, getting the cliff notes from

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Speaker 1: a friend who really cared about it, Like if they

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Speaker 1: what are they gonna ask me? And what I gotta say?

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Speaker 1: And it was like, well, if they asked you about

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Speaker 1: the difference between investment bankers and commercial bankers, you tell

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Speaker 1: them that investment bankers drive ferraris and and commercial bankers

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Speaker 1: drive forwards kind of thing, and and uh and it

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Speaker 1: was but but it was it was so I mean shallow.

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Speaker 1: It was a It was a shallow as having a

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Speaker 1: quick conversation with a friend and then ducking into an

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Speaker 1: interview with Lehman Brothers to see if I could get

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Speaker 1: away with it um And it wasn't any genuine interest

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Speaker 1: because you how could it be genuine interests? You no

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Speaker 1: idea what they did. Now, my insight was that this

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Speaker 1: was true of the other you know, seven d people

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Speaker 1: in my class who were applying for these jobs too,

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Speaker 1: that nobody knew what they did. Almost nobody knew what

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Speaker 1: they did, so everybody wanted to do it even though

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Speaker 1: they didn't know what it was. I found it really

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Speaker 1: ironic that you got rejected by Lehman Brothers who then

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Speaker 1: come back into your life with the big short Well.

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Speaker 1: I never really made that I didn't feel deeply embitter

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Speaker 1: everybody being injected. Were followed me about the Lehman Brothers

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Speaker 1: interview and his inn liars poker, and I feel this

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Speaker 1: to the day is that there were two people interviewing me,

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Speaker 1: and one of them was a young woman I really

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Speaker 1: liked who was two years ahead of me at Princeton

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Speaker 1: and we were like pals on the Princeton campus and

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Speaker 1: she knew me well pretty well. And when I get

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Speaker 1: into the interview, it's like she's a different person. She's like,

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Speaker 1: we've never met. And if I don't know, if I

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Speaker 1: can't talk intelligently about stocks and bonds, she's giving me

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Speaker 1: a cold stare. And she created a really chilly environment.

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Speaker 1: And I thought, this is strange. It's strange to do

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Speaker 1: that with someone who you probably know well enough already

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Speaker 1: to evaluate whether this person is going to fit in

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Speaker 1: or not fit in, or be able to do the

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Speaker 1: job or not do the job, or you know, has

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Speaker 1: anything going on between their ears or he doesn't. And

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Speaker 1: she it was this really artificial thing. She was in

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Speaker 1: one of those at the time, the suits that women

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Speaker 1: wore with a big boat the little puffy boat ie

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Speaker 1: and uh, and I just thought that it's just it's

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Speaker 1: just it's just a really uncomfortable, socially uncomfortable. And I

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Speaker 1: did pick up. I don't know, probably every kid picks

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Speaker 1: this up when they're moving from school life to work life.

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Speaker 1: Just um, how how how artificial work life can be,

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Speaker 1: how artificial it can seem. Uh And and that was

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Speaker 1: that was my first brush with it, and it was

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Speaker 1: really unsettling. I can I can imagine. So, so you

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Speaker 1: don't get by Lehman Brothers. But eventually, through a crazy

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Speaker 1: story you telling liars poker, you end up at what

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Speaker 1: actually is the hottest firm in the world, Solomon Brothers.

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Speaker 1: How soon after you arrived at Sally did you realize

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Speaker 1: this is a really unusual place. Well, I'll tell you.

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Speaker 1: I'll tell you two stories and you can decide which

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Speaker 1: one is true, because I actually don't remember. But um,

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Speaker 1: the first story is I told myself, I thought, I

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Speaker 1: told myself, Look, I know I want to be a writer,

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Speaker 1: but no one's paying me to be a writer, and

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Speaker 1: a really and you know, I can get ninety dollars

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Speaker 1: an article writing for the Economist of the Wall Street

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Speaker 1: Jurnal up at page or I can go take this

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Speaker 1: job for huge piles of money. I can make some

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Speaker 1: money and then figure out how to be a writer.

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Speaker 1: I think that's what was on my mind. And but

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Speaker 1: but but I walked into I knew even before I

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Speaker 1: walked into the place that it was a really interesting place.

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Speaker 1: I mean, it was if you just go back and

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Speaker 1: look at how much at Solomon's profits compared to the

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Speaker 1: rest of Wall Street in say Night four they made,

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Speaker 1: it was like they made more money than all the

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Speaker 1: rest of Wall Street. Like it was just you were

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Speaker 1: they were clearly in some other business. Even if you

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Speaker 1: didn't know what it was, you'd say, something weird is

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Speaker 1: going on here, and I get there and it's raucous.

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Speaker 1: I mean, it's crazy. The training program as a frat house.

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Speaker 1: The trading floor is an even better frat house. It's

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Speaker 1: it's it's intellectually stimulating. It's actually the the the false

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Speaker 1: kind of presentation of Wall Street at the time was

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Speaker 1: that these investment bankers and the people in the investment

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Speaker 1: banking department start out as analysts and become associates, and

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Speaker 1: that worked their way up to vice presidents and they're

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Speaker 1: always they're meeting with CEOs and they're doing the M

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Speaker 1: and A transaction and all that. That that's where the

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Speaker 1: actual intellectual life was. If you were a really good student,

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Speaker 1: that's where you went. And if you were like just

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Speaker 1: had greasy elbows, you went to the trading floor. The

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Speaker 1: truth was that the real intellectual work was being done

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Speaker 1: on the trading floor. It was pricing these figuring out

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Speaker 1: how to price and value and and trade these all

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Speaker 1: these new complicated securities, and it was riveting. And also

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Speaker 1: understanding how global markets were working. I mean just just

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Speaker 1: they are all these new markets opening up everywhere, and

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Speaker 1: their relationships. It was far more intellectually stimulating than then

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Speaker 1: the stuffy stuff that was going on inside the offices

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Speaker 1: of the investment bankers. So instantly it's like, wow, people

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Speaker 1: are wild here, and wow, it's actually intellectually interesting. So

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Speaker 1: that the training class, which goes on for five months

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Speaker 1: or wherever it was was, was one of the best

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Speaker 1: courses I've ever had in anything. It was absolutely riveting,

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Speaker 1: and I sat there taking notes and asking questions and

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Speaker 1: feeling like I was getting the world's best survey course

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Speaker 1: in how the financials and worked. Um so I was

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Speaker 1: so the second story. So the first story is I'm

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Speaker 1: gonna go make some money and then figure out how

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Speaker 1: to be a writer. The second story. And you can

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Speaker 1: decide whether this ring is true or not. I have

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Speaker 1: a friend who was in that training class, that first

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Speaker 1: training class that I was in. His name was Keenan Damon.

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Speaker 1: He was an earnest young guy from Minnesota, and I

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Speaker 1: never met him. I sat down next to him the

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Speaker 1: first day of class, he says, and he said, and

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Speaker 1: he says, I sat down and I said, Hey, who

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Speaker 1: are you and what are you here for? And he said,

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Speaker 1: I'm Keenan Damon and I'm here because I want to

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Speaker 1: sell mortgage bonds and this is the place to sell

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Speaker 1: mortgage bonds, which I thought was strange because how would

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Speaker 1: anyone know they know me wanted to sell mortgage bonds.

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Speaker 1: But anyway, uh, and he said, he said to me,

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Speaker 1: who are you and what are you here for? And

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Speaker 1: according to him, I said, I'm Michael Lewis, and I'm

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Speaker 1: here to write a book. Uh. Now, I can't believe

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Speaker 1: I would have said that the you know, the first

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Speaker 1: day of class as Solomon Brothers. But it is possible

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Speaker 1: that I was already thinking this material is so good

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Speaker 1: that this is what I'm gonna do. I'm gonna spend

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Speaker 1: a few years here to write a book about it.

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Speaker 1: But it was messy because I was kind of like,

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Speaker 1: I got very engaged with it for a while. If

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Speaker 1: you'd asked me a year in what I was gonna do,

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Speaker 1: I probably would have said I was going to stay

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Speaker 1: five years. So you also kept a diary well during

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Speaker 1: your days at Solomon Brothers. That that might suggest that

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Speaker 1: you had a book on the mine. When did you

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Speaker 1: start keeping that diary. Yeah, I'm not really a diary keeper,

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Speaker 1: so that's true. If I was, and I was keeping

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Speaker 1: a diary, diary is a little strong. It wasn't like,

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Speaker 1: you know, I'm sad today and because my my best

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Speaker 1: friend said something mean to me. I didn't do it,

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Speaker 1: none of that stuff. It was. I was just recording

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Speaker 1: what I saw, and um and my thoughts about what

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Speaker 1: I saw, and by the and and by the I mean,

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Speaker 1: I do remember that by the crash of U when

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Speaker 1: I just by chance was wandering around the New York

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Speaker 1: trading floor, I worked in London but had been flown

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Speaker 1: back to New York, and all hell was breaking loose.

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Speaker 1: I I wandered around with a notebook out, just writing

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Speaker 1: everything down. Uh, And I knew that I was going

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Speaker 1: to write about this at that point. I left three

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Speaker 1: months later, But I think that what I was doing

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Speaker 1: was going I was. I was still writing while I

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Speaker 1: was there. I was going home at night and trying

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Speaker 1: to publish, write magazine articles, so I think at the

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Speaker 1: same time I was just kind of kind of keeping

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Speaker 1: a record in my computer of what I was seeing

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Speaker 1: and and so that does suggest that at some point

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Speaker 1: I realized this was material for me. So you touch

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Speaker 1: on so many things. I have to ask. First, good

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Speaker 1: trade leaving Sally three months after the eighty seven crash?

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Speaker 1: Was that was that good timing? Well, the timing wasn't

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Speaker 1: to the crash. The timing was to my bonus, which

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Speaker 1: landed in the bank account at the end of January.

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Speaker 1: So I had to hold my breath until that money hit. Um.

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Speaker 1: At the end of eighty seven, I already had a

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Speaker 1: book contract. I didn't sign it, but so I'd already

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Speaker 1: I'd already sold an idea for a book and gone

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Speaker 1: in And so at the end of January I went

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Speaker 1: and told my employers that I was leaving this good trade. Um, well,

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Speaker 1: if my literary career hadn't worked out, it had been catastrophic,

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Speaker 1: I was. I was. It looked anyway like I was

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Speaker 1: gonna make a lot of money Solomon Brothers. I was paid.

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Speaker 1: Then they told me I was gonna make a lot

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Speaker 1: of money. Um. And I tell you, there was a

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Speaker 1: really funny moment, and this tells you something about the

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Speaker 1: spirit of that moment. It's very different from now. It's

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Speaker 1: hard for people to believe that. You would think right

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Speaker 1: anybody was within like Goldman Sacks. Now we think there's

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Speaker 1: no way I can like walk out of Golden sacttions

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Speaker 1: and write a book about what I just saw. Goldman

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Speaker 1: Sacs are gonna assume me. I will have signed all

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Speaker 1: these non disclosure agreements. I'll be discredited every which way. Actually,

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Speaker 1: there were no non disclosure agreements that Solomon Brothers. There was.

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Speaker 1: I told when I told the bosses I was leaving,

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Speaker 1: they took me. They took These were very senior people.

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Speaker 1: They took me into a room and I told him

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Speaker 1: I was leaving. I was gonna write a book about

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Speaker 1: Wall Street. I didn't know what the book was gonna

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Speaker 1: look like exactly, but I said, I'm gonna go write

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Speaker 1: a book about Wall Street. They didn't say, oh, like,

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Speaker 1: what's in the book, and don't write about us. Nothing

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Speaker 1: that was like furthest from their minds. They were worried

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Speaker 1: about my mental health. They were sincerely worried. It was

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Speaker 1: really sweet. If you're there, you just be thinking, these

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Speaker 1: people really care about this young man they really thought.

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Speaker 1: They said, look, you just made whatever, a quarter of

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Speaker 1: million dollars, You're probably gonna make twice that next year.

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Speaker 1: They actually said, now, this is probably b s. But

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Speaker 1: they did say, we think you're someone who might run

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Speaker 1: the firm one day. And and I was just like, wow,

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Speaker 1: you know, this is so nice of them to care

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Speaker 1: so much, um and the and it was like, they

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Speaker 1: just just don't do this, Like they said, wait ten years,

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Speaker 1: wait five years, you get rich and then go write

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Speaker 1: your books, which is also what my father said. And uh,

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Speaker 1: and I said to them, you know, I just can't.

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Speaker 1: I just feel like I got to do this thing.

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Speaker 1: And it was does a really sweet departure conversation, and

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Speaker 1: they're just worried. They thought I was insane. So at

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Speaker 1: the moment, it looked like in the moment, it looked

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Speaker 1: like a totally insane trade. But but you know, when

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Speaker 1: you're twenty seven years old and you are full of

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Speaker 1: passion and you think you know what you want to do,

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Speaker 1: I think you really, I think it's smart to honor

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Speaker 1: those ceilings. Ceilings. I really had a I mean I

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Speaker 1: had a head of steam. I had no real justification

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Speaker 1: for thinking that I was going to be a big

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Speaker 1: success as a writer, but I had a head of steam.

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Speaker 1: So so there are two points I have to sort

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Speaker 1: of annotate what you said. First, I think it's fair

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Speaker 1: to say that liars poker is to some large degree

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Speaker 1: why Goldman Sachs has non disclosure agreements. You kind of

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Speaker 1: you kind of force that on the rest of the street.

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Speaker 1: I think that's pretty fair, right, So I I ruined

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Speaker 1: it for everybody. You did. Hey, listen, someone has to

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Speaker 1: break the glass. And then second really end up on

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Speaker 1: the bottom of the sea and concrete shoes. But yeah,

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Speaker 1: but secondly, you had already published a coliment the Wall

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Speaker 1: Street Journal while you were working at Sally that got

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Speaker 1: you into trouble that had the most hilarious resolution. Tell

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Speaker 1: us about the compromise that was reached when you published

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Speaker 1: under your own name. So this you have to do

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Speaker 1: a tiny bit of back story you need here. It

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Speaker 1: was so I was writing while I was there, and

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Speaker 1: things would get into print, and maybe a year and

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Speaker 1: a half into my journey there, um I published an

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Speaker 1: article on the op ed page of The Wall Street

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Speaker 1: Journal arguing that investment bankers were overpaid. And it said

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Speaker 1: at the bottom Michael Lewis is an associated Solomon Brothers

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Speaker 1: in London, and um and I know, so this actually

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Speaker 1: gets to you really kind of can't believe the spirit

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Speaker 1: of the thing. But I remember exactly how I felt.

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Speaker 1: I was so excited I was in the Wall Street Journal.

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Speaker 1: I thought when I came in the next day, like

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Speaker 1: people would be slapping on the back, going, wow, you

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Speaker 1: got a piece of the journal. All that I thought.

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Speaker 1: I thought like everybody could be happy for me. And

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Speaker 1: I rolled in to the London office and the next

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Speaker 1: morning and Charlie mcpayh, who I had adored, who ran

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Speaker 1: the whole of Solomon Brothers International and had been the

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Speaker 1: one who hired me, was waiting at my desk ashen faced,

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Speaker 1: and he hadn't slept, and he said, we've had meetings

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Speaker 1: with like the board of directors overnight about your piece

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Speaker 1: because it's being apparently gonna be reprinted all over the

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Speaker 1: country and people are talking about the clients are calling.

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Speaker 1: And he said, he said, you can't. I mean, my god,

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Speaker 1: you've created crisis. And now you would think, oh, Michael,

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Speaker 1: you're fired. There is the next line, But actually I

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Speaker 1: think this is the backstory. I was in a very

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Speaker 1: odd position I had at that point, maybe the second

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Speaker 1: or third biggest customer of the whole firm who would

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Speaker 1: speak only to me. Uh, it was it was a

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Speaker 1: it was a proto hedge fund in London. Jacobroth's child

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Speaker 1: was the was the firm. But and the guy who

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Speaker 1: ran the money there. Um thought it was amusing because

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Speaker 1: I acknowledged to him how little I knew. He said, well,

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Speaker 1: nobody knows anything. You want to at least try to

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Speaker 1: sell me stuff. As long as don't try to sell

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Speaker 1: me stuff, he said, I'll do my business through you,

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Speaker 1: and he made me like the most successful salesman and

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Speaker 1: in in in the London office overnight. He was just

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Speaker 1: channeling a huge volume through me and would refuse to

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Speaker 1: like speak with anyone else at the firm, including John

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Speaker 1: good Friend, the chairman. When he would show up in London,

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Speaker 1: he'd say, I only talked to Michael. So I had

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Speaker 1: this situation where that guy, he was probably generating ten

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Speaker 1: million dollars of profits for Solomon Brothers, they were going

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Speaker 1: to fire me because of him, and so it was

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Speaker 1: sort of like, how do we deal with this problem?

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Speaker 1: And the boss of all of the bosses was sitting

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Speaker 1: there at my desk and he said, I said, I'm

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Speaker 1: not stopping writing that. That's you know. I made to

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Speaker 1: do this. I'm gonna do it. And he said all right,

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Speaker 1: he said could we do could you do it under?

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Speaker 1: Could you leave us out of it? I said, yeah,

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Speaker 1: I'm sorry, Ibou sad and he said, he said, uh.

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Speaker 1: He said could you use another name? And I said, well,

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Speaker 1: how about if I used my mother's maiden name. I

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Speaker 1: don't know why that popped into my head, but my

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Speaker 1: mother's main name was Diana Bleaker Monroe, and Diana Bleaker

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Speaker 1: Monroe wrote several pieces, a couple for the New Republic,

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Speaker 1: a couple for a magazine in London about and I'm

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Speaker 1: still using the material around me. It was just disguised

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Speaker 1: and um and I would come a couple of times

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Speaker 1: the New Republic rand pieces. I'd come into the office

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Speaker 1: or the evening. They'd come out kind of thing that

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Speaker 1: someone would fax them over to the London office. They

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Speaker 1: would be reprinted a thousand times and all over the desk,

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Speaker 1: and no one knew it was me who wrote them,

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Speaker 1: and they were everybody was reading him. So I had

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Speaker 1: market testing for this stuff before I wrote. War was poker.

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Speaker 1: I knew that people fought what I was writing about

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Speaker 1: Wall Street was kind of funny and like on point.

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Speaker 1: But that's that's so I had a little literary career

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Speaker 1: rolling alongside my my career on the Solomon Trading for

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Speaker 1: because of this conversation with this guy. So not a

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Speaker 1: total leap of faith. You had an idea, Hey, I

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Speaker 1: have some traction as as a writer. I just you know,

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Speaker 1: it seemed to me when I published a couple of

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Speaker 1: things I published that were about Wall Street, that everybody

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Speaker 1: on Wall Street wanted to read them. I wasn't thinking.

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Speaker 1: I didn't know how big the audience was exactly, but

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Speaker 1: I thought that was a good sign. Really interesting. Season

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Speaker 1: three of Against the Rules just dropped. Season one was

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Speaker 1: about umpires and all the interesting things they go through

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Speaker 1: and how umpire has changed. Season two was about coaching.

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Speaker 1: Tell us a little bit about season three and experts.

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Speaker 1: Why did you choose experts as a topic. Well, so

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Speaker 1: the idea is to pick some role in American life.

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Speaker 1: So referees are coaches very broadly defined, like referee is

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Speaker 1: also regulators for example, um or or you know, art

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Speaker 1: kind of sours people who are making making calls about

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Speaker 1: things and with experts, and the key to the role

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Speaker 1: is that it be important and then it be a

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Speaker 1: little volatile, and you're asking the question like, what's happened

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Speaker 1: to this role? And there are a couple of things

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Speaker 1: about experts that got me into it. Well one, I mean,

404
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Speaker 1: just to hook it up to the liars poker. I

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Speaker 1: have been bewildered by people's willingness to accept other people

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Speaker 1: ex experts since I was on Wall Street. But when

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Speaker 1: I was on the phone selling stuff to people and

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Speaker 1: professional investors would take what I said seriously when I

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Speaker 1: knew I didn't know what I was talking about. That

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Speaker 1: because I was at Solomon Brothers, I was the expert,

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Speaker 1: and so I I got So I think my interest

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Speaker 1: actually dates back to that, to the just how how

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Speaker 1: how fuzzy the whole concept is. And then of course,

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Speaker 1: like my whole literary career is based on finding true

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00:22:04,600 --> 00:22:07,800
Speaker 1: the best experts. I mean, it's one way of looking

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Speaker 1: at all the books I find. I find people who

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Speaker 1: actually know what's going on, who you might not think

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Speaker 1: are the people who know what's going on. Certainly true

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Speaker 1: the big short moneyball, I mean, it happens over and

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Speaker 1: over the PREMNISI exactly. It's it's it's it's surprising where

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Speaker 1: you find the expert I have found over and over again.

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Speaker 1: And it's often not the high status people. It's often

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Speaker 1: people who are buried away and no one knows who

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Speaker 1: they are. And so I wind up writing whole books

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Speaker 1: about people characters that the world thinks are in the

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00:22:41,040 --> 00:22:43,680
Speaker 1: beginning at least obscure until they make the movie about them.

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Speaker 1: But they are obscure to begin with. And and but

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Speaker 1: there they shouldn't be, because they are the one who

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Speaker 1: actually knows, say, how you value a baseball player, or

430
00:22:53,680 --> 00:22:56,640
Speaker 1: how you should manage a pandemic, or what's going on

431
00:22:56,640 --> 00:23:00,720
Speaker 1: on in in in sub prime mortgages in two thousand

432
00:23:00,720 --> 00:23:04,960
Speaker 1: and six, um. And so I think that's another source

433
00:23:05,000 --> 00:23:08,560
Speaker 1: of interest. Um. But but so that's got that got

434
00:23:08,560 --> 00:23:11,280
Speaker 1: me into it. But they are all these questions that

435
00:23:11,520 --> 00:23:17,560
Speaker 1: just seemed really worth exploring, starting with like the pandemic. Um.

436
00:23:17,720 --> 00:23:22,760
Speaker 1: Before the pandemic, the United States was like judged to

437
00:23:22,880 --> 00:23:28,480
Speaker 1: be by far the most expert in managing pandemics of

438
00:23:28,520 --> 00:23:31,119
Speaker 1: all countries on earth. But in a in a survey

439
00:23:31,160 --> 00:23:34,919
Speaker 1: that had been done, and you know, a year into it,

440
00:23:34,960 --> 00:23:37,960
Speaker 1: we have we have four pent of the world's population.

441
00:23:38,640 --> 00:23:40,960
Speaker 1: Of the world of death. We clearly didn't whatever that

442
00:23:41,000 --> 00:23:44,439
Speaker 1: expertise was, it didn't quite work. And I kind of

443
00:23:44,440 --> 00:23:46,720
Speaker 1: look at the world and I think over and our country,

444
00:23:47,040 --> 00:23:49,560
Speaker 1: and I think over and over again. We're demonstrating this

445
00:23:49,760 --> 00:23:54,359
Speaker 1: very strange ability to generate expertise, to generate knowledge and

446
00:23:54,640 --> 00:23:57,639
Speaker 1: not use it, or not understand it, or not identify

447
00:23:57,720 --> 00:24:01,560
Speaker 1: it or not respected. Um. So that gives me in

448
00:24:01,800 --> 00:24:03,600
Speaker 1: and and the nature of the podcast is different from

449
00:24:03,640 --> 00:24:05,400
Speaker 1: what you and I are doing, right, I mean, these

450
00:24:05,400 --> 00:24:09,800
Speaker 1: are I'm writing film script. Every episode is is I

451
00:24:09,840 --> 00:24:13,040
Speaker 1: mean a pain in the ass. It's every episode is.

452
00:24:13,080 --> 00:24:17,320
Speaker 1: It's what everyone's like. Everyone takes me about as long

453
00:24:17,359 --> 00:24:19,880
Speaker 1: as a long magazine article tak I interview a bunch

454
00:24:19,920 --> 00:24:22,720
Speaker 1: of people and try to make sense of some aspect

455
00:24:22,800 --> 00:24:25,400
Speaker 1: of this problem and try to tell it as a story.

456
00:24:25,600 --> 00:24:28,879
Speaker 1: And um, and so the seven episodes, each one is

457
00:24:28,920 --> 00:24:33,520
Speaker 1: a different story. And UM, I mean, like the one

458
00:24:33,520 --> 00:24:35,639
Speaker 1: that dropped this week to just give you, just to

459
00:24:35,640 --> 00:24:38,000
Speaker 1: give an idea of how it works. One that dropped

460
00:24:38,000 --> 00:24:40,399
Speaker 1: this week is an attempt to make a kind of

461
00:24:40,520 --> 00:24:46,879
Speaker 1: argument in story, um about why about this paradox and

462
00:24:46,880 --> 00:24:51,760
Speaker 1: the paradox is, they're all these fields where you can

463
00:24:51,800 --> 00:24:54,880
Speaker 1: see expertise has improved, where the experts are getting better

464
00:24:54,920 --> 00:24:57,919
Speaker 1: and better, but where people trust them less and less

465
00:24:58,359 --> 00:25:01,760
Speaker 1: or think they're actually say they're more. They're all I

466
00:25:01,760 --> 00:25:04,480
Speaker 1: think less and less of them. So medicine is a

467
00:25:04,480 --> 00:25:06,720
Speaker 1: really good example. Nurses and doctors will tell you that

468
00:25:06,800 --> 00:25:10,760
Speaker 1: for the last you know, fifteen years, they've felt they're

469
00:25:10,840 --> 00:25:14,320
Speaker 1: clearly more likely to help you than they were. You know,

470
00:25:14,600 --> 00:25:18,520
Speaker 1: every day they're learning stuff and uh, and yet every

471
00:25:18,600 --> 00:25:20,760
Speaker 1: day the people who walk in their office are more

472
00:25:20,800 --> 00:25:22,920
Speaker 1: likely to be armed with something from like web m

473
00:25:23,000 --> 00:25:25,159
Speaker 1: D they read that says the doctor doesn't know what

474
00:25:25,200 --> 00:25:28,800
Speaker 1: he's talking about. And um, but but you know, really

475
00:25:29,080 --> 00:25:31,600
Speaker 1: so that's complicated example, but a really simple example that's

476
00:25:31,680 --> 00:25:35,359
Speaker 1: kind of fun. Um talked to a really old weatherman,

477
00:25:35,520 --> 00:25:38,480
Speaker 1: someone who's been a meteorologist on TV for the last say,

478
00:25:38,560 --> 00:25:42,600
Speaker 1: fifty years, as we did, and they'll tell you that, um,

479
00:25:42,840 --> 00:25:46,879
Speaker 1: look fifty years ago, my forecast is basically sticking sticking

480
00:25:46,920 --> 00:25:48,920
Speaker 1: my head out the window and saying with the weather

481
00:25:49,160 --> 00:25:51,840
Speaker 1: was that that, yeah, I could kind of do it

482
00:25:51,840 --> 00:25:55,159
Speaker 1: a kind of okay, two or three day forecast, my

483
00:25:55,240 --> 00:25:58,080
Speaker 1: ten day forecast was just as good as guessing and

484
00:25:58,119 --> 00:26:00,560
Speaker 1: no better. And I certainly could and tell you like

485
00:26:00,560 --> 00:26:03,000
Speaker 1: where when tornadoes were gonna happen and where they were

486
00:26:03,040 --> 00:26:05,680
Speaker 1: going to hit. They can do all this stuff now.

487
00:26:05,800 --> 00:26:08,359
Speaker 1: They can be very precise about extreme whether their ten

488
00:26:08,440 --> 00:26:10,880
Speaker 1: day forecasts are pretty good, their three day forecasts are

489
00:26:10,960 --> 00:26:14,360
Speaker 1: multiples more accurate than they used to be. But they

490
00:26:14,480 --> 00:26:16,560
Speaker 1: used But they'll also say, we used to get on

491
00:26:16,640 --> 00:26:19,760
Speaker 1: TV and speak with total certainty, like Ron Burgundy. We

492
00:26:19,800 --> 00:26:23,800
Speaker 1: were like puffed up, important, confident people. Now we speak

493
00:26:23,840 --> 00:26:27,080
Speaker 1: because we understand that we really understand things. We're kind

494
00:26:27,080 --> 00:26:29,880
Speaker 1: of talking in terms of probabilities and uncertainties, and we're

495
00:26:29,880 --> 00:26:34,080
Speaker 1: expressing uncertainty and the audience. The way the audience has

496
00:26:34,160 --> 00:26:38,800
Speaker 1: responded is you like to doubt the more. Uh. So

497
00:26:39,440 --> 00:26:42,520
Speaker 1: the podcast is about how people don't really think probabilistically

498
00:26:42,760 --> 00:26:44,840
Speaker 1: and and if you give them, if you tell them

499
00:26:44,880 --> 00:26:48,359
Speaker 1: there's uh chance of rain and it rains, they think

500
00:26:48,400 --> 00:26:49,840
Speaker 1: you don't know what you're talking about it they don't

501
00:26:49,880 --> 00:26:52,960
Speaker 1: understand what that means. And so I think so much

502
00:26:53,119 --> 00:26:56,879
Speaker 1: modern expertise. One answer to the question why the expertise

503
00:26:56,920 --> 00:26:59,200
Speaker 1: is getting better and better and why people understand it

504
00:26:59,280 --> 00:27:02,119
Speaker 1: less and less is the nature of the expertise. The

505
00:27:02,160 --> 00:27:05,800
Speaker 1: expertise is very is probabilistic and data based, and it's

506
00:27:05,880 --> 00:27:09,000
Speaker 1: it's a you know, in grand historic terms, data is

507
00:27:09,040 --> 00:27:12,879
Speaker 1: a relatively new phenomenon, and people really don't understand when

508
00:27:12,960 --> 00:27:16,560
Speaker 1: Nate Silver says, you know, Hillary Clinton has a seventies

509
00:27:16,560 --> 00:27:19,520
Speaker 1: seven percent chance of beating Donald Trump and Trump wins.

510
00:27:19,560 --> 00:27:21,560
Speaker 1: They think Nate Silver doesn't know where he's talking about.

511
00:27:21,680 --> 00:27:24,359
Speaker 1: What they should say is well, Nate Silver was actually

512
00:27:24,440 --> 00:27:26,200
Speaker 1: a little more bush on Trump than all the people

513
00:27:26,200 --> 00:27:29,760
Speaker 1: on TV, and in his model, Trump won almost three

514
00:27:29,760 --> 00:27:34,000
Speaker 1: out of ten times. So it's it's um, it's so

515
00:27:34,040 --> 00:27:37,600
Speaker 1: it's exploring this phenomenon, this this problem people have with

516
00:27:37,760 --> 00:27:40,680
Speaker 1: problems with experts who talk in terms of probabilities. And

517
00:27:41,080 --> 00:27:44,320
Speaker 1: you and I discuss this when we did the podcast

518
00:27:44,440 --> 00:27:47,880
Speaker 1: after the Undoing Project that if someone goes on TV

519
00:27:48,000 --> 00:27:52,840
Speaker 1: and says something bold with a lot of confidence, they're

520
00:27:52,880 --> 00:27:55,560
Speaker 1: believed more by the audience. And the person who comes

521
00:27:55,560 --> 00:27:58,040
Speaker 1: out and says, well, you know, there's a sixty percent

522
00:27:58,160 --> 00:28:00,320
Speaker 1: chance this could happen, and there's a probably if that

523
00:28:00,320 --> 00:28:04,280
Speaker 1: can happen, they're perceived as wishy washy not. Not only

524
00:28:04,600 --> 00:28:10,200
Speaker 1: does the person who expresses certainty, usually stupidly, um, get believed,

525
00:28:10,560 --> 00:28:12,840
Speaker 1: they're much more likely to be on TV. When the

526
00:28:12,840 --> 00:28:15,439
Speaker 1: TV producer calls you up if you say maybe this

527
00:28:15,520 --> 00:28:18,119
Speaker 1: and maybe that, they just don't invite you on TV.

528
00:28:18,640 --> 00:28:21,399
Speaker 1: TV wants you to come on and be certain, uh

529
00:28:21,400 --> 00:28:26,040
Speaker 1: and bold and interesting. Uh So it's um, it is.

530
00:28:26,160 --> 00:28:32,160
Speaker 1: It's screwy how we don't we should respect experts who

531
00:28:32,240 --> 00:28:36,879
Speaker 1: expressed doubts, even in their own understanding of the world,

532
00:28:37,640 --> 00:28:42,000
Speaker 1: far more than experts who seem really confident. Uh. That

533
00:28:42,040 --> 00:28:44,200
Speaker 1: should be like a that should be the bias, not

534
00:28:44,320 --> 00:28:49,040
Speaker 1: the opposite. Um. And instead we were we reward this

535
00:28:49,120 --> 00:28:53,440
Speaker 1: phony certainty, this phony confidence. We think we think it is,

536
00:28:54,200 --> 00:28:56,959
Speaker 1: we think it reflects a deep understanding. We sort of

537
00:28:57,240 --> 00:28:58,680
Speaker 1: we sort of get bluffed all the time at the

538
00:28:58,720 --> 00:29:03,440
Speaker 1: poker table. Um, instead of realizing that this is a bluff. Um.

539
00:29:03,440 --> 00:29:06,040
Speaker 1: And the person, of course, oftentimes the person who's expressing

540
00:29:06,080 --> 00:29:08,640
Speaker 1: total certainly thinks they're right. It isn't that they're lying,

541
00:29:09,000 --> 00:29:13,560
Speaker 1: it's that they actually actually they know they they know

542
00:29:13,720 --> 00:29:16,320
Speaker 1: little enough about what they're talking about to sound certain

543
00:29:16,360 --> 00:29:20,360
Speaker 1: about it, often wrong, never in doubt, often wrong, never

544
00:29:20,400 --> 00:29:24,000
Speaker 1: in doubt that there is Um a quote of yours

545
00:29:24,080 --> 00:29:26,160
Speaker 1: from I don't remember it was the first or second

546
00:29:26,160 --> 00:29:30,200
Speaker 1: episode this season about how challenging it is to find

547
00:29:30,240 --> 00:29:34,760
Speaker 1: the experts, and the line that you uses your job

548
00:29:35,040 --> 00:29:39,080
Speaker 1: is to find the L six explain what the L

549
00:29:39,200 --> 00:29:43,160
Speaker 1: six is. And and this I specifically is the person

550
00:29:43,240 --> 00:29:47,800
Speaker 1: who ends up saving thousands of lives via the Coast

551
00:29:47,840 --> 00:29:52,560
Speaker 1: Guard because he changes the way we look for missing voters.

552
00:29:53,960 --> 00:29:57,320
Speaker 1: So those are you're conflating two episodes here, Uh yeah,

553
00:29:57,400 --> 00:29:59,880
Speaker 1: the ALL six. The L six episode is about a woman,

554
00:30:00,240 --> 00:30:02,080
Speaker 1: a woman who figures out how to get money out

555
00:30:02,120 --> 00:30:05,920
Speaker 1: of insurance companies. Me. But but you know what, the

556
00:30:06,080 --> 00:30:08,920
Speaker 1: it's also true that the guy in the Coast Guard

557
00:30:09,080 --> 00:30:11,920
Speaker 1: is an L six, uh six, and L six is

558
00:30:11,960 --> 00:30:14,959
Speaker 1: six levels down in the organization. And this is an

559
00:30:14,960 --> 00:30:20,000
Speaker 1: insight that I first heard from an entrepreneur named Todd Park.

560
00:30:20,280 --> 00:30:24,840
Speaker 1: And Todd Park had Um has created I think three

561
00:30:24,880 --> 00:30:28,920
Speaker 1: different multibillion dollar companies in the healthcare industry, and in addition,

562
00:30:29,000 --> 00:30:31,960
Speaker 1: he was chief Technology Officer for the United States and

563
00:30:32,000 --> 00:30:35,360
Speaker 1: the Obama administration. And Tod Park said to me, and

564
00:30:35,440 --> 00:30:37,360
Speaker 1: the story we tell in the first episode is his

565
00:30:37,440 --> 00:30:40,520
Speaker 1: first company and it's the story of he's trying to

566
00:30:40,560 --> 00:30:45,640
Speaker 1: create um a business where he makes pregnancy less dangerous,

567
00:30:45,800 --> 00:30:48,880
Speaker 1: more pleasant for women and and cuts the cost of

568
00:30:48,960 --> 00:30:53,400
Speaker 1: catastrophic outcomes by basically caring for the mom better and

569
00:30:53,600 --> 00:30:57,040
Speaker 1: buys a pregnancy clinic in San Diego. And it's catastrophe

570
00:30:57,040 --> 00:30:59,760
Speaker 1: because it's a catastrophe because one the insurers won't pay

571
00:30:59,800 --> 00:31:03,400
Speaker 1: him and make pregnancy more pleasant, and to the clinic

572
00:31:03,440 --> 00:31:05,959
Speaker 1: itself isn't getting paid for the work it's doing. And

573
00:31:05,960 --> 00:31:08,440
Speaker 1: he realizes that the problem he really needs to solve

574
00:31:08,920 --> 00:31:12,240
Speaker 1: is medical billing, that all around the country the insurance

575
00:31:12,240 --> 00:31:15,240
Speaker 1: industry has gotten so complicated, and how it responds to

576
00:31:15,320 --> 00:31:18,800
Speaker 1: doctor's claims that doctors aren't getting paid. And he finds

577
00:31:18,880 --> 00:31:22,120
Speaker 1: burying a basement in the hospital in Boston, this woman

578
00:31:22,160 --> 00:31:26,080
Speaker 1: who has mastered the complexity the thousands of different insurance

579
00:31:26,120 --> 00:31:29,880
Speaker 1: programs and the thousands of different permutations on the programs,

580
00:31:30,280 --> 00:31:34,240
Speaker 1: and it's just got a gift for getting paid, uh

581
00:31:34,360 --> 00:31:36,920
Speaker 1: knowing how to handle the complexity. Her name is Sue Henderson.

582
00:31:37,480 --> 00:31:39,920
Speaker 1: And he realized that like on the ORG chart of

583
00:31:39,960 --> 00:31:43,720
Speaker 1: the hospital, she's six levels down. But without her, the

584
00:31:43,760 --> 00:31:47,840
Speaker 1: hospitals that goes bankrupt, and the hospital itself doesn't think,

585
00:31:47,880 --> 00:31:52,000
Speaker 1: it doesn't understand why it's business is working. And Todd

586
00:31:52,000 --> 00:31:56,200
Speaker 1: extrapolates from this and realizes that in big systems and

587
00:31:56,240 --> 00:32:01,080
Speaker 1: big corporations and big agencies and government that at when

588
00:32:01,120 --> 00:32:04,280
Speaker 1: there is a crisis, when there is a problem and

589
00:32:04,360 --> 00:32:08,040
Speaker 1: you're looking for the expertise to solve the problem, to

590
00:32:08,120 --> 00:32:11,960
Speaker 1: answer the question, it's never at the top of the organization.

591
00:32:12,480 --> 00:32:15,880
Speaker 1: It's always some someone low in the organization who has

592
00:32:15,920 --> 00:32:24,000
Speaker 1: some specific knowledge. And when you have, when you have uh,

593
00:32:24,320 --> 00:32:28,760
Speaker 1: hierarchical organization, not a flat organization, that knowledge, the expertise

594
00:32:28,800 --> 00:32:33,600
Speaker 1: has unbelievable difficulty in finding its way into the decision

595
00:32:33,680 --> 00:32:38,680
Speaker 1: maker's hands. Um. And so Todd sets out to kind

596
00:32:38,680 --> 00:32:41,560
Speaker 1: of build a career on this insight, and they're really

597
00:32:41,600 --> 00:32:45,280
Speaker 1: spectacular results he gets. He gets called in when when

598
00:32:45,360 --> 00:32:49,040
Speaker 1: Obamacare fails on the first day, when the website crashes,

599
00:32:49,520 --> 00:32:51,600
Speaker 1: and it's a it's like one of the one of

600
00:32:51,640 --> 00:32:54,440
Speaker 1: the catastrophes of the Obama presidency. Right, he goes all

601
00:32:54,480 --> 00:32:57,960
Speaker 1: the trouble of getting getting the thing passed and and

602
00:32:58,120 --> 00:33:01,560
Speaker 1: now the website crashes to is I think it's that

603
00:33:01,640 --> 00:33:06,680
Speaker 1: point CTO of the country, and he knows, don't ask

604
00:33:06,720 --> 00:33:09,280
Speaker 1: the people who are a top goes go go six

605
00:33:09,360 --> 00:33:11,920
Speaker 1: levels down to ask who understands how this software works,

606
00:33:12,240 --> 00:33:15,080
Speaker 1: and he finally finds six levels down contractors for the

607
00:33:15,120 --> 00:33:18,160
Speaker 1: government who who can solve the problem. But over and

608
00:33:18,240 --> 00:33:21,320
Speaker 1: over he finds that you've got to go to these people,

609
00:33:21,520 --> 00:33:25,959
Speaker 1: and so it raises like this bigger issue about expertise.

610
00:33:26,040 --> 00:33:29,440
Speaker 1: I think, um, when you live in a society that's

611
00:33:29,480 --> 00:33:32,600
Speaker 1: more or less equal, where where the persons six levels

612
00:33:32,640 --> 00:33:34,960
Speaker 1: down is not all that far away in status from

613
00:33:34,960 --> 00:33:37,600
Speaker 1: the person at the top and pay in the way

614
00:33:37,720 --> 00:33:40,040
Speaker 1: people look at them in their sense of self importance,

615
00:33:40,680 --> 00:33:44,800
Speaker 1: there's a freer flow of conversation information. It's easier for

616
00:33:44,840 --> 00:33:46,520
Speaker 1: the L six to get what they know into the

617
00:33:46,520 --> 00:33:49,440
Speaker 1: head of the all one. But when you literally live

618
00:33:49,480 --> 00:33:53,040
Speaker 1: in an increasingly unequal society where the CEO is being

619
00:33:53,040 --> 00:33:55,560
Speaker 1: paid thirty million dollars and the L six is being

620
00:33:55,560 --> 00:33:59,120
Speaker 1: paid fifty thou and is regarded as you know, an

621
00:33:59,160 --> 00:34:04,240
Speaker 1: interchangeable art um, it's harder. And I think that part

622
00:34:04,240 --> 00:34:08,640
Speaker 1: of our problem in unearthing expertise is a problem with inequality. UM.

623
00:34:08,840 --> 00:34:10,840
Speaker 1: But we that that we get it, that only elliptically.

624
00:34:11,120 --> 00:34:14,440
Speaker 1: The story of this woman kind of coming in a

625
00:34:14,520 --> 00:34:18,919
Speaker 1: completely unknown, unsung person and what's in her head, going

626
00:34:18,920 --> 00:34:22,279
Speaker 1: into software and creating a multi billion dollar company called

627
00:34:22,280 --> 00:34:26,399
Speaker 1: the Sene Health is a spectacular story. And and so

628
00:34:26,920 --> 00:34:30,239
Speaker 1: that's the first episode of the season. So now you're

629
00:34:30,400 --> 00:34:33,919
Speaker 1: you're almost done with season three. How do you like

630
00:34:34,640 --> 00:34:38,959
Speaker 1: the sort of scripted podcast format that you're doing it?

631
00:34:38,960 --> 00:34:42,600
Speaker 1: It seems a whole lot more collaborative than sitting alone

632
00:34:42,640 --> 00:34:46,319
Speaker 1: and typing in your your office at home. It's a

633
00:34:46,400 --> 00:34:49,799
Speaker 1: perfect palate cleanser cleanser between books because it does a

634
00:34:49,840 --> 00:34:53,040
Speaker 1: couple of things, and it is collaborative. It does work

635
00:34:53,080 --> 00:34:55,359
Speaker 1: different muscles because you're writing for the year rather than

636
00:34:55,400 --> 00:34:58,000
Speaker 1: the eye, and the year is a more. It's a more,

637
00:34:58,360 --> 00:35:01,640
Speaker 1: it's got a it's it's got a different emotional palette

638
00:35:01,680 --> 00:35:05,919
Speaker 1: than the It really responds differently to emotion you hear,

639
00:35:06,239 --> 00:35:09,720
Speaker 1: you hear the emotion in people's voices. It rewards emotion

640
00:35:10,080 --> 00:35:12,880
Speaker 1: um and so I like being pulled in that direction

641
00:35:13,760 --> 00:35:19,200
Speaker 1: for the podcast. I love I love the storytelling challenge

642
00:35:19,719 --> 00:35:22,080
Speaker 1: of writing these scripts. I think it's just really useful

643
00:35:22,120 --> 00:35:25,920
Speaker 1: for me. It's just it's a different it's it's um

644
00:35:25,960 --> 00:35:28,359
Speaker 1: it's in some ways looser some way it's tighter than

645
00:35:28,520 --> 00:35:31,719
Speaker 1: what happens with with when I'm writing a book. But

646
00:35:31,800 --> 00:35:35,200
Speaker 1: it's it is cross training. It's like working different muscles.

647
00:35:35,239 --> 00:35:37,759
Speaker 1: So I really like doing them. I wouldn't want to

648
00:35:37,800 --> 00:35:41,800
Speaker 1: just do them. I think alternating between books and podcast

649
00:35:41,880 --> 00:35:44,279
Speaker 1: seasons is a really good thing, is really good for me,

650
00:35:44,520 --> 00:35:48,479
Speaker 1: really healthy. A year ago, or barely a year ago,

651
00:35:48,719 --> 00:35:52,879
Speaker 1: you released The Premonition, a Pandemic story, which was all

652
00:35:52,920 --> 00:35:58,200
Speaker 1: about America's history with pandemics and how well prepared we

653
00:35:58,200 --> 00:36:02,360
Speaker 1: were for the coronavirus rest. So, so it's been a

654
00:36:02,480 --> 00:36:06,200
Speaker 1: year since the book has come out, and probably two

655
00:36:06,280 --> 00:36:08,640
Speaker 1: years since you first sat down to start writing it.

656
00:36:09,560 --> 00:36:15,279
Speaker 1: How do you think it's held up in the ensuing decades. Well,

657
00:36:15,320 --> 00:36:17,640
Speaker 1: it was a story that was designed to hold up

658
00:36:17,680 --> 00:36:21,360
Speaker 1: in this way that I knew that it ended in

659
00:36:22,320 --> 00:36:26,920
Speaker 1: May of two thousand, of two thousand and twenty, So

660
00:36:27,160 --> 00:36:30,600
Speaker 1: it ended once it was clear that the United States

661
00:36:30,640 --> 00:36:34,239
Speaker 1: had screwed up its response. Uh, and that most of

662
00:36:34,280 --> 00:36:39,279
Speaker 1: what comes before is characters kind of showing you why

663
00:36:39,400 --> 00:36:42,520
Speaker 1: the response was going to be screwed up. So and

664
00:36:42,640 --> 00:36:47,279
Speaker 1: that's and so it didn't depend It didn't depend on

665
00:36:47,320 --> 00:36:50,920
Speaker 1: anything after that. It really is. It was the story

666
00:36:51,000 --> 00:36:53,040
Speaker 1: was kind of over when I wrote it, which sounds

667
00:36:53,080 --> 00:36:58,600
Speaker 1: strange because the pandemic is not over. Um the UM.

668
00:36:58,640 --> 00:37:03,440
Speaker 1: I'm disappointed with the the the effect of the book

669
00:37:03,880 --> 00:37:07,640
Speaker 1: in that I thought I'd watched the big short have

670
00:37:07,680 --> 00:37:09,520
Speaker 1: a very big effect. I don't know it was exactly

671
00:37:09,600 --> 00:37:13,480
Speaker 1: the right effect, but I thought that there was such

672
00:37:13,520 --> 00:37:16,839
Speaker 1: an obvious response to the stories. It wasn't you know

673
00:37:16,960 --> 00:37:19,160
Speaker 1: what I was saying with the characters were saying, who

674
00:37:19,160 --> 00:37:22,160
Speaker 1: were clearly the people among the people we should have

675
00:37:22,200 --> 00:37:25,759
Speaker 1: been listening to going into the pandemic, uh, and that

676
00:37:25,960 --> 00:37:29,840
Speaker 1: they were saying that the CDC has ceased to do

677
00:37:30,160 --> 00:37:32,200
Speaker 1: what it what you think it does. It does not

678
00:37:32,280 --> 00:37:36,319
Speaker 1: control disease. It observes and reports on disease. It's not

679
00:37:36,480 --> 00:37:40,800
Speaker 1: set up to be battlefield command in a pandemic. And

680
00:37:41,080 --> 00:37:44,640
Speaker 1: so the first thing you do is create this creates

681
00:37:44,640 --> 00:37:49,000
Speaker 1: something new that does respond uh to a pandemic, and

682
00:37:49,040 --> 00:37:51,520
Speaker 1: you acknowledge this isn't what goes on in the CDC,

683
00:37:52,280 --> 00:37:54,600
Speaker 1: and instead sent it's trying to pour more money into

684
00:37:54,600 --> 00:37:57,919
Speaker 1: into the CDC. That surprised me. I thought I thought

685
00:37:57,960 --> 00:38:00,640
Speaker 1: the book might stop such stuff from happening. So I'm

686
00:38:00,719 --> 00:38:04,840
Speaker 1: kind of disappointed. I'm kind of disappointed in that. Um

687
00:38:05,040 --> 00:38:08,640
Speaker 1: the second and kind of this isn't the fault to

688
00:38:08,840 --> 00:38:11,600
Speaker 1: the book, but it's it's it's a curious aspect of

689
00:38:11,640 --> 00:38:15,200
Speaker 1: our society that one of the things the book points

690
00:38:15,239 --> 00:38:19,480
Speaker 1: out that I find riveting. One of the characters had

691
00:38:19,520 --> 00:38:23,799
Speaker 1: gone back, you know, uh, this was now fifteen years ago.

692
00:38:23,840 --> 00:38:26,080
Speaker 1: He'd gone back and looked at what happened in nineteen

693
00:38:26,160 --> 00:38:31,080
Speaker 1: eighteen in the pandemic and realized that the people then

694
00:38:31,400 --> 00:38:34,759
Speaker 1: at the end of their pandemic hadn't fully understand what

695
00:38:34,840 --> 00:38:38,640
Speaker 1: it actually happened that they did. They didn't understand, in particular,

696
00:38:39,160 --> 00:38:41,440
Speaker 1: that the things they had done to slow disease and

697
00:38:41,480 --> 00:38:45,759
Speaker 1: prevent death, like closing churches and schools and saloons and

698
00:38:45,840 --> 00:38:50,120
Speaker 1: social distancing stuff wearing masks, had actually really worked and

699
00:38:50,200 --> 00:38:56,160
Speaker 1: explained differences in death rates between cities in America. And

700
00:38:56,480 --> 00:38:59,120
Speaker 1: they hadn't. They hadn't. They just thought, well, there were

701
00:38:59,160 --> 00:39:02,400
Speaker 1: deaths everywhere, it's hard to see the effects of these things.

702
00:39:02,719 --> 00:39:06,200
Speaker 1: They didn't have the data whatever, um, But they hadn't

703
00:39:06,200 --> 00:39:09,200
Speaker 1: really done a postmortem that enabled them to be prepared

704
00:39:09,320 --> 00:39:12,280
Speaker 1: if it happened again, like what worked and what didn't?

705
00:39:12,719 --> 00:39:14,960
Speaker 1: And it seemed to me, I described that what this

706
00:39:15,000 --> 00:39:17,239
Speaker 1: guy does and some at some length it seems to

707
00:39:17,239 --> 00:39:19,799
Speaker 1: me like a natural thing for us to be doing

708
00:39:19,840 --> 00:39:22,879
Speaker 1: now and we're not doing it. Uh, And I can't

709
00:39:22,920 --> 00:39:25,480
Speaker 1: I can't. I can't quite believe it. I mean, I

710
00:39:25,520 --> 00:39:27,879
Speaker 1: can't believe that no one's asking why the death rate

711
00:39:27,920 --> 00:39:30,759
Speaker 1: in Miami is three and a half times the death

712
00:39:30,840 --> 00:39:33,759
Speaker 1: rates in San Francisco, or or why the death rate

713
00:39:33,880 --> 00:39:36,600
Speaker 1: in in the red counties out here in California that

714
00:39:36,880 --> 00:39:40,200
Speaker 1: didn't comply with public health orders is double or triple

715
00:39:40,320 --> 00:39:43,279
Speaker 1: the death rate in the blue counties that did you know?

716
00:39:43,400 --> 00:39:46,840
Speaker 1: I It may it may not be that the social

717
00:39:46,840 --> 00:39:49,680
Speaker 1: distancing worked. There may be some other explanation, but we

718
00:39:49,719 --> 00:39:53,360
Speaker 1: need to know it because there were really different outcomes

719
00:39:53,400 --> 00:39:56,719
Speaker 1: from place to place, and it's and I think we

720
00:39:56,760 --> 00:40:00,440
Speaker 1: need ununderstand why. So so let's bring this back to

721
00:40:00,520 --> 00:40:05,880
Speaker 1: our previous conversation about experts. It seems that the pandemic

722
00:40:06,040 --> 00:40:10,239
Speaker 1: has led to even greater mistrust for experts, Or am

723
00:40:10,239 --> 00:40:14,320
Speaker 1: I saying that backwards? Did the pandemic reveal a mistrust

724
00:40:14,400 --> 00:40:20,040
Speaker 1: that was already there. You know, what it revealed was

725
00:40:20,440 --> 00:40:25,239
Speaker 1: an L six problem, that the that there was so

726
00:40:25,440 --> 00:40:30,680
Speaker 1: little honest concern about pandemics for such a long time,

727
00:40:31,520 --> 00:40:35,320
Speaker 1: that we had shoved the that the role, the actual

728
00:40:35,520 --> 00:40:40,800
Speaker 1: job of controlling communicable disease, of preventing disease from moving

729
00:40:40,840 --> 00:40:44,080
Speaker 1: from person to person, had been shoved down on local

730
00:40:44,120 --> 00:40:47,560
Speaker 1: public health officers who had very who had very little

731
00:40:47,600 --> 00:40:52,080
Speaker 1: social cloud, poorly paid, no one knew who they were, uh,

732
00:40:52,120 --> 00:40:57,640
Speaker 1: you know, not important people, and so they You know,

733
00:40:57,640 --> 00:41:01,960
Speaker 1: if you want to find expertise in actually controlling communicable disease,

734
00:41:02,160 --> 00:41:06,520
Speaker 1: you go inside you're really who nobody does, inside your

735
00:41:06,600 --> 00:41:09,240
Speaker 1: local public health office, and you talk to the local

736
00:41:09,280 --> 00:41:12,200
Speaker 1: public health officer who handled the measles outbreak at the school,

737
00:41:12,320 --> 00:41:16,320
Speaker 1: or or or the you know, drug multi drug resistant

738
00:41:16,320 --> 00:41:21,279
Speaker 1: tuberculosis outbreak in the bad neighborhood. You know, it's it's um.

739
00:41:21,320 --> 00:41:23,560
Speaker 1: They've been doing this and they have been very aware

740
00:41:23,719 --> 00:41:27,680
Speaker 1: of the political consequences of trying to constrain people's movements

741
00:41:28,080 --> 00:41:30,480
Speaker 1: and very aware of how you actually stop people from

742
00:41:30,480 --> 00:41:32,719
Speaker 1: getting sick and dying. And they've been they're they've been

743
00:41:32,719 --> 00:41:36,040
Speaker 1: fighting battles. So this war breaks out and to this

744
00:41:36,200 --> 00:41:39,319
Speaker 1: day we have not acknowledged to those are the people

745
00:41:39,320 --> 00:41:41,520
Speaker 1: who should be in front of the Senate talking about it,

746
00:41:41,719 --> 00:41:44,200
Speaker 1: or or on a commission riding up a plan for

747
00:41:44,239 --> 00:41:47,080
Speaker 1: the country. It isn't kind of grand pubas who are

748
00:41:47,080 --> 00:41:50,560
Speaker 1: floating around Washington. It's people at the local level who

749
00:41:50,719 --> 00:41:53,839
Speaker 1: who we should surface as the experts. And they were

750
00:41:53,840 --> 00:41:56,440
Speaker 1: the experts going in and they got slaughtered because they

751
00:41:56,440 --> 00:41:58,880
Speaker 1: didn't have the social authority that you know. And what

752
00:41:59,000 --> 00:42:02,040
Speaker 1: happened is in various states around the country, their their

753
00:42:02,120 --> 00:42:04,560
Speaker 1: legal authority is being dialed back, which I think is

754
00:42:04,560 --> 00:42:08,400
Speaker 1: a catastrophe. I think that that that that removing the

755
00:42:08,480 --> 00:42:10,880
Speaker 1: authority from the expert to do what needs to be

756
00:42:10,920 --> 00:42:13,719
Speaker 1: done if there's a disease operak in your neighborhood is

757
00:42:13,840 --> 00:42:15,959
Speaker 1: really a bad idea. To leave it in the hands

758
00:42:15,960 --> 00:42:18,839
Speaker 1: of politicians is really a bad idea. Well, let's talk

759
00:42:18,840 --> 00:42:22,279
Speaker 1: about one of those local experts who you surfaced. Um.

760
00:42:22,400 --> 00:42:25,480
Speaker 1: Charity Dean is one of the key characters in the book.

761
00:42:26,160 --> 00:42:29,479
Speaker 1: I actually got to interview her at a conference last

762
00:42:29,480 --> 00:42:33,560
Speaker 1: weekend of all places, Miami, since you mentioned it, and

763
00:42:33,680 --> 00:42:37,680
Speaker 1: she is saying that given the b A to omicron

764
00:42:37,880 --> 00:42:42,960
Speaker 1: variant that's starting to show up both in hospitals and

765
00:42:43,040 --> 00:42:46,960
Speaker 1: in in waste treatment um plants, which she believes we

766
00:42:47,000 --> 00:42:50,280
Speaker 1: should be checking lots and lots more of. She's looking

767
00:42:50,320 --> 00:42:52,880
Speaker 1: for a surgeon in May and June. Tell us a

768
00:42:52,880 --> 00:42:57,600
Speaker 1: little bit about how you found charity Dean. Yeah, the

769
00:42:58,040 --> 00:43:01,800
Speaker 1: the charity Dean was a is a wonderful character because

770
00:43:01,840 --> 00:43:05,480
Speaker 1: she dramatizes the central problem is just how brave you

771
00:43:05,560 --> 00:43:07,560
Speaker 1: have to be as a local public health officer to

772
00:43:07,600 --> 00:43:09,759
Speaker 1: really do your job. Well, nobody should have to be

773
00:43:09,840 --> 00:43:12,719
Speaker 1: as brave as she had to be. And um, she

774
00:43:13,239 --> 00:43:17,160
Speaker 1: but I found how I found her. It's kind of funny. Um.

775
00:43:17,200 --> 00:43:21,240
Speaker 1: At the beginning of the pandemic, I thought I should

776
00:43:21,320 --> 00:43:25,080
Speaker 1: be looking into this as a subject because I the

777
00:43:25,120 --> 00:43:27,640
Speaker 1: book before the Premonition was the Fifth Risk, and was

778
00:43:27,680 --> 00:43:32,560
Speaker 1: about how the government manages or doesn't manage or uh

779
00:43:32,719 --> 00:43:35,799
Speaker 1: existential risks, how the federal government, how the tools we

780
00:43:35,880 --> 00:43:39,200
Speaker 1: have at the federal level have been allowed to decay

781
00:43:39,239 --> 00:43:43,120
Speaker 1: and offify and so so, and what were the consequences

782
00:43:43,120 --> 00:43:45,920
Speaker 1: of that. Well, here this existential risk pop pops up,

783
00:43:45,960 --> 00:43:48,040
Speaker 1: and I think, well, it's an example of kind of

784
00:43:48,040 --> 00:43:50,200
Speaker 1: what I was writing about. Let's see, let's see if

785
00:43:50,200 --> 00:43:55,160
Speaker 1: there's a story here, And Charity was the last character

786
00:43:55,239 --> 00:43:58,840
Speaker 1: I found of the main characters, and every other main character,

787
00:43:59,320 --> 00:44:02,440
Speaker 1: UM Joe to you see a prominent viral prominent um

788
00:44:03,480 --> 00:44:07,760
Speaker 1: virus hunter. Basically at UCSF UM a group of doctors

789
00:44:07,880 --> 00:44:10,359
Speaker 1: they called themselves the Wolverines who had written the US

790
00:44:10,440 --> 00:44:17,120
Speaker 1: Pandemic plan um uh. Various people all said to me, Look,

791
00:44:17,200 --> 00:44:19,120
Speaker 1: if you want to get to the guts of this,

792
00:44:19,760 --> 00:44:22,160
Speaker 1: you've got to meet Charity Dean, because we met her,

793
00:44:22,200 --> 00:44:25,560
Speaker 1: and she knows more more about like how to actually

794
00:44:25,600 --> 00:44:27,560
Speaker 1: manage this in the middle of you know, in the

795
00:44:27,600 --> 00:44:31,680
Speaker 1: fog of war than anybody. But Charity Deane herself was

796
00:44:31,719 --> 00:44:35,040
Speaker 1: an L six. She was buried inside the State of

797
00:44:35,080 --> 00:44:37,520
Speaker 1: California Health Department, and she wasn't even running it. She

798
00:44:37,600 --> 00:44:40,560
Speaker 1: was she was actually exactly six levels down from Gavin

799
00:44:40,600 --> 00:44:44,680
Speaker 1: Newsom and and was being in January of two thousand

800
00:44:44,760 --> 00:44:50,799
Speaker 1: twenty forbidden from using the word pandemic and banned from

801
00:44:50,800 --> 00:44:53,359
Speaker 1: the meetings where they were discussing what would happen if

802
00:44:53,360 --> 00:44:55,279
Speaker 1: this was this thing that was happening in China was

803
00:44:55,320 --> 00:44:59,200
Speaker 1: actually serious. She had already figured out it was very serious,

804
00:44:59,560 --> 00:45:02,120
Speaker 1: and it was already thinking about strategies to deal with it,

805
00:45:02,200 --> 00:45:05,279
Speaker 1: and she was being excluded from the conversations that that

806
00:45:05,520 --> 00:45:08,320
Speaker 1: we're happening in California for the first couple of months

807
00:45:08,320 --> 00:45:12,040
Speaker 1: of this thing, and um, and so I wrote her,

808
00:45:12,560 --> 00:45:14,880
Speaker 1: I have an email somewhere where I wrote to the

809
00:45:14,920 --> 00:45:17,719
Speaker 1: Department of Public Health in like, oh, I don't know May,

810
00:45:17,960 --> 00:45:21,040
Speaker 1: April or May, and said I really want to interview

811
00:45:21,200 --> 00:45:24,440
Speaker 1: Charity Dean. And I got a note back saying she

812
00:45:24,520 --> 00:45:26,680
Speaker 1: doesn't want to. She's she's unable to talk to you.

813
00:45:27,040 --> 00:45:29,040
Speaker 1: I'm afraid that that's not going to happen. And it

814
00:45:29,120 --> 00:45:31,719
Speaker 1: wasn't from her, so I put it to one side.

815
00:45:31,760 --> 00:45:33,120
Speaker 1: I thought it was too bad, you don't want to

816
00:45:33,120 --> 00:45:36,000
Speaker 1: talk to me, And then I got it annoyed me,

817
00:45:36,440 --> 00:45:38,480
Speaker 1: And like a month later I managed to get her

818
00:45:38,480 --> 00:45:40,799
Speaker 1: cell phone and I texted her and she said, they

819
00:45:40,840 --> 00:45:43,279
Speaker 1: never sent me, they never asked me, they never told

820
00:45:43,280 --> 00:45:44,799
Speaker 1: me that you would call it. I'm happy to talk

821
00:45:44,800 --> 00:45:50,120
Speaker 1: to you and uh and thus began this, I mean,

822
00:45:50,480 --> 00:45:54,120
Speaker 1: an exploration of the character who I would argue might

823
00:45:54,160 --> 00:45:57,800
Speaker 1: be the best character I have ever had for any book. Um,

824
00:45:57,840 --> 00:46:02,040
Speaker 1: just spectacular and and who took que two to the

825
00:46:02,120 --> 00:46:06,120
Speaker 1: nub of the problem in our pandemic response. UM, And

826
00:46:06,160 --> 00:46:07,640
Speaker 1: I tell you what among the other things that A

827
00:46:07,719 --> 00:46:11,120
Speaker 1: surprised that surprised me about writing the premonition. When you

828
00:46:11,160 --> 00:46:14,880
Speaker 1: go and spend time with someone who is a local

829
00:46:14,960 --> 00:46:18,200
Speaker 1: public health officer, just asked them to tell you stories

830
00:46:18,239 --> 00:46:23,200
Speaker 1: from their day or their career, it is so dramatic.

831
00:46:23,840 --> 00:46:26,880
Speaker 1: I mean, it's it's guns and violence and scary stuff

832
00:46:26,920 --> 00:46:29,839
Speaker 1: and people dying of disease and squirrelly doctors who were

833
00:46:30,120 --> 00:46:33,319
Speaker 1: with dirty needles who are giving people hepatitis. It's it's

834
00:46:33,440 --> 00:46:36,480
Speaker 1: it's one drama after another. And I couldn't figure out

835
00:46:36,480 --> 00:46:38,440
Speaker 1: why no one had done the TV show. I mean

836
00:46:38,440 --> 00:46:41,520
Speaker 1: it was just the material was so good, I thought,

837
00:46:41,760 --> 00:46:45,680
Speaker 1: And it was. It was naturally dramatic, naturally anecdotal material.

838
00:46:45,960 --> 00:46:49,120
Speaker 1: I couldn't figure out why we didn't know about these people. UM.

839
00:46:49,160 --> 00:46:51,880
Speaker 1: It was it was an arbitrage. It was like finding

840
00:46:52,080 --> 00:46:54,360
Speaker 1: it was like finding a stock. No one's paid attention

841
00:46:54,400 --> 00:46:57,799
Speaker 1: to UM and she was the stock. Uh. And I

842
00:46:57,840 --> 00:47:03,640
Speaker 1: went along say the very least the last last premonition question.

843
00:47:04,160 --> 00:47:09,160
Speaker 1: We're recording this two days after a Trump appointed judge

844
00:47:09,160 --> 00:47:13,880
Speaker 1: who the A b. A Described as not qualified, overturned

845
00:47:13,960 --> 00:47:17,200
Speaker 1: the CDC mass mandates. What what are your thoughts on this?

846
00:47:18,400 --> 00:47:21,480
Speaker 1: I think with the judges with effectively saying I didn't

847
00:47:21,520 --> 00:47:24,040
Speaker 1: read I need to go read the you know, sixty

848
00:47:24,040 --> 00:47:29,120
Speaker 1: page decision, but um, I glanced at it. Uh. The

849
00:47:30,560 --> 00:47:36,120
Speaker 1: is that's that the Congress, not the CDC, has the

850
00:47:36,160 --> 00:47:38,880
Speaker 1: power to do this, And it's sort of a version

851
00:47:38,920 --> 00:47:40,680
Speaker 1: of which happened at the local at the state and

852
00:47:40,719 --> 00:47:46,520
Speaker 1: local level across the country. That the political process, and

853
00:47:46,560 --> 00:47:52,040
Speaker 1: it's the it's the right wing removing the authority from

854
00:47:52,320 --> 00:47:56,680
Speaker 1: the public health expert to do public health. I think

855
00:47:56,680 --> 00:48:00,000
Speaker 1: it's really a really bad idea. However, inapt to see

856
00:48:00,080 --> 00:48:04,439
Speaker 1: DC has been um for for sort of these sort

857
00:48:04,440 --> 00:48:08,359
Speaker 1: of federal decisions. They really you know, until we get

858
00:48:08,400 --> 00:48:11,359
Speaker 1: something better, that they kind of need to be the

859
00:48:11,440 --> 00:48:15,160
Speaker 1: expert who's making the call on this, not not not

860
00:48:15,200 --> 00:48:21,600
Speaker 1: a Congress. Uh. And I think, um, effectively, what what's

861
00:48:21,680 --> 00:48:25,239
Speaker 1: what what's happened is she's killed a lot of people. Um,

862
00:48:25,320 --> 00:48:27,440
Speaker 1: she's doing this just as there is a rise in

863
00:48:27,440 --> 00:48:30,360
Speaker 1: the number of cases she's making. She's making public trends.

864
00:48:30,440 --> 00:48:32,120
Speaker 1: I don't want to wear a mask. So you're talking

865
00:48:32,120 --> 00:48:35,359
Speaker 1: to someone, but half of my brain says, God's great,

866
00:48:35,400 --> 00:48:37,040
Speaker 1: I don't have to wear a mask on an airplane anymore.

867
00:48:37,040 --> 00:48:40,680
Speaker 1: I'm not at risk. I got I'm vaccinated, I'm Elsie nothing,

868
00:48:40,840 --> 00:48:42,840
Speaker 1: I don't have any I'm none of them, none of

869
00:48:42,880 --> 00:48:45,759
Speaker 1: the risk buckets. So who Yeah, great, I don't have

870
00:48:45,760 --> 00:48:49,400
Speaker 1: to wear a mask. You you actually do have a

871
00:48:49,480 --> 00:48:53,959
Speaker 1: risk bucket because sixty plus is a co morbidity. Yeah,

872
00:48:53,960 --> 00:48:55,719
Speaker 1: but I'm sixty one with the body of a thirty

873
00:48:55,800 --> 00:48:59,040
Speaker 1: year old. So so so I actually don't think I'm

874
00:48:59,080 --> 00:49:03,400
Speaker 1: in the risk bucket. You feel and it's it's um

875
00:49:03,440 --> 00:49:07,480
Speaker 1: and so I just I don't. I don't myself. I

876
00:49:07,520 --> 00:49:09,600
Speaker 1: really my first reaction is that, wow, great, thank God

877
00:49:09,760 --> 00:49:12,200
Speaker 1: enough to wear my mask. But the second reaction is

878
00:49:12,239 --> 00:49:15,560
Speaker 1: this is really bad public policy. This is like if

879
00:49:15,640 --> 00:49:18,160
Speaker 1: you're just looking at what's going to happen because of this,

880
00:49:18,880 --> 00:49:23,240
Speaker 1: and I mean, I just it's a shame. It's a shame.

881
00:49:23,360 --> 00:49:27,000
Speaker 1: It's a shame. And I think that that bold people

882
00:49:27,040 --> 00:49:30,160
Speaker 1: will pay the price and what. But this gets back

883
00:49:30,200 --> 00:49:34,839
Speaker 1: to the question of we need a post mortem at

884
00:49:34,880 --> 00:49:37,959
Speaker 1: the end of this to show why people died where

885
00:49:37,960 --> 00:49:41,080
Speaker 1: they died and were like what and why they were

886
00:49:41,120 --> 00:49:45,640
Speaker 1: saved where they were saved, not for purpose of the retribution,

887
00:49:45,760 --> 00:49:48,279
Speaker 1: not for purposes of blaming this judge for people dying

888
00:49:48,320 --> 00:49:51,320
Speaker 1: because they caught it on an airplane, but for purposes

889
00:49:51,320 --> 00:49:53,719
Speaker 1: of going forward into the next one. We're not we're

890
00:49:53,760 --> 00:49:56,080
Speaker 1: not using this as a learning experience. We're using is

891
00:49:56,120 --> 00:49:59,280
Speaker 1: an arguing experience, and that it is such a shame

892
00:49:59,560 --> 00:50:02,040
Speaker 1: because it's going to happen again. Cherry's right. I think

893
00:50:02,080 --> 00:50:05,520
Speaker 1: Cherry's write about this. I mean, all my characters they say, look,

894
00:50:05,880 --> 00:50:09,440
Speaker 1: this steals anomalous, this steals once every century. But actually

895
00:50:09,520 --> 00:50:13,720
Speaker 1: the last twenty years, these these things have been jumping

896
00:50:13,760 --> 00:50:16,040
Speaker 1: from animals to people at a greater rate. And there's

897
00:50:16,040 --> 00:50:19,680
Speaker 1: a reason our relationship with nature is broken, and and

898
00:50:19,719 --> 00:50:23,399
Speaker 1: we're watching the result of that. Uh, and it's there's

899
00:50:23,400 --> 00:50:25,440
Speaker 1: no reason to think it's not going to keep happening.

900
00:50:25,719 --> 00:50:28,399
Speaker 1: So we need to learn. We really really need to learn.

901
00:50:28,440 --> 00:50:31,319
Speaker 1: Our experts need to learn. And you're not learning if

902
00:50:31,320 --> 00:50:36,560
Speaker 1: you're not asking honestly why things happened, really really really fascinating.

903
00:50:37,040 --> 00:50:41,080
Speaker 1: When the audio rites for Liars Poker reverted back, you

904
00:50:41,200 --> 00:50:44,640
Speaker 1: decided to make a complete audio recording of the book.

905
00:50:45,520 --> 00:50:48,080
Speaker 1: I just reread it for the first time since the

906
00:50:48,120 --> 00:50:52,359
Speaker 1: mid nineties. Tell us what your experience was rereading your

907
00:50:52,400 --> 00:50:57,280
Speaker 1: own work unsettling. I just I don't reread my books.

908
00:50:57,320 --> 00:50:59,120
Speaker 1: Sometimes I feel like I should, and I pick them

909
00:50:59,200 --> 00:51:01,239
Speaker 1: up in the first sentence that I got, I can't

910
00:51:01,239 --> 00:51:04,720
Speaker 1: do this. And I did that with Liars Poker. I remember,

911
00:51:05,120 --> 00:51:06,839
Speaker 1: right on the paperback tour year after it came out,

912
00:51:06,880 --> 00:51:08,279
Speaker 1: I thought I gotta go read it and remember what

913
00:51:08,400 --> 00:51:10,320
Speaker 1: was in it, and I couldn't even do it. Um,

914
00:51:10,320 --> 00:51:12,560
Speaker 1: So this really is the first time I've reread it,

915
00:51:12,719 --> 00:51:16,160
Speaker 1: And I thought A couple of things were instantly obvious.

916
00:51:16,560 --> 00:51:19,480
Speaker 1: One I was in the hands of an amateur um

917
00:51:19,600 --> 00:51:24,440
Speaker 1: and I could actually hear. One form the amateurism took

918
00:51:25,320 --> 00:51:29,720
Speaker 1: was the pros is infected by the voices of whoever

919
00:51:29,800 --> 00:51:31,640
Speaker 1: is book I was reading while I was writing it.

920
00:51:32,000 --> 00:51:34,120
Speaker 1: So at one point I was reading from George Orwell

921
00:51:34,280 --> 00:51:38,320
Speaker 1: and other Mark Twain or or Tom Wolfe or Rebecca

922
00:51:38,400 --> 00:51:40,440
Speaker 1: West or. I remember what I was reading at the

923
00:51:40,480 --> 00:51:42,480
Speaker 1: time because I can hear their voices in my prose,

924
00:51:43,080 --> 00:51:46,319
Speaker 1: and that's it's a pale imitation of their voices. But

925
00:51:46,360 --> 00:51:48,920
Speaker 1: I could see that the voice was wavering in in

926
00:51:49,000 --> 00:51:51,920
Speaker 1: the book, and particularly early in the book, and not

927
00:51:52,040 --> 00:51:54,320
Speaker 1: the first chapter because I wrote the first chapter last.

928
00:51:54,680 --> 00:51:57,760
Speaker 1: But but when you start at chapter two, you're seeing

929
00:51:57,800 --> 00:52:00,719
Speaker 1: me in the beginning of my career, and it's kind

930
00:52:00,719 --> 00:52:03,560
Speaker 1: of interesting. It's not until I get to about I

931
00:52:03,600 --> 00:52:06,760
Speaker 1: can't do the passage in like chapter eight where I thought, huh,

932
00:52:07,160 --> 00:52:10,600
Speaker 1: I'm liberated. This is actually more me. I recognized this

933
00:52:11,280 --> 00:52:13,759
Speaker 1: and it's subtle, but it was watching. It's sort of

934
00:52:13,800 --> 00:52:16,600
Speaker 1: like I was, I don't advise anybody to do this.

935
00:52:16,680 --> 00:52:18,319
Speaker 1: I was learning how to write a book by writing

936
00:52:18,360 --> 00:52:22,160
Speaker 1: a book. And um, and you can see it in

937
00:52:22,239 --> 00:52:25,319
Speaker 1: the pages of the book. So that surprised me. Um.

938
00:52:25,600 --> 00:52:27,520
Speaker 1: I mean, let me jump in here because I just

939
00:52:27,560 --> 00:52:31,360
Speaker 1: have to tell you I had the same experience rereading

940
00:52:31,400 --> 00:52:34,960
Speaker 1: this in that it's clear in the beginning it's not

941
00:52:35,440 --> 00:52:41,520
Speaker 1: truly you hadn't discovered your voice yet, but towards the

942
00:52:42,680 --> 00:52:44,920
Speaker 1: mark or so, and I read this on a kindle,

943
00:52:45,000 --> 00:52:49,239
Speaker 1: which I normally I prefer hard paper. But UM, I

944
00:52:49,480 --> 00:52:52,880
Speaker 1: noticed that where you start talking about the mistakes that

945
00:52:52,960 --> 00:52:55,920
Speaker 1: Salomon Brothers Management made, like the beginning of the end

946
00:52:55,960 --> 00:53:00,440
Speaker 1: of Salomon Brothers, Your you're becoming Michael lew. Listen that

947
00:53:00,480 --> 00:53:05,640
Speaker 1: you're making these broad observations about other people's judgment errors

948
00:53:05,680 --> 00:53:09,040
Speaker 1: and your voice really rings true there and my own

949
00:53:09,120 --> 00:53:11,399
Speaker 1: judgment errors. I mean, I think the moment I said,

950
00:53:11,440 --> 00:53:14,799
Speaker 1: the moment I first recognized, really recognized myself on the

951
00:53:14,840 --> 00:53:19,640
Speaker 1: page is um an eight page or ten page story

952
00:53:19,640 --> 00:53:21,759
Speaker 1: where I it's the first time I rip off a

953
00:53:21,800 --> 00:53:25,000
Speaker 1: customer and I don't I'm so stupid. I don't know

954
00:53:25,080 --> 00:53:27,120
Speaker 1: I'm ripping them off. I think that the trader has

955
00:53:27,160 --> 00:53:30,279
Speaker 1: just given me a smart thing to do, and um,

956
00:53:30,360 --> 00:53:33,200
Speaker 1: and that that's the first time I thought, oh god,

957
00:53:33,440 --> 00:53:36,560
Speaker 1: this works. I wouldn't actually change this, and this feels

958
00:53:36,600 --> 00:53:41,799
Speaker 1: like me. Uh So that's you know, that's um. It

959
00:53:41,880 --> 00:53:44,080
Speaker 1: was so that So that was the first takeaway was

960
00:53:44,120 --> 00:53:47,640
Speaker 1: it was just I was I was figuring out how

961
00:53:47,680 --> 00:53:51,239
Speaker 1: to trust myself as I was writing the book, and

962
00:53:51,280 --> 00:53:55,120
Speaker 1: I came to trust myself eventually. Uh So that first

963
00:53:55,120 --> 00:53:59,640
Speaker 1: that's observation number one. Observation number two, UM was how

964
00:53:59,719 --> 00:54:04,520
Speaker 1: much the financial world had changed since then. That I

965
00:54:04,600 --> 00:54:06,919
Speaker 1: remember thinking as I was reading, I was thinking, God,

966
00:54:06,960 --> 00:54:09,160
Speaker 1: I was so lucky that people actually shadowed at each

967
00:54:09,200 --> 00:54:12,520
Speaker 1: other and prove telephones at each other, and and and

968
00:54:12,640 --> 00:54:18,080
Speaker 1: we're actually doing trades face to face, because that's you know,

969
00:54:18,320 --> 00:54:21,120
Speaker 1: without that, the book just has no life. And you

970
00:54:21,239 --> 00:54:24,040
Speaker 1: walk into a trading floor or edge fund now and

971
00:54:24,040 --> 00:54:26,920
Speaker 1: it's just like silence. It's like people staring screens and

972
00:54:26,920 --> 00:54:29,719
Speaker 1: tapping away and al goes are doing the trades. And

973
00:54:30,200 --> 00:54:34,120
Speaker 1: I would be very hard to make it interesting now

974
00:54:34,680 --> 00:54:36,160
Speaker 1: as it was. It's just I think it was just

975
00:54:36,239 --> 00:54:42,280
Speaker 1: a more lively place. But but there was the butt

976
00:54:42,440 --> 00:54:46,280
Speaker 1: was you could see the seeds of what Wall Street

977
00:54:46,360 --> 00:54:49,839
Speaker 1: is now in what Wall Street was becoming. Men. Uh

978
00:54:49,920 --> 00:54:53,040
Speaker 1: that there are big macro things happening, and they're happening

979
00:54:53,040 --> 00:54:56,319
Speaker 1: in the book. That are big changes starting with like

980
00:54:56,880 --> 00:54:58,480
Speaker 1: half the class of Princeton wants to go work on

981
00:54:58,520 --> 00:55:02,920
Speaker 1: Wall Street. Uh, these changes that are happening in the culture. Uh,

982
00:55:02,960 --> 00:55:06,480
Speaker 1: that are happening right then. And so in that way

983
00:55:06,840 --> 00:55:09,759
Speaker 1: there was a current, there was still some currency to it.

984
00:55:10,400 --> 00:55:13,160
Speaker 1: Um that was That was the other reaction had lots

985
00:55:13,200 --> 00:55:16,839
Speaker 1: of other little reactions. The main little reaction was, and

986
00:55:16,880 --> 00:55:20,359
Speaker 1: this is like a rule, is that it was when

987
00:55:20,400 --> 00:55:24,200
Speaker 1: I thought I was being funny, I wasn't funny. And

988
00:55:24,239 --> 00:55:27,440
Speaker 1: the stuff that was funny I didn't realize was funny.

989
00:55:27,920 --> 00:55:30,200
Speaker 1: When I was I was laughing when I was rereading

990
00:55:30,239 --> 00:55:32,319
Speaker 1: my book. I was laughing in places where I didn't

991
00:55:32,400 --> 00:55:34,600
Speaker 1: laugh when I wrote it, and I wasn't laughing in

992
00:55:34,680 --> 00:55:37,520
Speaker 1: places where I did laugh where I wrote it. So

993
00:55:37,520 --> 00:55:40,279
Speaker 1: so let me share one thought with you that I

994
00:55:40,320 --> 00:55:44,200
Speaker 1: didn't I couldn't have picked up in in nine whenever

995
00:55:44,239 --> 00:55:46,719
Speaker 1: I read it the first time. But but it was

996
00:55:47,480 --> 00:55:52,760
Speaker 1: very clear this time. Um not just that Salomon Brothers

997
00:55:52,880 --> 00:55:58,319
Speaker 1: was was formative to Liars Poker, but Liars Poker very

998
00:55:58,440 --> 00:56:03,799
Speaker 1: much foreshadowed your future books. The whole discussion of of

999
00:56:03,920 --> 00:56:08,000
Speaker 1: how mortgage bonds were developed and other the IO p

1000
00:56:08,120 --> 00:56:11,760
Speaker 1: O bonds and other sort of things sort of uh

1001
00:56:12,040 --> 00:56:16,480
Speaker 1: presage the Big Short. That there's conversations about geeks and

1002
00:56:16,640 --> 00:56:21,360
Speaker 1: experts being ignored, presaging money boil and premonition. There's even

1003
00:56:21,560 --> 00:56:25,640
Speaker 1: some discussions about the computer guys coming in and they're

1004
00:56:25,680 --> 00:56:30,719
Speaker 1: still ignored. But eventually that's flashboys. And am I wildly

1005
00:56:30,760 --> 00:56:34,120
Speaker 1: overstating this or are there seeds of of your future

1006
00:56:34,160 --> 00:56:39,600
Speaker 1: books present? There's no question that the Big Short is

1007
00:56:40,360 --> 00:56:43,200
Speaker 1: presaged in in the mortgage all the stuff about the

1008
00:56:43,200 --> 00:56:46,760
Speaker 1: mortgage market that's going on. I mean, Louis Rohnieri himself,

1009
00:56:46,880 --> 00:56:52,640
Speaker 1: the guy who who created the mortgage securities market when

1010
00:56:53,080 --> 00:56:59,600
Speaker 1: when the the financial crisis happens, blames himself. I don't

1011
00:56:59,600 --> 00:57:02,479
Speaker 1: think that's fair. It's like it's like it's like Dr

1012
00:57:02,520 --> 00:57:07,960
Speaker 1: Frankenstein blaming himself for what the monster became. But it's uh,

1013
00:57:08,200 --> 00:57:12,359
Speaker 1: he it's um, he saw the connection. So that's there's

1014
00:57:12,360 --> 00:57:15,920
Speaker 1: an obvious connection between the innovation that occurred while I

1015
00:57:16,040 --> 00:57:21,000
Speaker 1: was at Solomon Brothers and the disaster that ensued twenty

1016
00:57:21,080 --> 00:57:28,360
Speaker 1: years later. Um. The intellectualization of finance, um is there

1017
00:57:28,480 --> 00:57:33,480
Speaker 1: is a connection between that and the intellectualization of sports. Um.

1018
00:57:34,200 --> 00:57:37,440
Speaker 1: You know. First, I mean I would there's probably a

1019
00:57:37,440 --> 00:57:41,960
Speaker 1: great story in the undergraduate physics program at M I T.

1020
00:57:42,720 --> 00:57:45,040
Speaker 1: And if you go back forty years, I bet like

1021
00:57:45,120 --> 00:57:48,800
Speaker 1: they all become physicists. And if you go back thirty years,

1022
00:57:48,840 --> 00:57:51,640
Speaker 1: a few of them are trickling onto Wall Street. Uh.

1023
00:57:51,680 --> 00:57:54,160
Speaker 1: And you go there now and it's sort of like

1024
00:57:54,280 --> 00:57:56,240
Speaker 1: they either go to Wall Street or they go into sports.

1025
00:57:56,760 --> 00:58:02,880
Speaker 1: It's it's it's it's uh. It's it's interesting how we've

1026
00:58:03,560 --> 00:58:08,080
Speaker 1: or maybe Silicon Valley, how we have channel that kind

1027
00:58:08,080 --> 00:58:11,680
Speaker 1: of intellect in the enterprises that previously didn't see a

1028
00:58:11,720 --> 00:58:15,920
Speaker 1: need for it by complicating those enterprises. And you know,

1029
00:58:16,160 --> 00:58:20,439
Speaker 1: first finance got very complicated, and then sports got very complicated. Huh,

1030
00:58:20,600 --> 00:58:25,000
Speaker 1: really really interesting, Um, tell us, what was the law

1031
00:58:25,120 --> 00:58:28,000
Speaker 1: of the jungle which runs through the book so much.

1032
00:58:28,440 --> 00:58:30,440
Speaker 1: I always thought of it as as you know, kill

1033
00:58:30,520 --> 00:58:35,280
Speaker 1: or be killed, which very much is a factor here.

1034
00:58:35,880 --> 00:58:39,480
Speaker 1: But but Solomon Brothers was a little unique in the

1035
00:58:39,480 --> 00:58:42,760
Speaker 1: way they managed that. And you point out later in

1036
00:58:42,800 --> 00:58:48,200
Speaker 1: the book how they allowed their biggest, best, most profitable

1037
00:58:48,320 --> 00:58:52,640
Speaker 1: traders to leave after they were no longer a partnership.

1038
00:58:52,760 --> 00:58:55,840
Speaker 1: And you know, these guys are traders, and they made

1039
00:58:55,880 --> 00:58:58,840
Speaker 1: the trade to you know, to hit the bid and

1040
00:58:58,960 --> 00:59:02,439
Speaker 1: joined goldman Or or Morgan Stanley or somewhere else where

1041
00:59:02,440 --> 00:59:05,240
Speaker 1: they were Merrill Lynch where they would be paid millions

1042
00:59:05,320 --> 00:59:08,600
Speaker 1: more than the few hundred thousand they were getting, plus

1043
00:59:08,600 --> 00:59:11,800
Speaker 1: a bonus at Sally. Yeah, there was an odd contradiction

1044
00:59:12,560 --> 00:59:17,840
Speaker 1: in the solemn management theory. Um. John good Friend would

1045
00:59:17,840 --> 00:59:20,920
Speaker 1: say things like, um, you gotta get you're gonna come

1046
00:59:20,920 --> 00:59:22,600
Speaker 1: work here. You have to be you have to wake

1047
00:59:22,680 --> 00:59:25,040
Speaker 1: up in the morning willing to bite the ass off

1048
00:59:25,040 --> 00:59:28,360
Speaker 1: a bear. Or he'd say, nobody here is gonna get

1049
00:59:28,400 --> 00:59:30,120
Speaker 1: stabbed in the back of people are gonna come at

1050
00:59:30,160 --> 00:59:33,080
Speaker 1: you through the front door with a hatchet. Uh. That

1051
00:59:33,200 --> 00:59:38,080
Speaker 1: he encouraged this red and tooth and claw free for

1052
00:59:38,160 --> 00:59:42,440
Speaker 1: all on the trading floor where everybody kind of for himself,

1053
00:59:42,600 --> 00:59:46,120
Speaker 1: all for the firm sort of thing. And um, at

1054
00:59:46,160 --> 00:59:50,200
Speaker 1: the same time, he's after he sold the firm, and

1055
00:59:50,240 --> 00:59:53,320
Speaker 1: so there was not the partnership stake to yoke people

1056
00:59:53,360 --> 00:59:58,360
Speaker 1: to the firm. Um. He expected total loyalty and fealty

1057
00:59:58,440 --> 01:00:02,200
Speaker 1: from these killers who we had encouraged, and that that

1058
01:00:02,440 --> 01:00:05,040
Speaker 1: they weren't if they were being paid three thousand dollars

1059
01:00:05,080 --> 01:00:07,760
Speaker 1: and Solomon Brothers and Merrilynch offered him a million, it

1060
01:00:07,760 --> 01:00:09,960
Speaker 1: would have been it was it was regarded as treason

1061
01:00:10,080 --> 01:00:14,200
Speaker 1: to take the million, and that was crazy that you

1062
01:00:14,240 --> 01:00:20,240
Speaker 1: couldn't have both. Um. So he sort of encouraged the

1063
01:00:20,400 --> 01:00:24,720
Speaker 1: very qualities that led people to look out for themselves

1064
01:00:25,400 --> 01:00:29,640
Speaker 1: and respond to market incentives rather than to other kinds

1065
01:00:29,640 --> 01:00:34,000
Speaker 1: of incentives like loyalty of the firm um. And and

1066
01:00:34,080 --> 01:00:38,040
Speaker 1: didn't see the contradiction. Uh, And it really cost him.

1067
01:00:38,080 --> 01:00:41,280
Speaker 1: I mean, he had virtual monopolies in markets that he

1068
01:00:41,360 --> 01:00:44,280
Speaker 1: just let's slip away by letting traders go and of

1069
01:00:44,320 --> 01:00:46,960
Speaker 1: course they wouldn't have been able to preserve the monopoly.

1070
01:00:47,000 --> 01:00:49,440
Speaker 1: Eventually they would have lost their grip on the mortgage

1071
01:00:49,480 --> 01:00:53,240
Speaker 1: market or on the arbitrage trading or whatever it was.

1072
01:00:53,280 --> 01:00:55,280
Speaker 1: That they had an edge, but they had have kept

1073
01:00:55,360 --> 01:00:58,120
Speaker 1: it free some more time. And while they had it,

1074
01:00:58,160 --> 01:01:01,680
Speaker 1: it was so valuable. So it was, it was, It was.

1075
01:01:01,760 --> 01:01:06,240
Speaker 1: It was an odd situation, um and the whole firm,

1076
01:01:06,480 --> 01:01:10,040
Speaker 1: the whole firm knew it was mismanaged. While I was there,

1077
01:01:10,240 --> 01:01:14,040
Speaker 1: I mean, down to the lowest geek, everybody knew whatever

1078
01:01:14,040 --> 01:01:16,840
Speaker 1: they thought about Good Fund personally, they realized that the

1079
01:01:16,880 --> 01:01:20,640
Speaker 1: thing was just not managed well and they couldn't quite

1080
01:01:20,720 --> 01:01:23,520
Speaker 1: understand why it was managed the way it was managed.

1081
01:01:23,960 --> 01:01:27,240
Speaker 1: But the effect for me was a really smoothly managed

1082
01:01:27,240 --> 01:01:30,400
Speaker 1: firm is much less fun to write about. The total chaos,

1083
01:01:30,560 --> 01:01:34,000
Speaker 1: just a total chaos. So the chaos that I got

1084
01:01:34,000 --> 01:01:37,200
Speaker 1: to write about was much more fun. So I mean,

1085
01:01:37,200 --> 01:01:39,959
Speaker 1: in some ways I'm forever in John good Friend's debt

1086
01:01:40,960 --> 01:01:46,000
Speaker 1: because because he created an environment that was literary gold mine.

1087
01:01:46,800 --> 01:01:50,160
Speaker 1: To say the very least last question before we get

1088
01:01:50,200 --> 01:01:53,920
Speaker 1: to our speed round, and that is throughout the book.

1089
01:01:54,120 --> 01:01:58,160
Speaker 1: Because Sally was a bond shop there's a lot of

1090
01:01:58,200 --> 01:02:02,880
Speaker 1: talk about debt, government debt, consumer debt, mortgage debt, America's

1091
01:02:02,960 --> 01:02:06,480
Speaker 1: borrowers and and all, what an evil this is, how

1092
01:02:06,520 --> 01:02:09,840
Speaker 1: it will eventually weaken the dollar and cause all sorts

1093
01:02:09,840 --> 01:02:13,880
Speaker 1: of economic mischief. But it's three decades later, and it's

1094
01:02:14,360 --> 01:02:18,760
Speaker 1: other than the financial crisis, which was very specific and

1095
01:02:18,840 --> 01:02:23,360
Speaker 1: not traditional debt driven. We really haven't seen a lot

1096
01:02:23,440 --> 01:02:27,280
Speaker 1: of the bad things come to pass from all that debt.

1097
01:02:27,920 --> 01:02:31,800
Speaker 1: What's your assessment of that era? Did everybody just repeat

1098
01:02:31,880 --> 01:02:35,560
Speaker 1: the same things and more or less out at wrong? Well? Yes,

1099
01:02:36,440 --> 01:02:37,840
Speaker 1: part of what was going on is it's such a

1100
01:02:37,880 --> 01:02:43,440
Speaker 1: departure from American historical historical American finance, uh that it was.

1101
01:02:43,880 --> 01:02:45,640
Speaker 1: I mean the people who said this is all going

1102
01:02:45,680 --> 01:02:50,439
Speaker 1: to be fine have improved right so far. I think

1103
01:02:50,480 --> 01:02:54,880
Speaker 1: that there's still another shooter drop and maybe it's dropping now.

1104
01:02:55,480 --> 01:03:00,640
Speaker 1: I mean, eventually, you can't live beyond on your means

1105
01:03:00,680 --> 01:03:05,480
Speaker 1: forever and um. And the financial crisis was in some ways,

1106
01:03:06,720 --> 01:03:10,200
Speaker 1: of a lot of ways a byproduct of this American

1107
01:03:11,200 --> 01:03:16,520
Speaker 1: a willingness to live well beyond its means um and

1108
01:03:16,800 --> 01:03:21,520
Speaker 1: using and using debt to do it. Um the machine,

1109
01:03:21,560 --> 01:03:24,800
Speaker 1: I mean, the crucial ingredients, the crucial parts of this

1110
01:03:25,080 --> 01:03:27,800
Speaker 1: enabled this machine to function, or things like the dollar

1111
01:03:27,960 --> 01:03:30,680
Speaker 1: is a reserve currency around the world which we're putting

1112
01:03:30,720 --> 01:03:35,920
Speaker 1: at risk, or um, I mean it's it's so I'm

1113
01:03:35,960 --> 01:03:38,080
Speaker 1: not I know, I'm not completely answering your question that

1114
01:03:38,120 --> 01:03:40,960
Speaker 1: people kind of get it wrong back then. I don't.

1115
01:03:41,000 --> 01:03:42,560
Speaker 1: I mean I think people would. If you go back

1116
01:03:42,600 --> 01:03:46,440
Speaker 1: and talk to Henry Kaufman way back in three or

1117
01:03:46,480 --> 01:03:49,720
Speaker 1: eighty five, I think he probably would say that I'm

1118
01:03:49,760 --> 01:03:52,840
Speaker 1: surprised by what happened. I would have thought that. I

1119
01:03:52,840 --> 01:03:54,920
Speaker 1: wouldn't have fought the federal government will be able to

1120
01:03:55,000 --> 01:03:56,960
Speaker 1: run the deficits it's been running for as long as

1121
01:03:56,960 --> 01:03:59,000
Speaker 1: it's been running it. I wouldn't have thought the American

1122
01:03:59,040 --> 01:04:01,640
Speaker 1: consumer would get way with with the American consumer got

1123
01:04:01,640 --> 01:04:04,160
Speaker 1: away with in the run up to the to the

1124
01:04:04,160 --> 01:04:07,240
Speaker 1: financial crisis. But and it's not going to end well,

1125
01:04:07,440 --> 01:04:10,560
Speaker 1: he would say, But it's still has it ended? I mean,

1126
01:04:10,600 --> 01:04:13,880
Speaker 1: we're still kind of in this period. So, um, the

1127
01:04:14,480 --> 01:04:19,120
Speaker 1: period the Great American debt explosion. So I have to

1128
01:04:19,280 --> 01:04:22,080
Speaker 1: point out that each of your books led to a

1129
01:04:22,200 --> 01:04:26,920
Speaker 1: subsequent expansion of American debt. You had Liars Poker and

1130
01:04:27,240 --> 01:04:29,600
Speaker 1: the big debt explosion we saw in the eighties and nineties,

1131
01:04:30,360 --> 01:04:32,400
Speaker 1: the big short look at look at how the FedEx

1132
01:04:32,440 --> 01:04:35,760
Speaker 1: been in the barrel battleship, and then the pandemic. So

1133
01:04:35,840 --> 01:04:41,680
Speaker 1: I'm not suggestingzation, right, but but you're talking. Every time

1134
01:04:41,760 --> 01:04:44,240
Speaker 1: you describe one of these big issues in a book,

1135
01:04:45,160 --> 01:04:48,840
Speaker 1: it's often because the result of that issue was a

1136
01:04:48,960 --> 01:04:53,600
Speaker 1: huge expansion of debt. Yeah, it's true. So so I

1137
01:04:53,680 --> 01:04:55,720
Speaker 1: know I have a hard stop with you. So let

1138
01:04:55,720 --> 01:04:59,320
Speaker 1: me in the last two minutes jump to our speed

1139
01:04:59,400 --> 01:05:04,360
Speaker 1: round and score favorite questions. Five questions, seconds on the clock.

1140
01:05:04,480 --> 01:05:07,600
Speaker 1: Let's let's get this started. What are you streaming these days?

1141
01:05:07,680 --> 01:05:12,240
Speaker 1: Tell us what's keeping you entertained? Well, oddly, I'm streaming

1142
01:05:12,920 --> 01:05:16,240
Speaker 1: a preview of the six part neck Netflix series called

1143
01:05:16,240 --> 01:05:19,080
Speaker 1: The G Word, which is based on the Fifth Risk.

1144
01:05:19,320 --> 01:05:22,560
Speaker 1: So I'm just started watching my own television show. I

1145
01:05:22,600 --> 01:05:25,200
Speaker 1: didn't make it, Adam kind of over made at the comedian,

1146
01:05:25,280 --> 01:05:28,800
Speaker 1: But um, I'm watching that. When when does that come

1147
01:05:28,800 --> 01:05:30,880
Speaker 1: out on Netflix? When can the rest of us dream that?

1148
01:05:31,480 --> 01:05:34,560
Speaker 1: End of may? Alright, looking forward to that? So so

1149
01:05:34,720 --> 01:05:38,480
Speaker 1: you uh in in the new podcast in in UM

1150
01:05:38,680 --> 01:05:42,880
Speaker 1: season three, you kind of um reveal some of your

1151
01:05:42,920 --> 01:05:46,240
Speaker 1: mentors tell us a little bit about dash rip Rock

1152
01:05:46,440 --> 01:05:51,240
Speaker 1: and Alexander and the human Piranha. Um. I actually go

1153
01:05:51,320 --> 01:05:53,960
Speaker 1: back and talk to these pseudonymous characters, and they reveal

1154
01:05:54,040 --> 01:05:57,520
Speaker 1: themselves in the podcast. Um, it's it's kind of where

1155
01:05:57,520 --> 01:05:59,720
Speaker 1: they are now. That's interesting because you can see where

1156
01:05:59,720 --> 01:06:02,600
Speaker 1: they were and then in the book. But the human piranha,

1157
01:06:02,800 --> 01:06:05,760
Speaker 1: who was ferocious on the Solomon training floor, has mellowed

1158
01:06:05,800 --> 01:06:14,440
Speaker 1: into just a sweet guy who is emotionally intelligent. He's

1159
01:06:14,480 --> 01:06:18,560
Speaker 1: just he's transformed in some ways. Um. Dash rip Rock

1160
01:06:18,720 --> 01:06:22,560
Speaker 1: spenting his career he made up up until very recently

1161
01:06:22,720 --> 01:06:25,280
Speaker 1: was in the bond markets and has watched essentially, he says,

1162
01:06:25,320 --> 01:06:27,920
Speaker 1: the death of the American bond salesman. He's watched his career,

1163
01:06:28,680 --> 01:06:32,640
Speaker 1: his occupation just more or less banish. Uh and Alexander

1164
01:06:33,840 --> 01:06:38,320
Speaker 1: left Solomon Brothers, had a blew up, blew up at

1165
01:06:38,320 --> 01:06:42,040
Speaker 1: a hedge fund um and it has had a kind

1166
01:06:42,040 --> 01:06:49,000
Speaker 1: of interesting career as a private investor and lives in Singapore. Um.

1167
01:06:49,080 --> 01:06:52,600
Speaker 1: So they they're all, they they've all, they've all kind

1168
01:06:52,600 --> 01:06:56,560
Speaker 1: of mellowed. Uh. And they all I think I think

1169
01:06:56,560 --> 01:07:00,160
Speaker 1: it's probably fair to say, like everybody in my training class. Us.

1170
01:07:00,640 --> 01:07:02,520
Speaker 1: All the people who stand on Wall Street anyway, they

1171
01:07:02,560 --> 01:07:06,720
Speaker 1: all made more money than me. Uh that I don't doubt. UM.

1172
01:07:06,840 --> 01:07:09,960
Speaker 1: Give us two books that you've read, either a longtime

1173
01:07:10,040 --> 01:07:13,360
Speaker 1: favorite or what you're reading right now. I've got two

1174
01:07:13,400 --> 01:07:15,960
Speaker 1: novels that I'm starting and I'm gonna I'm reading. I

1175
01:07:15,960 --> 01:07:18,200
Speaker 1: shouldn't do this, but I'm about to do it, uh,

1176
01:07:18,360 --> 01:07:22,000
Speaker 1: or read at the same time. One is a novel

1177
01:07:22,040 --> 01:07:26,200
Speaker 1: called Horse by Geraldine Brooks, who is an old friend

1178
01:07:26,240 --> 01:07:29,000
Speaker 1: and and is like a really great writer. And it's

1179
01:07:29,000 --> 01:07:30,840
Speaker 1: so much fun when one of your friends is actually

1180
01:07:30,840 --> 01:07:34,960
Speaker 1: a great writer. Um and so, and that actually isn't

1181
01:07:34,960 --> 01:07:37,320
Speaker 1: out yet, that comes out next month. So I'm reading

1182
01:07:37,320 --> 01:07:40,640
Speaker 1: the galleys of that book. And I just picked up

1183
01:07:40,680 --> 01:07:44,920
Speaker 1: at the same time, UM, a book about my hometown

1184
01:07:44,920 --> 01:07:46,720
Speaker 1: and novel set in my hometown by a writer I

1185
01:07:46,720 --> 01:07:50,720
Speaker 1: don't know books called The Yellow House set in New Orleans.

1186
01:07:50,920 --> 01:07:52,880
Speaker 1: I think it won the Pulitzer Prize of the National

1187
01:07:52,880 --> 01:07:55,640
Speaker 1: Book Award. Sarah Broom is the name of the author.

1188
01:07:55,960 --> 01:07:57,800
Speaker 1: And it's a it's a it's a view of New

1189
01:07:57,880 --> 01:07:59,880
Speaker 1: Orleans as very different from the New Orleans I grew up.

1190
01:08:00,200 --> 01:08:03,640
Speaker 1: It's it's it's um, it's black New Orleans rather than

1191
01:08:03,640 --> 01:08:07,800
Speaker 1: white New Orleans, and that always interests me. So you

1192
01:08:07,920 --> 01:08:11,760
Speaker 1: have said that Liars Poker had a very different impact

1193
01:08:11,800 --> 01:08:16,280
Speaker 1: on the world than you expected, and people requested advice

1194
01:08:16,680 --> 01:08:19,920
Speaker 1: of you after the book came out or thought the

1195
01:08:19,920 --> 01:08:23,120
Speaker 1: book was a how to guide. What sort of advice

1196
01:08:23,160 --> 01:08:26,519
Speaker 1: would you give today to a recent college grad who

1197
01:08:26,600 --> 01:08:30,840
Speaker 1: was interested in a career on Wall Street? Um, ask

1198
01:08:30,960 --> 01:08:35,599
Speaker 1: why you're interested first, and go talk to people who

1199
01:08:35,600 --> 01:08:38,799
Speaker 1: were twenty years older than you who kind of remind

1200
01:08:38,880 --> 01:08:41,800
Speaker 1: you of how you, who kind of looked like they

1201
01:08:41,880 --> 01:08:44,240
Speaker 1: might have been like you when they were your age,

1202
01:08:44,520 --> 01:08:47,679
Speaker 1: and see what you think of their lives. Because they're

1203
01:08:47,680 --> 01:08:49,640
Speaker 1: really great ways to have careers on Wall Street, and

1204
01:08:49,640 --> 01:08:51,439
Speaker 1: they're really bad ways a career in Wall Street, and

1205
01:08:51,479 --> 01:08:55,240
Speaker 1: people go in for the wrong reasons, for obvious reasons. Um.

1206
01:08:55,560 --> 01:08:59,599
Speaker 1: The other thing I'd say is figure out whether whether

1207
01:09:00,040 --> 01:09:03,000
Speaker 1: you're a job a career person, a job person, or

1208
01:09:03,000 --> 01:09:05,840
Speaker 1: a calling person. That if you need a calling as

1209
01:09:05,840 --> 01:09:10,120
Speaker 1: opposed to a job, um, uh, you can find it

1210
01:09:10,160 --> 01:09:12,640
Speaker 1: on Wall Street. But it's much more likely you got

1211
01:09:12,680 --> 01:09:15,680
Speaker 1: a job that pays real well and you're gonna be

1212
01:09:15,800 --> 01:09:18,479
Speaker 1: really frustrated with your life if you spend it in

1213
01:09:18,520 --> 01:09:21,679
Speaker 1: a job when what you really need is a calling. Alright,

1214
01:09:21,720 --> 01:09:24,840
Speaker 1: Final question, what do you know about the world of

1215
01:09:24,880 --> 01:09:29,360
Speaker 1: either investing or writing today? You wish you knew when

1216
01:09:29,439 --> 01:09:32,720
Speaker 1: you first sat down to write Liars Poker thirty two

1217
01:09:32,800 --> 01:09:38,320
Speaker 1: years ago. This is damning. I don't think I've actually

1218
01:09:38,439 --> 01:09:41,320
Speaker 1: learned anything about investing in the last thirty two years.

1219
01:09:41,400 --> 01:09:43,720
Speaker 1: It's all at all useful. I think that's sort of

1220
01:09:43,760 --> 01:09:47,200
Speaker 1: like all the useful things are really simple, and I

1221
01:09:47,320 --> 01:09:50,680
Speaker 1: picked those up by doing the opposite back in with

1222
01:09:50,720 --> 01:09:56,160
Speaker 1: other people's money. Um writing, you know, I'll give you

1223
01:09:56,200 --> 01:09:59,719
Speaker 1: one simple answer. It's and it's I think the best

1224
01:10:00,000 --> 01:10:03,280
Speaker 1: things I've done are because I've got the best characters.

1225
01:10:03,760 --> 01:10:07,639
Speaker 1: That I think that I underestimated the importance of character

1226
01:10:08,240 --> 01:10:11,639
Speaker 1: early on in my writing career, and I've I've gotten

1227
01:10:11,640 --> 01:10:16,320
Speaker 1: better and better at at at identifying characters who are

1228
01:10:16,320 --> 01:10:19,479
Speaker 1: really good and and writing them. So I think that

1229
01:10:20,120 --> 01:10:23,679
Speaker 1: leading with character is what I've learned. We have been

1230
01:10:23,760 --> 01:10:28,640
Speaker 1: speaking with Michael Lewis, author of such seminal books as Moneyball,

1231
01:10:28,760 --> 01:10:33,800
Speaker 1: The Big Short, and Liars Poker. If you enjoy this conversation,

1232
01:10:33,920 --> 01:10:38,160
Speaker 1: be sure and check out any of our previous three

1233
01:10:38,360 --> 01:10:42,080
Speaker 1: prior discussions. You can find those wherever you get your podcasts.

1234
01:10:43,120 --> 01:10:46,120
Speaker 1: We love your comments, feedback and suggestions right to us

1235
01:10:46,160 --> 01:10:49,720
Speaker 1: at m IB podcast at Bloomberg dot net. Check out

1236
01:10:49,760 --> 01:10:52,240
Speaker 1: my daily reads at rid Halts dot com. Follow me

1237
01:10:52,280 --> 01:10:54,680
Speaker 1: on Twitter at rit Halts. I would be remiss if

1238
01:10:54,720 --> 01:10:56,680
Speaker 1: I did not thank the crack team who helps with

1239
01:10:56,840 --> 01:11:00,559
Speaker 1: these conversations together each week. Justin no Her is my

1240
01:11:00,640 --> 01:11:05,280
Speaker 1: audio engineer. Attica Valbran is my project manager. Paris Walds

1241
01:11:05,439 --> 01:11:10,679
Speaker 1: is my producer. Sean Russo is my research director. I'm

1242
01:11:10,720 --> 01:11:14,400
Speaker 1: Barry Results. You've been listening to Masters in Business on

1243
01:11:14,600 --> 01:11:15,479
Speaker 1: Boomberg Radio