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Speaker 1: Pushkin.

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Speaker 2: Welcome back to Risky Business, a show about making better decisions.

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Speaker 2: I'm Maria Kanakova.

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Speaker 3: And I'm Nate Silver.

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Speaker 2: Today on the show, Nate, we're going to start by

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Speaker 2: talking about brackets. I don't sound very excited because I'm

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Speaker 2: not doing well, but we'll do a full catch up

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Speaker 2: there and talk also a little bit about free speech,

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Speaker 2: what's going on right now in college campuses, and then

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Speaker 2: go into twenty three and meters and whether it's a

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Speaker 2: good idea to send your ganic and data to a

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Speaker 2: private company. Tough one, tough one, Hey, tough one. And

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Speaker 2: then finally, let's talk about how we value our time.

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Speaker 2: So you know, how do you make decisions that trade

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Speaker 2: off time against other things? How do you actually think

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Speaker 2: about that? Let's get into it with some march madness, Nate,

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Speaker 2: I have watched more basketball in the last week than

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Speaker 2: I think.

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Speaker 3: I have or something.

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Speaker 2: No, I've actually watched multiple games. I've watched multiple games

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Speaker 2: because I was first rooting for Tennessee. You know, I

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Speaker 2: was anti sweating Florida. There were so many games that

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Speaker 2: just did not go way. I have quite a chat

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Speaker 2: going with Monty who if people were not listening to

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Speaker 2: our show. A few weeks ago, Monty McNair helped me

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Speaker 2: with my brackets, and on Saturday I texted him and said,

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Speaker 2: I'm anti sweating Florida hard, to which he said, we've

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Speaker 2: made you a college basketball junkie, given how often I

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Speaker 2: am texting him now, And I said no, I just

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Speaker 2: I said, ha ha ha, We've got to beat Nate

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Speaker 2: and he said, for sure, this would help, and then

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Speaker 2: Florida made a comeback.

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Speaker 3: So you need are you drawing?

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Speaker 1: No? I need Duke to win.

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Speaker 2: Oh, if Duke wins, I win, I'm not drawing dead.

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Speaker 3: I think I fucked up the whole game theory because

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Speaker 3: I should have just picked Dukes if I was going

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Speaker 3: to be ahead, and I out psyched myself. So yeah, anyway, yeah,

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Speaker 3: I'm already pretty anti Duke, justin general in life and

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Speaker 3: also in some of my real sports tie way, you

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Speaker 3: want a little you went a little tidbit into like

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Speaker 3: the sports betting, the sports betting.

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Speaker 1: Life, right, Yeah, it's dark always so far.

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Speaker 3: I bet Let me see here, I have bet one

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Speaker 3: hundred and twenty units on the NCAA tournament. Both the

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Speaker 3: men and the women were equal opportunity here, and I'm

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Speaker 3: ahead by zero point six. Oh wow, this is yeah,

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Speaker 3: this is how it often goes where but you're ahead,

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Speaker 3: which is better than ninety eight percent of people. I

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Speaker 3: would imagine we would really like it if Houston wins.

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Speaker 3: We would like it if Florida went, both for our

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Speaker 3: bracket and for my old bets. I mean, like, if

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Speaker 3: this South Carolina win and win, so that happens, we

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Speaker 3: end up underwater probably.

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Speaker 2: Well, I would like Duke to win. I am now

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Speaker 2: one hundred percent on Duke. I you know, it's so funny.

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Speaker 2: This is, as I told Monty, this is why I

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Speaker 2: do not watch sports normally. It is wild because Florida

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Speaker 2: so nate because you have Florida winning. I was anti

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Speaker 2: sweating them right because they were behind in that game

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Speaker 2: and it looked like they might lose, which would be

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Speaker 2: great because I need Florida to not win along with

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Speaker 2: Duke winning. And I just had to say, this is

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Speaker 2: why I don't watch sports, to which you said it's

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Speaker 2: an emotional roller coaster, which it really is, but we

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Speaker 2: are still alive, and it does They'll make it a

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Speaker 2: lot more fun to be sweating anti sweating. It's kind

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Speaker 2: of like poker, right when I know the people playing.

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Speaker 2: It's always fun when I like people to root for,

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Speaker 2: and it's also really really fun when I dislike someone

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Speaker 2: and I'm.

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Speaker 1: Just actively.

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Speaker 2: I do not answer that on a public podcast that

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Speaker 2: is being listened to by tens of thousands of people.

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Speaker 3: Maybe a gender and a nationality that doesn't really narrow

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Speaker 3: it less, like Slovenian or something.

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Speaker 2: Well, one of the people. I can't give you a nationality,

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Speaker 2: but my mail.

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Speaker 1: Okay, thanks, thanks mail. Oh okay.

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Speaker 2: One of the people I most dislike is male and

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Speaker 2: uh oh fuck no that that that's gonna that's gonna error.

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Speaker 1: I don't want to be mean. I I don't.

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Speaker 2: I don't want to be mean, but I think some

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Speaker 2: of these people, oh male an American. Here we go,

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Speaker 2: I know one of the people.

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Speaker 3: I'm you're not allowed to give an answer.

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Speaker 1: There you go, but it's true to you.

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Speaker 3: Okay, okay, But.

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Speaker 2: It's always it's always very fun to anti sweat as well.

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Speaker 2: That's that's mean of me, isn't it.

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Speaker 3: No, That's how we get our pleasure in life. I mean,

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Speaker 3: that's why people, this is why humans are human beings. Right.

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Speaker 3: We fight for honor, we fight to the death, you know,

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Speaker 3: and the people in charge of country also seem to

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Speaker 3: be fueled by grievance. I don't know if we want

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Speaker 3: to talk about politics or net.

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Speaker 2: Yeah, yeah, I mean, I think the one thing that

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Speaker 2: I would like to talk about, just briefly, because I

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Speaker 2: think it's really important, is what's happening right now with

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Speaker 2: you know, free speech in this country and with how

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Speaker 2: college's universities are reacting to pressure from Trump. Not just universities,

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Speaker 2: by the way, this is happening everywhere law firms. You know,

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Speaker 2: there's just this big muzzling where where people are just

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Speaker 2: caving left and right. But one of the things that,

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Speaker 2: you know, it's very personal to me because first, my

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Speaker 2: graduate alma mater, Columbia University, just completely cave to Trump,

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Speaker 2: making me, frankly, just very upset that I went there,

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Speaker 2: like kind of embarrassed that I have a Columbia degree

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Speaker 2: by how it handled this whole thing. And now there

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Speaker 2: was a threat made against my undergraduate alma mater, Harvard,

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Speaker 2: to withdraw nine billion dollars worth of funding, and we

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Speaker 2: got this lovely email from the Harvard president and other

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Speaker 2: people basically saying all of the ways that they're going

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Speaker 2: to give in to the Trump demands before he's even

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Speaker 2: made anything so that the funding is not cut. And

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Speaker 2: the Crimson, by the way, the Harvard Crimson, which is

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Speaker 2: the Harvard student newspaper, ran an editorial by students last

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Speaker 2: week which was like, you can't cave in, right, you

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Speaker 2: need to stand up for academic integrity, for free speech.

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Speaker 2: And now the Harvard administration's like, yeah, you know, we're

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Speaker 2: just going to quietly and meekly do this thing. And

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Speaker 2: to me, if you're looking at this kind of through

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Speaker 2: a game theory lens, right, everyone is showing themselves to

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Speaker 2: be completely risk intolerant, like knits to the twentieth twenty

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Speaker 2: millionth degree that they are just saying, we're going to

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Speaker 2: cover our asses. We're not going to speak out in solidarity,

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Speaker 2: we're not going to do anything. We just want to

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Speaker 2: protect ourselves right now. And that's incredibly shortsighted, I think,

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Speaker 2: because this is not a single iteration game. This is

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Speaker 2: going to be a repeat game. And if you give

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Speaker 2: in right now, you know, what are you doing right?

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Speaker 2: What is happening to your ability to take risks in

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Speaker 2: the future, to research, to just everything. And I'm looking

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Speaker 2: at this and I'm saying, you guys, like, you really

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Speaker 2: need to speak up and stand up to this. Harvard

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Speaker 2: can afford to, right. I realize that billions are a lot,

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Speaker 2: but Harvard has the second largest endowment.

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Speaker 3: In the world two billion dollars three billions sorry ms

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Speaker 3: billion here there.

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Speaker 2: This is, I mean, this is what it's there for,

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Speaker 2: right to protect academic freedom and the future of the

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Speaker 2: research and the work that you do. So if Harvard

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Speaker 2: is caving, if Columbia is caving, there's just no future

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Speaker 2: for the rest of it. And we have to remember

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Speaker 2: that this is where some of our most important research, ideas,

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Speaker 2: just everything come from. And it's just it's also we

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Speaker 2: don't even have to talk about how, you know, hypocritical.

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Speaker 2: It is that Trump was saying that he was going

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Speaker 2: to be supporting free speech and now this is happening.

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Speaker 2: But I think we can could have predicted that. But anyway,

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Speaker 2: I think it's a very scary response because this is

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Speaker 2: you know, shutting up, being quiet, being meek, not taking

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Speaker 2: risks at this point, not speaking out is how we

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Speaker 2: go down a very dark path. And I think that

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Speaker 2: people will be rewarded for taking risks right now, but

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Speaker 2: they don't think of it that way. Right It's a

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Speaker 2: cover my ass immediately type of reaction, which, yeah, which

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Speaker 2: I think is the wrong way of looking at it.

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Speaker 3: You know, I forgot to pack the world's tiny oft

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Speaker 3: file in in my luggage. But like I, out of

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Speaker 3: all things Trump is doing, going after the Ivy League

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Speaker 3: universes is one of the things I'm most sympathetic too,

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Speaker 3: and where we probably have an audience that over your

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Speaker 3: next is. But I think for years these universes and

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Speaker 3: there are exceptions. I would think that my elemmentar Eativers

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Speaker 3: of Chicago is one of them. But like these universes

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Speaker 3: have lit a culture of free speech in road, they

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Speaker 3: have let their at it's become politicized, I think, in

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Speaker 3: one direction towards a certain type of lectning behavior, and

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Speaker 3: they after this though they were immune from public backlash,

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Speaker 3: and believe me, Harvard is more immune from it than

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Speaker 3: state schools, for example. But I think there's a reason

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Speaker 3: why Trump is going after these schools and not the

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Speaker 3: University of Texas, the University of Maryland or things like that.

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Speaker 3: So I look, I mean, I think they should tap

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Speaker 3: any endowment and tell Trump to to fuck off, Like

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Speaker 3: what's it? What's it for?

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Speaker 2: Uh?

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Speaker 3: But I don't know, I don't want to say that,

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Speaker 3: like I am questioning the utility of like do Ivy

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Speaker 3: League schools make America better? I'm not sure about that.

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Speaker 2: Actually, well, I think that I think that they do

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Speaker 2: in the sense of, you know, the research that they

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Speaker 2: the research conduct is but but where else, like that's

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Speaker 2: you know, where the cutting edge research is happening, not

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Speaker 2: just Ivy leagues obviously, but in the universities. It's happening

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Speaker 2: in those laboratories. It's happening in those graduate departments. That's

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Speaker 2: where all of the scientific innovation is happening. Those ideas

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Speaker 2: are not coming from the private sector like that's economics

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Speaker 2: one oh one, right, that they will not fund them

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Speaker 2: until the research is at a certain stage then they

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Speaker 2: will fund them. But that research, those idea explorations that.

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Speaker 3: Happens within that happens.

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Speaker 2: Oh I'm talking about I'm talking about other like basic science,

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Speaker 2: not tech, that all happens in academia. So so I

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Speaker 2: think that the value here is absolutely enormous. And I

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Speaker 2: actually hate so obviously I'm Jewish, very sensitive to anti

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Speaker 2: Semitism stuff, but I hate that he's using that as

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Speaker 2: kind of to make people be like, oh, well, you know,

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Speaker 2: we're combating anti semitism. It's not that bad. No, like

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Speaker 2: this has nothing to do with anti semitism, because he

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Speaker 2: has plenty of very anti Semitic policies.

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Speaker 1: He's using that.

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Speaker 2: As a cover to basically assert his will and say that,

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Speaker 2: you know that I can dictate what universities can and

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Speaker 2: can't do. Academia is not perfect, far from perfect. We've

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Speaker 2: talked about this before. It needs to be reformed. But

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Speaker 2: Paul Weiss, like, what the fuck?

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Speaker 1: You know?

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Speaker 2: You have this happening, This muzzling people, just backing down

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Speaker 2: and not saying anything, happening everywhere you know, law firms,

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Speaker 2: and it's just to me, that's that's a very scary

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Speaker 2: precedent to set. I just read that the former head

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Speaker 2: of Doctors Without Borders had her presentation. I think it

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Speaker 2: was at NYU canceled for being anti government because she

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Speaker 2: was going to be talking about USAID cuts. Like that's

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Speaker 2: fucked up, right, Like that that kind of thing is

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Speaker 2: is totally fucked up, and people are scared. And the

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Speaker 2: moment that you're the most scared is when you actually

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Speaker 2: should start taking these risks and protesting because it's only

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Speaker 2: going to get worse. And you know, let's just look

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Speaker 2: at the big picture as opposed to like the nitty

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Speaker 2: gritty and say that this is not good. The fact

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Speaker 2: that Columbia kept capitulated is not good, setting a horrible precedent,

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Speaker 2: and I think it makes it even more important for

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Speaker 2: places like Harvard to say fuck you, and the fact

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Speaker 2: that they haven't is not good.

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Speaker 3: I'm not as sure that it's only going to get worse.

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Speaker 3: Trump is probably going to keep getting more unpopular, particularly

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Speaker 3: if the economy suffers due to I mean, we're like, oh,

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Speaker 3: we won the election on inflation, so let's make cars

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Speaker 3: more extensive like that seems like a pretty stupid idea,

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Speaker 3: Maria from a risk management standpoint, and.

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Speaker 1: Okay, paying higher prices night Americans will be.

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Speaker 3: Okay, investors are longer buy it. Like GM stock was

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Speaker 3: off quite a bit more than some of the four manufacturers.

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Speaker 3: Tesla's stock was off quite a bit. But you know,

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Speaker 3: I think Trump has been smart in the tactical sense

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Speaker 3: of trying to pack a lot in at the start.

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Speaker 3: When they adamare political capital, they're probably going to lose

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Speaker 3: political capital over time, and when they're resistance, I mean

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Speaker 3: that both kind of figurably and literally is kind of

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Speaker 3: like confused and it's combobulated. Look, there are lovers in

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Speaker 3: the system. The courts can fight back, people can protest.

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Speaker 3: We have a decentralized system of government in which states

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Speaker 3: and localities have a lot of power. Potentially their midterm

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Speaker 3: elections coming up. There are special elections increening one or

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Speaker 3: to today in Florida, re seats that the jup will

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Speaker 3: probably hold, but much closer than you would typically expect it.

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Speaker 3: If there's a huge surprise, then you know, and then

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Speaker 3: within the realm of remote possibility, I suppose. And by

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Speaker 3: the way, Democrats having well, I mean, look the racing

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Speaker 3: it's kind of more competitive, probably was in upstate New York,

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Speaker 3: but I mean stathetic. Harvard, right, by the way, is

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Speaker 3: no longer being nominated to the UN because Trump is

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Speaker 3: afraid of nominating a someone who in a district he

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Speaker 3: won by twenty one points because it might cut their

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Speaker 3: majority too much. Right, so you know, so there is

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Speaker 3: resistance elon Musk, you see, even more in popular than Trump.

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Speaker 3: The point is not lost though that like when you

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Speaker 3: create a precedent that you can cave and you saw,

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Speaker 3: by the way, this happened with with like Canada and

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Speaker 3: Mexico to some degree on tariffs. At first, the conservatives

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Speaker 3: in Canada were like, Okay, well, I just give you

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Speaker 3: this little tribune, right and then and their voters got

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Speaker 3: furious at them, right.

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Speaker 1: You know.

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Speaker 3: Also, some of the Harvard donors would be like, fuck you, Harvard.

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Speaker 3: I'm not if you could pitch like Trump, then I'm

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Speaker 3: not doing any of you anymore. So You're gonna cost you

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Speaker 3: money either way. And they have fifty two million dollars

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Speaker 3: to burn, billion dollars to burn, and so you know, again,

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Speaker 3: I'm not that I'm not that sympathetic, but I think

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Speaker 3: probably probably the worst hight paying job in the country

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Speaker 3: would be president of a major research IVY League university

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Speaker 3: right now.

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Speaker 2: Yes, and we know that the Columbia president has resigned again,

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Speaker 2: and yeah, this this is definitely an unprecedented kind of

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Speaker 2: assault on a lot in a lot of in a

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Speaker 2: lot of ways.

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Speaker 1: Let's see how it goes. Nate.

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Speaker 2: I hope that your optimism is warranted. I'm much more pessimistic.

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Speaker 2: I think it is going to get worse before it

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Speaker 2: gets better. If it gets better.

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Speaker 3: I'm not actually optimistic. I don't think about the picture

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Speaker 3: of the country. I mean, you know, look, Trump does

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Speaker 3: things and then the courts react. But I do think

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Speaker 3: you have to recognize though, that to some extent they

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Speaker 3: are signing from a position of weakness, right, They're not.

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Speaker 3: I mean, although even here let me qualify that a bit.

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Speaker 3: It is also true that like these I of the universes,

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Speaker 3: like I said, are unsympathetic targets, right, And the reason

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Speaker 3: why they kind of frame it around anti Semitism is

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Speaker 3: because that's an issue that like does capture some of

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Speaker 3: the center. But George, people were pissed off about the

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Speaker 3: congressional hearings in twenty twenty three, for example, the three

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Speaker 3: university presence and so like, so they're kind of like

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Speaker 3: tactically smart about like, oh, acting their targets a little bit.

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Speaker 3: But I don't know, yeah, I don't know.

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Speaker 2: Yeah, it's tactically I mean, it's obviously one hundred percent disingenuous,

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Speaker 2: but very tactically smart way for Trump forgetting what he wants,

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Speaker 2: which is this kind of culture where everyone is scared

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Speaker 2: to say anything, and that's why he's doing it and

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Speaker 2: framing it the way he is. It's actually like it's

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Speaker 2: a very savvy way of doing it. Which is why

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Speaker 2: it's very scary.

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Speaker 3: The last thing I'll say is that like history will

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Speaker 3: remember this, I don't need to dramatize this as the same

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Speaker 3: as like the most important pivot point in American history.

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Speaker 3: I'm just saying, like a lot of people have done

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Speaker 3: a lot of really cringey things in the first what

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Speaker 3: is it now, two and a half months of Trump, Right,

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Speaker 3: all the CEOs who met the need at the inauguration,

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Speaker 3: and all the people who are you know, but the networks,

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Speaker 3: even the liberals are now back to watching the news

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Speaker 3: who fired all their liberal correspondents, right, But like that

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Speaker 3: stuff will not age well if Trump goes down as

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Speaker 3: an unsuccessful president or worse dot right And again, I

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Speaker 3: think you can see the trajectory already toward him becoming

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Speaker 3: more unpopular. If you didn't fuck up the economy, it

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Speaker 3: might be a whole different ballgame. If you want to

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Speaker 3: be like a fucking dictator, then ruining the economy is

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Speaker 3: about the stupidest thing you can do in terms of

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Speaker 3: maintaining public support.

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Speaker 1: Yeah, I think that's right.

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Speaker 2: So I hope, I hope it all falls down around him,

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Speaker 2: and I hope you're right that the Sarah will be

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Speaker 2: remembered as that as opposed to the start of the

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Speaker 2: end offination democracy. If we're being dramatic, I hope we

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Speaker 2: don't get that far.

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Speaker 1: There's a there's.

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Speaker 3: A gray zone, now there are any democracy already has

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Speaker 3: been weekend a little bit right, get a little bit weaker.

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Speaker 1: Yeah, Let's let's hope the gray zone resolves.

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Speaker 2: In a good way and not in the dictatorial way.

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Speaker 2: Let's take a little break and talk about something that

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Speaker 2: is also newsy but very different. Let's talk about twenty

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Speaker 2: three and me. Have you ever given your genetic data

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Speaker 2: to a website?

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Speaker 3: No, and I don't think.

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Speaker 2: I don't think I would neither have I. I am

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Speaker 2: one of those people who forever I told everyone in

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Speaker 2: my family was like, do not ever upload your genetic

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Speaker 2: information to twenty three and meters, to ancestry dot com,

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Speaker 2: to any of those, do not give your genetic data

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Speaker 2: to any private corporation because of a lot of things.

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Speaker 2: First of all, you know obviously data security. Second of all,

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Speaker 2: you are not protected. You know, this is not health

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Speaker 2: services that hit backed does not protect you whatsoever. And

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Speaker 2: it's just it's just dumb. And also you can't see

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Speaker 2: the future. We were just talking about being in a

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Speaker 2: gray zone politically right now, like, who is your data

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Speaker 2: going to be sold to? Potentially? How will it be used?

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Speaker 2: How will you potentially be discriminated against in the future

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Speaker 2: once we know that ooh, this combination of genes equals

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Speaker 2: this in terms of your risk for this disease. And

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Speaker 2: so now insurance companies you know, are are going to

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Speaker 2: have access to that. You don't know any of this anyway.

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Speaker 2: I have never given my genetic information, and I think

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Speaker 2: that the risks for individuals at weigh any potential benefits

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Speaker 2: of being able to say, oh, look, Nate, you and

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Speaker 2: I are twentieth cousins once removed.

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Speaker 1: How cool is that?

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Speaker 3: Well, people can do that for that reason, for the

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Speaker 3: for the what's it called genealogy? Is that? What the

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Speaker 3: what do the Mormons do?

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Speaker 2: A lot of Oh I don't yeah, genealogy, Yeah, genealogy, Okay, yeah.

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Speaker 2: Ancestry dot com is all about so twenty three and

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Speaker 2: meter is all about health data. Ancestry dot com is

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Speaker 2: all about genealogy. Either way, you have to give your

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Speaker 2: genetic information too to do this, and I think people

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Speaker 2: did it as kind of a novelty thing curiosity, Right,

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Speaker 2: you want to find out stuff. But I think that

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Speaker 2: those motivations are not sufficient because of the risks that

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Speaker 2: a company it.

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Speaker 3: Yeah, I think you could also do genetics reading for

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Speaker 3: certain disease.

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Speaker 2: I mean they used to be so twenty three and

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Speaker 2: meters over promised and under delivered on that front because

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Speaker 2: genetics can we just like pause this and go back

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Speaker 2: out for a second and say, genetics is really complicated, right,

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Speaker 2: and there are very very few genetic conditions where it's

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Speaker 2: like this gene maps to this risk. Yes, there are

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Speaker 2: a few of them, but it's tiny, tiny, tiny, And

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Speaker 2: at first twenty three and me was trying to cover

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Speaker 2: everything and be like, oh, well there was one paper

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Speaker 2: about this and that, and so you can have false positive,

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Speaker 2: false negatives, like just stuff that there wasn't enough data for.

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Speaker 2: And then the type of testing they were doing is

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Speaker 2: not at the level that you would get if you actually,

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Speaker 2: you know, are in a doctor's office health you know

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Speaker 2: situation where you're getting screened for all of these things correctly.

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Speaker 2: And so there was a lot of uncertainty involved. There's

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Speaker 2: a lot of actually ethical gray zones, even if you're

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Speaker 2: doing it in a doctor's office, with screening for things

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Speaker 2: that are actually pretty black and white, like the BRCA

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Speaker 2: gene and breast cancer. Right, there's a lot of kind

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Speaker 2: of controversy around well, you know, how do you how

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Speaker 2: do you communicate it? You know, do you tell people

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Speaker 2: what can they do? What if they didn't want to

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Speaker 2: screen for it but you found out and there are

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Speaker 2: people you train doctors, and okay, how do you communicate

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Speaker 2: this risk?

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Speaker 1: What do you say?

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Speaker 2: You know, how do you give this life changing information

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Speaker 2: to someone twenty three and me? Like, there's none of that, right,

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Speaker 2: You just like get your results back and you're like,

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Speaker 2: oh wow, Like, oh my god, what am I supposed

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Speaker 2: to do with that? So there it was ethically fraud

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Speaker 2: even on that front. And I would not have used

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Speaker 2: it to find out my you know, genetic risk of something.

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Speaker 2: I would have gone to a doctor to get those tests.

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Speaker 3: Yeah, what I've seen friends who've done it. It's quite vague, right,

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Speaker 3: It's like, oh, you have an elevator risk of this

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Speaker 3: area or that area. Right, if you have elevated risk

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Speaker 3: of some condition in effects one and a hundred thousand people,

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Speaker 3: then you're probably harming yourself more with the extra stress

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Speaker 3: of that then, and you're learning altered about your chances.

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Speaker 3: I just don't trust anybody with giving away information. I

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Speaker 3: kind of assume it'll be leaked at some point.

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Speaker 2: If absolutely, if it gets there, should happens, and your

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Speaker 2: information is not secure. And I actually I hate, you know,

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Speaker 2: all biometrics, Like I hate that at this point, like

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Speaker 2: in the airports, you have to smile into the camera

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Speaker 2: and it always yeah I do. It's very easy, but

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Speaker 2: it's it is much faster, right, But we're giving up

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Speaker 2: so much privacy for convenience.

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Speaker 3: Yeah, travel is right. Yeah, travel is a right, not

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Speaker 3: a privilege. My partner of this character, it's like kind

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Speaker 3: of Mary Joe Quimby from the Simpsons, like or a Channy,

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Speaker 3: but like only campaigns and like frequent flyer complaints. We

432
00:22:51,164 --> 00:22:54,524
Speaker 3: will have a bit of sky lounge.

433
00:22:55,964 --> 00:22:57,604
Speaker 2: I think, I think, I think you've got to You've

434
00:22:57,644 --> 00:23:01,644
Speaker 2: got to hit on yours. No, it is, so that's

435
00:23:01,644 --> 00:23:03,924
Speaker 2: the thing. I do it because it's much faster, and

436
00:23:03,964 --> 00:23:06,164
Speaker 2: there's always a thing. So I was gonna say, there's

437
00:23:06,164 --> 00:23:08,084
Speaker 2: always a thing that says, oh you can opt out, right,

438
00:23:08,124 --> 00:23:10,524
Speaker 2: you don't have to do the biometric thing.

439
00:23:10,844 --> 00:23:12,044
Speaker 1: We delete the data right.

440
00:23:11,964 --> 00:23:13,364
Speaker 2: Away, and I was like, oh, but it's going to

441
00:23:13,404 --> 00:23:15,244
Speaker 2: take If I say I want to opt out, it's

442
00:23:15,284 --> 00:23:16,964
Speaker 2: going to take me like twenty minutes to get through

443
00:23:17,004 --> 00:23:18,924
Speaker 2: security because then they're going to pull me aside and

444
00:23:18,924 --> 00:23:19,724
Speaker 2: do all this stuff.

445
00:23:19,844 --> 00:23:21,404
Speaker 1: So I don't opt out. I just do that.

446
00:23:21,764 --> 00:23:24,284
Speaker 2: But I still don't love it, because you know, you're

447
00:23:24,324 --> 00:23:27,404
Speaker 2: giving all of your facial data, biometric data. I don't

448
00:23:27,404 --> 00:23:29,884
Speaker 2: want it, you know, as far as I can tell, Like,

449
00:23:30,004 --> 00:23:33,404
Speaker 2: I'd rather just not give as much data as I

450
00:23:33,484 --> 00:23:37,684
Speaker 2: can to the government, to private corporations. But genetic data

451
00:23:37,764 --> 00:23:39,924
Speaker 2: is something that like that is something that you can

452
00:23:39,964 --> 00:23:44,444
Speaker 2: really control. It doesn't make travel easier. So I think

453
00:23:44,484 --> 00:23:47,244
Speaker 2: that the like the risk reward trade offs there are

454
00:23:47,284 --> 00:23:50,084
Speaker 2: just soberblown and now people are finally coming to their

455
00:23:50,084 --> 00:23:52,524
Speaker 2: senses and they're like, oh shit, it's going bankrupt. Like

456
00:23:52,564 --> 00:23:55,524
Speaker 2: here's how you delete your data? Really, is my data

457
00:23:55,564 --> 00:23:57,604
Speaker 2: only stored in one place? Is it really all going

458
00:23:57,684 --> 00:23:59,924
Speaker 2: to be? Like there are a lot of questions here,

459
00:24:00,004 --> 00:24:01,524
Speaker 2: Like I wouldn't be so sure.

460
00:24:02,284 --> 00:24:05,444
Speaker 3: Yeah, the California age called for customers to delete their

461
00:24:05,484 --> 00:24:09,844
Speaker 3: twenty three aeters data, So probably good idea, you know that.

462
00:24:09,884 --> 00:24:11,484
Speaker 3: I think I think maybe I'm not as much of

463
00:24:11,524 --> 00:24:16,324
Speaker 3: a privacy and consent I think the improved efficiency and

464
00:24:16,404 --> 00:24:18,684
Speaker 3: airport security screening. And by the way, also if you

465
00:24:18,804 --> 00:24:22,204
Speaker 3: traveled internationally, it's much faster now most entries to get

466
00:24:22,204 --> 00:24:24,524
Speaker 3: out of there when you're when you're going through customs

467
00:24:24,524 --> 00:24:26,284
Speaker 3: and so forth. I know, I think that might be

468
00:24:26,284 --> 00:24:28,484
Speaker 3: a category where I think it's it's worth the trade off.

469
00:24:29,364 --> 00:24:33,564
Speaker 3: I like, I really about guiling your time in a minute.

470
00:24:33,324 --> 00:24:37,044
Speaker 2: Right yeah, And like I said, Nate, I actually like

471
00:24:37,204 --> 00:24:40,004
Speaker 2: I I have made that trade off when traveling as well.

472
00:24:40,364 --> 00:24:42,364
Speaker 2: All of these things are trade offs, and you do

473
00:24:42,484 --> 00:24:45,324
Speaker 2: need to realize that they're all. You know, there is

474
00:24:45,444 --> 00:24:48,724
Speaker 2: always going to be a privacy concern and there's always

475
00:24:48,724 --> 00:24:51,084
Speaker 2: going to be a concern with how your data is stored,

476
00:24:51,204 --> 00:24:54,284
Speaker 2: how it's used, with all of these things, and you

477
00:24:54,324 --> 00:24:55,284
Speaker 2: just need to think about it.

478
00:24:55,324 --> 00:24:57,444
Speaker 3: I did have a trainer one time who found out

479
00:24:57,484 --> 00:24:59,924
Speaker 3: that he had some degree of Middle Eastern in ancestry,

480
00:24:59,924 --> 00:25:02,164
Speaker 3: which he didn't know about. So that was interesting. That

481
00:25:02,324 --> 00:25:04,404
Speaker 3: changed the self conception I think a little bit. So

482
00:25:04,564 --> 00:25:05,404
Speaker 3: I was in wit guy.

483
00:25:05,284 --> 00:25:07,924
Speaker 2: From Well and I mean a lot of times people

484
00:25:08,004 --> 00:25:10,844
Speaker 2: you know who do give their genetic information do find

485
00:25:10,844 --> 00:25:13,884
Speaker 2: out things right like there is I understand why people

486
00:25:13,924 --> 00:25:16,524
Speaker 2: are curious, especially like there are people who can't find

487
00:25:16,524 --> 00:25:19,284
Speaker 2: you who don't know who their parents are. Well, sometimes

488
00:25:19,324 --> 00:25:21,204
Speaker 2: people think they know who their parents are and find

489
00:25:21,204 --> 00:25:24,324
Speaker 2: out should that they really didn't want to find out, right,

490
00:25:24,404 --> 00:25:26,884
Speaker 2: Like a lot of family secrets coming out. I get

491
00:25:26,884 --> 00:25:30,204
Speaker 2: the impulse, but you always, to me, like, you just

492
00:25:30,284 --> 00:25:33,524
Speaker 2: always need to think through what the next steps are.

493
00:25:33,564 --> 00:25:36,284
Speaker 2: And right now we're seeing that, right, and we're seeing

494
00:25:36,284 --> 00:25:39,404
Speaker 2: that just play out in real time. Do you think so,

495
00:25:39,684 --> 00:25:43,604
Speaker 2: I've like imagine trying to delete your data from Facebook, right,

496
00:25:43,684 --> 00:25:46,324
Speaker 2: Like I know people who tried over and over and

497
00:25:46,324 --> 00:25:49,204
Speaker 2: it's just impossible, right, Like those those photos like that

498
00:25:49,204 --> 00:25:52,804
Speaker 2: that shouldn't get deleted. So now like deleting your data

499
00:25:52,844 --> 00:25:55,124
Speaker 2: from twenty three on me, Like, I don't think that

500
00:25:55,204 --> 00:25:57,764
Speaker 2: data is getting deleted in the way that you think.

501
00:25:59,164 --> 00:26:04,004
Speaker 2: I do think that more and more, as we're moving

502
00:26:04,364 --> 00:26:09,164
Speaker 2: to our technological future, certain things like you know, facial recognition,

503
00:26:09,684 --> 00:26:13,084
Speaker 2: they're so ubiquitous that it's really like it's almost basically

504
00:26:13,124 --> 00:26:16,604
Speaker 2: impossible to opt out, right, Like I think that we're

505
00:26:16,644 --> 00:26:19,404
Speaker 2: probably nearing that point with some of these things, but

506
00:26:19,444 --> 00:26:21,524
Speaker 2: not with all of them, And so the little bits

507
00:26:21,524 --> 00:26:23,644
Speaker 2: of privacy that we still can protect I think we

508
00:26:23,684 --> 00:26:25,164
Speaker 2: should well.

509
00:26:25,204 --> 00:26:28,124
Speaker 3: And AI AFFECTSMOS too, in part because like basically they

510
00:26:28,244 --> 00:26:30,884
Speaker 3: just kind of the AI models have a corpus of

511
00:26:30,964 --> 00:26:34,324
Speaker 3: data and they just silk up all the data trained

512
00:26:34,404 --> 00:26:37,124
Speaker 3: on it for a while and then have model ways

513
00:26:37,164 --> 00:26:39,564
Speaker 3: to produce outputs. Right, It's kind of hard once you

514
00:26:39,564 --> 00:26:42,284
Speaker 3: train the model, it's very hard to go back and say, oh,

515
00:26:42,284 --> 00:26:45,884
Speaker 3: we weren't supposed to use Maria's DNA sequence right for

516
00:26:46,004 --> 00:26:50,004
Speaker 3: this new genomic AI that we have right untrained, Well,

517
00:26:50,044 --> 00:26:52,484
Speaker 3: we're gonna We're gonna untrained, and then we'll come back

518
00:26:52,524 --> 00:26:55,004
Speaker 3: in a year and waste billions of dollars in I mean,

519
00:26:55,004 --> 00:26:57,044
Speaker 3: it doesn't really work. And I think we're probably in

520
00:26:57,084 --> 00:27:02,124
Speaker 3: a world where there's going to need to be more surveillance,

521
00:27:02,124 --> 00:27:04,004
Speaker 3: which I'm not happy about, but I think that's direction

522
00:27:04,044 --> 00:27:04,724
Speaker 3: that we're headed in.

523
00:27:05,164 --> 00:27:08,924
Speaker 2: Yeah, I do think that, uh, this is where we're going.

524
00:27:09,044 --> 00:27:10,764
Speaker 2: There's a really good book about this, by the way,

525
00:27:10,844 --> 00:27:14,644
Speaker 2: so Cash Hell's book Your Face Belongs to Us, which

526
00:27:14,684 --> 00:27:20,524
Speaker 2: is a really interesting and it's a book about facial

527
00:27:20,564 --> 00:27:24,244
Speaker 2: recognition and privacy concerns. She's a reporter with The New

528
00:27:24,324 --> 00:27:28,964
Speaker 2: York Times. She's also a poker player night, So I'm

529
00:27:29,084 --> 00:27:31,924
Speaker 2: very glad Nate that you have Also, you also do

530
00:27:31,964 --> 00:27:34,844
Speaker 2: not need to pull your data, your unpullable data from

531
00:27:34,884 --> 00:27:39,284
Speaker 2: twenty three and me, and I hope you know, for

532
00:27:39,564 --> 00:27:44,724
Speaker 2: everyone's sake that this resolves in a nicer way than

533
00:27:44,724 --> 00:27:48,244
Speaker 2: it could, because I'm not at all optimistic that this

534
00:27:48,444 --> 00:27:51,764
Speaker 2: data isn't going to be sold to companies that are

535
00:27:51,844 --> 00:27:53,444
Speaker 2: going to use it, not in the way that you

536
00:27:53,524 --> 00:27:57,644
Speaker 2: intended when you initially sent those little samples of saliva

537
00:27:58,084 --> 00:28:02,644
Speaker 2: to twenty three and me. On that note, Nate, let's

538
00:28:03,004 --> 00:28:05,564
Speaker 2: take a break, and I hope that you and all

539
00:28:05,604 --> 00:28:12,604
Speaker 2: of our listeners use that break productively, because time is valuable.

540
00:28:15,044 --> 00:28:16,684
Speaker 3: A little, a little force pery of it.

541
00:28:16,884 --> 00:28:37,444
Speaker 2: You know, Well, Okay, I did my best. This is

542
00:28:37,844 --> 00:28:42,764
Speaker 2: a question that doesn't come up nearly enough, but I

543
00:28:42,764 --> 00:28:45,644
Speaker 2: think it's really really important, which is, how do you

544
00:28:45,844 --> 00:28:49,524
Speaker 2: actually place a value right on your time? I made

545
00:28:49,524 --> 00:28:52,044
Speaker 2: a I made a bad joke, Nate, you you called

546
00:28:52,084 --> 00:28:56,564
Speaker 2: it forced. I feel very heard about using our break

547
00:28:56,644 --> 00:29:00,204
Speaker 2: productively because time is money, and we I mean, time

548
00:29:00,284 --> 00:29:02,884
Speaker 2: is money is such a cliche, but it's a cliche

549
00:29:02,964 --> 00:29:06,604
Speaker 2: for a reason. That's actually the case. Right every single

550
00:29:06,764 --> 00:29:10,164
Speaker 2: time that we do something, we're making trade offs. We're

551
00:29:10,204 --> 00:29:12,724
Speaker 2: not doing something else. And this is the whole point

552
00:29:12,764 --> 00:29:16,284
Speaker 2: of getting paid. It's your time. You're literally trading off

553
00:29:16,644 --> 00:29:19,724
Speaker 2: time that you would rather be doing something else usually,

554
00:29:20,164 --> 00:29:22,844
Speaker 2: or time that you're getting paid to do something. And

555
00:29:22,924 --> 00:29:26,084
Speaker 2: so this is a calculus that I think we're always making,

556
00:29:26,484 --> 00:29:29,244
Speaker 2: but we're not always explicitly aware that we're making it.

557
00:29:29,284 --> 00:29:31,364
Speaker 2: But I think we could make much better decisions if

558
00:29:31,404 --> 00:29:35,924
Speaker 2: we were explicitly aware and actually could kind of game

559
00:29:36,004 --> 00:29:38,924
Speaker 2: theorize it a little bit and try to figure out, Okay, well,

560
00:29:39,284 --> 00:29:40,164
Speaker 2: you know how much.

561
00:29:40,004 --> 00:29:42,004
Speaker 1: Do I value my time? Is this worth it? Is

562
00:29:42,044 --> 00:29:42,484
Speaker 1: that worth it?

563
00:29:42,524 --> 00:29:44,484
Speaker 2: Obviously you don't want to go through your entire life

564
00:29:44,764 --> 00:29:47,324
Speaker 2: thinking that way, but I think that for big decisions,

565
00:29:47,404 --> 00:29:52,644
Speaker 2: for those types of trade offs, it is an interesting

566
00:29:52,684 --> 00:29:54,964
Speaker 2: way of looking at it, is that how do you

567
00:29:55,204 --> 00:29:59,444
Speaker 2: actually go about this night? Do you consciously think you

568
00:29:59,484 --> 00:30:01,084
Speaker 2: know what is the value of my time?

569
00:30:02,124 --> 00:30:03,084
Speaker 1: Good question, And let.

570
00:30:02,924 --> 00:30:06,884
Speaker 3: Me acknowledge upfront that this is like a little bit

571
00:30:07,204 --> 00:30:09,684
Speaker 3: I'm not big on, like the privilege trip. Tell me

572
00:30:09,924 --> 00:30:11,404
Speaker 3: I acknowledge though, this is like a little bit of

573
00:30:11,404 --> 00:30:14,684
Speaker 3: maybe a kind of a privilegy conversation where if you're

574
00:30:14,724 --> 00:30:17,404
Speaker 3: somebody who has the opportunity to like to make money,

575
00:30:17,484 --> 00:30:19,644
Speaker 3: or have more than one opportunity you can pursue, right,

576
00:30:20,004 --> 00:30:23,844
Speaker 3: and you have kind of more capacity to take on

577
00:30:24,444 --> 00:30:26,884
Speaker 3: additional work or valuable things to trade off with. Right.

578
00:30:27,884 --> 00:30:31,764
Speaker 3: In my case, for example, I'm considering whether to accept

579
00:30:32,404 --> 00:30:35,964
Speaker 3: consulting work, right, because there you're actually like kind of

580
00:30:36,044 --> 00:30:40,084
Speaker 3: like setting a rate that you're paid on an hourly basis, right,

581
00:30:40,164 --> 00:30:43,124
Speaker 3: Or sometimes I mean, no huge secret if you're if

582
00:30:43,124 --> 00:30:46,124
Speaker 3: you're an author who sells books like Marie, or I'll

583
00:30:46,124 --> 00:30:49,644
Speaker 3: get opportunities to do speaking gigs where you travel. I'm

584
00:30:49,644 --> 00:30:51,684
Speaker 3: out here in California for one, for example, right now,

585
00:30:51,764 --> 00:30:55,644
Speaker 3: and they pay you to talk, and maybe the talk

586
00:30:55,804 --> 00:30:58,124
Speaker 3: isn't that much time, but then you have two old

587
00:30:58,164 --> 00:31:00,764
Speaker 3: days you burn on travel, for example. So I think

588
00:31:00,764 --> 00:31:04,764
Speaker 3: you have to like think about these things fairly explicitly.

589
00:31:05,244 --> 00:31:09,084
Speaker 3: That's especially through like when you're I mean I'm essentially

590
00:31:09,164 --> 00:31:12,764
Speaker 3: a freelancer, right, or maybe a small business owner where

591
00:31:12,804 --> 00:31:16,204
Speaker 3: I write posts for Silver Bulletin newsletter. The more posts

592
00:31:16,284 --> 00:31:18,684
Speaker 3: you write, the more opportunities there are people to subscribe.

593
00:31:18,724 --> 00:31:22,724
Speaker 3: And so I probably have some calculation of like what

594
00:31:22,884 --> 00:31:25,364
Speaker 3: is the opportunity cost. Right, If I'm traveling on a

595
00:31:25,404 --> 00:31:27,484
Speaker 3: plane and the Wi Fi goes out, that's one less

596
00:31:27,524 --> 00:31:29,484
Speaker 3: post that I write. How much money would have for

597
00:31:29,604 --> 00:31:32,284
Speaker 3: sicken from that post. I mean, you know, I think

598
00:31:32,884 --> 00:31:36,724
Speaker 3: sometimes it's good to be honest with yourself about that

599
00:31:36,844 --> 00:31:40,564
Speaker 3: kind of thing. I also think that, like there's things

600
00:31:40,604 --> 00:31:43,244
Speaker 3: you want to treat as constraints. Right, So I'm going

601
00:31:43,324 --> 00:31:46,084
Speaker 3: to play I don't know, let's say, four or five

602
00:31:46,164 --> 00:31:49,044
Speaker 3: weeks of the World Series of Poker this summer, maybe

603
00:31:49,084 --> 00:31:50,804
Speaker 3: two thirds half to two thirds of the schedules about

604
00:31:50,804 --> 00:31:54,124
Speaker 3: what I settled into, right, That is clearly a bad

605
00:31:54,164 --> 00:31:57,924
Speaker 3: trade off from like an opportunity cost standpoint. Right, I'm

606
00:31:57,964 --> 00:32:02,524
Speaker 3: probably plus ev in most of the events that I play,

607
00:32:03,444 --> 00:32:07,964
Speaker 3: but if that leads to several fewer newsletter posts or

608
00:32:08,004 --> 00:32:10,684
Speaker 3: consulting opportunities, the trade af's pretty high. It was like

609
00:32:10,804 --> 00:32:14,084
Speaker 3: much easier where I worked for a giant, baseless corporation,

610
00:32:14,244 --> 00:32:16,004
Speaker 3: and like I was kind of like paying a fixed

611
00:32:16,044 --> 00:32:18,684
Speaker 3: salary and kind of working on the company dine basically,

612
00:32:19,124 --> 00:32:20,684
Speaker 3: So you know, I mean, it really kind of came

613
00:32:20,724 --> 00:32:22,884
Speaker 3: to light last year when like I was playing in

614
00:32:22,884 --> 00:32:26,564
Speaker 3: some roughly low buying event at the wind and then

615
00:32:27,164 --> 00:32:29,964
Speaker 3: Trump is charged with all these convicted I should say,

616
00:32:29,964 --> 00:32:32,364
Speaker 3: of all these felonies, and I have to write a

617
00:32:32,364 --> 00:32:35,764
Speaker 3: post about that, and I kind of like deliberately kind

618
00:32:35,764 --> 00:32:37,924
Speaker 3: of punted because I'm like, okay, literally, the value of

619
00:32:37,964 --> 00:32:41,884
Speaker 3: my stack here is like worthless than being really quick

620
00:32:41,924 --> 00:32:45,844
Speaker 3: on this news. But you know, or likewise, like I

621
00:32:46,124 --> 00:32:49,284
Speaker 3: was this past weekend at the New Orleans Book Festival,

622
00:32:49,364 --> 00:32:53,924
Speaker 3: which is a great event attracting lots of brand name

623
00:32:54,124 --> 00:32:57,564
Speaker 3: and obscure like authorial talent. Right this, by the way,

624
00:32:57,684 --> 00:32:59,324
Speaker 3: is free. It's on the campus at Too Lane, and

625
00:32:59,324 --> 00:33:01,084
Speaker 3: so it's kind of in the in the spirit of

626
00:33:01,124 --> 00:33:03,684
Speaker 3: like Edinburgh Fringefest or something where they want to like

627
00:33:04,084 --> 00:33:08,164
Speaker 3: take this kind of medium sized community and have this

628
00:33:08,244 --> 00:33:10,844
Speaker 3: festival once. A ye, I didn't get paid for that,

629
00:33:10,884 --> 00:33:13,244
Speaker 3: but like it's kind of like sometimes the caution either

630
00:33:13,324 --> 00:33:18,204
Speaker 3: be zero or a lot and yeah, right.

631
00:33:18,204 --> 00:33:20,884
Speaker 2: Yeah, no, I actually agree with that. And by the way,

632
00:33:21,164 --> 00:33:23,964
Speaker 2: to your first point, I think that's a really really

633
00:33:24,044 --> 00:33:28,044
Speaker 2: important point where time is money is very relevant in

634
00:33:28,084 --> 00:33:31,444
Speaker 2: the sense that this is something that we're privileged to

635
00:33:31,484 --> 00:33:33,284
Speaker 2: be able to think about it this way. And I've

636
00:33:33,324 --> 00:33:36,684
Speaker 2: actually written about this about time scarcity being like the

637
00:33:36,924 --> 00:33:40,284
Speaker 2: one of the huge constraints on poverty, right, And Cindilmula

638
00:33:40,324 --> 00:33:43,004
Speaker 2: Nathan at the University of Chicago has done a ton

639
00:33:43,164 --> 00:33:47,964
Speaker 2: of research into this about how time poverty is a thing, right,

640
00:33:48,084 --> 00:33:50,524
Speaker 2: and that if you're actually if you're poor, like this

641
00:33:50,644 --> 00:33:55,124
Speaker 2: is one of the biggest, one of the biggest barriers

642
00:33:55,164 --> 00:33:59,844
Speaker 2: to kind of getting out of poverty because all of

643
00:33:59,844 --> 00:34:01,804
Speaker 2: these things we take for granted, like, oh, I have

644
00:34:01,924 --> 00:34:04,924
Speaker 2: time to think through this decision. You know, the cognitive

645
00:34:04,964 --> 00:34:09,764
Speaker 2: overload of not not having that flexibility is actually huge, right,

646
00:34:09,844 --> 00:34:13,884
Speaker 2: because you're just living paycheck to paycheck. You don't have childcare, right,

647
00:34:13,884 --> 00:34:17,524
Speaker 2: you're not sleeping enough. All of these different things are

648
00:34:17,924 --> 00:34:21,484
Speaker 2: adding to the cognitive load, and you can't make choices

649
00:34:21,564 --> 00:34:24,604
Speaker 2: the way that you know you can afford to make

650
00:34:24,684 --> 00:34:27,964
Speaker 2: choices if you're living at a higher subsistence level. So

651
00:34:27,964 --> 00:34:30,884
Speaker 2: if people are interested in that research, highly recommend some

652
00:34:30,924 --> 00:34:33,484
Speaker 2: deals work, and that's something that we should we should

653
00:34:33,524 --> 00:34:36,844
Speaker 2: definitely not take for granted. But I agree with you that,

654
00:34:37,044 --> 00:34:39,764
Speaker 2: you know, when I think about big things like speaking engagements,

655
00:34:39,764 --> 00:34:42,644
Speaker 2: like what I'm going to take on, I usually think

656
00:34:42,684 --> 00:34:45,364
Speaker 2: about like what is the total time, right, It's never

657
00:34:45,564 --> 00:34:48,044
Speaker 2: just like an hour talk, Right, it's how long does

658
00:34:48,084 --> 00:34:50,644
Speaker 2: it take me to travel there? What else is it disrupting?

659
00:34:51,004 --> 00:34:53,524
Speaker 2: Like how long do I prepare? Like all all of

660
00:34:53,564 --> 00:34:56,204
Speaker 2: these different things add up, and you do need to

661
00:34:56,244 --> 00:34:58,244
Speaker 2: try to make that trade off. And sometimes I'll do

662
00:34:58,284 --> 00:35:00,684
Speaker 2: things for free if it's for a cause an organization,

663
00:35:00,884 --> 00:35:04,124
Speaker 2: like something that's important like book festivals. Right, I think

664
00:35:04,164 --> 00:35:07,244
Speaker 2: that that's an important value to the community, and so

665
00:35:07,324 --> 00:35:09,924
Speaker 2: you will just do that. And sometimes I will actually

666
00:35:09,964 --> 00:35:13,444
Speaker 2: take a lot less for something just because it's fun

667
00:35:13,444 --> 00:35:17,644
Speaker 2: to do, Like I will sometimes take writing assignments because

668
00:35:17,644 --> 00:35:19,564
Speaker 2: I want to write about this and like I actually

669
00:35:19,644 --> 00:35:22,444
Speaker 2: think that this is interesting, and like I will take

670
00:35:22,524 --> 00:35:26,084
Speaker 2: less than I would normally take because I enjoy it, right,

671
00:35:26,124 --> 00:35:28,124
Speaker 2: and there's going to be there's going to be something

672
00:35:28,164 --> 00:35:31,164
Speaker 2: else there for me. So it's not just money, right,

673
00:35:31,204 --> 00:35:31,924
Speaker 2: it's how much am.

674
00:35:31,844 --> 00:35:32,524
Speaker 1: I enjoying it?

675
00:35:32,604 --> 00:35:34,804
Speaker 2: Like what else? What else is there? What are their

676
00:35:34,804 --> 00:35:38,524
Speaker 2: trade offs are there? So that the calculus, just like

677
00:35:38,564 --> 00:35:40,964
Speaker 2: with all expected value calculations. I think one of the

678
00:35:41,004 --> 00:35:43,924
Speaker 2: reasons that you're still playing the World series, even though

679
00:35:44,124 --> 00:35:48,044
Speaker 2: technically speaking, is probably negative ev on some levels, because

680
00:35:48,044 --> 00:35:51,404
Speaker 2: you enjoy it, right, you get some intrinsic enjoyment out

681
00:35:51,404 --> 00:35:54,004
Speaker 2: of playing this, out of the competition, you know, out

682
00:35:54,044 --> 00:35:56,804
Speaker 2: of potentially winning. And the way that I also think

683
00:35:56,804 --> 00:35:59,564
Speaker 2: about it is well, it's actually huge for my brand

684
00:35:59,684 --> 00:36:02,404
Speaker 2: if I end up doing really well, right, like winning

685
00:36:02,444 --> 00:36:05,564
Speaker 2: a bracelet, that ev of that is insane and so

686
00:36:05,924 --> 00:36:09,084
Speaker 2: that you know, will help me book future speaking engagements

687
00:36:09,124 --> 00:36:11,644
Speaker 2: and Celtic work at all of this because it helps

688
00:36:11,684 --> 00:36:14,164
Speaker 2: my profile. And so they are all of these different

689
00:36:14,364 --> 00:36:18,804
Speaker 2: nuanced levels of calculations that go on, and so something

690
00:36:18,924 --> 00:36:22,004
Speaker 2: is not It might not be as straightforward as oh,

691
00:36:22,204 --> 00:36:24,404
Speaker 2: an hour speth doing this is not an hour spent

692
00:36:24,484 --> 00:36:24,804
Speaker 2: doing that.

693
00:36:25,364 --> 00:36:29,284
Speaker 3: Yeah, look, I would push back on that slightly, only

694
00:36:29,324 --> 00:36:30,804
Speaker 3: in the sense that if you kind of calculate, like

695
00:36:30,804 --> 00:36:32,484
Speaker 3: what are your odds of winning? You already have bracelet?

696
00:36:32,524 --> 00:36:36,444
Speaker 3: By the way, what are you but not wondering? I

697
00:36:36,444 --> 00:36:38,404
Speaker 3: guess the summer worlds here, like, what are the odds

698
00:36:38,444 --> 00:36:41,564
Speaker 3: of winning one? If you play two thirds of the schedule?

699
00:36:41,564 --> 00:36:45,364
Speaker 3: I mean in probably fairly low, right, And so you

700
00:36:45,404 --> 00:36:48,164
Speaker 3: can kind of what I kind of say is like,

701
00:36:49,844 --> 00:36:52,124
Speaker 3: people you have to the point of life, are not

702
00:36:52,164 --> 00:36:53,244
Speaker 3: the only point of life? Right?

703
00:36:54,324 --> 00:36:56,524
Speaker 1: Well, what's the meaning of life? Night I'm right that

704
00:36:56,564 --> 00:36:57,684
Speaker 1: we're all listening.

705
00:36:59,364 --> 00:37:01,524
Speaker 3: To be a good person, to contribute intellectually into it,

706
00:37:01,644 --> 00:37:03,684
Speaker 3: but to also enjoy yourself, right, And if like the

707
00:37:04,244 --> 00:37:07,364
Speaker 3: doing poker is one of the things you most enjoy,

708
00:37:07,604 --> 00:37:10,604
Speaker 3: and the World series pokenturmins can be a grind, right,

709
00:37:10,644 --> 00:37:14,884
Speaker 3: but when you make those final tables and day threes,

710
00:37:14,964 --> 00:37:17,684
Speaker 3: it's one of the most fun things ever. It kind

711
00:37:17,724 --> 00:37:21,524
Speaker 3: of also, I think is good for experience and character

712
00:37:21,564 --> 00:37:24,004
Speaker 3: building to play under high pressure, to kind of simulating.

713
00:37:24,044 --> 00:37:26,004
Speaker 3: So it's real hig pressure because the money GE's pretty

714
00:37:26,004 --> 00:37:28,324
Speaker 3: big if you actually are deep in a World series event.

715
00:37:29,324 --> 00:37:31,644
Speaker 3: So it's like, kind of, what's the point if, like

716
00:37:31,644 --> 00:37:34,604
Speaker 3: I'm not making time for the things that I enjoy, Right,

717
00:37:34,604 --> 00:37:36,404
Speaker 3: what's the whole point of like working so hard like

718
00:37:36,484 --> 00:37:39,004
Speaker 3: last year during election? If I if I, if I

719
00:37:39,044 --> 00:37:42,004
Speaker 3: can't sometimes relax a little bit, you know, I mean

720
00:37:42,244 --> 00:37:44,604
Speaker 3: the value of that is I you know, I'm now

721
00:37:45,244 --> 00:37:48,484
Speaker 3: yet more aware of kind of the privilegedness of this conversation.

722
00:37:48,644 --> 00:37:50,844
Speaker 3: But like, at the same time, I think people allow

723
00:37:50,884 --> 00:37:54,644
Speaker 3: themselves at all places in the income ladder to be

724
00:37:54,804 --> 00:38:00,004
Speaker 3: bogged down in jobs that aren't getting them anywhere in particular,

725
00:38:00,204 --> 00:38:03,764
Speaker 3: And it's not just an immediate time cost, but the

726
00:38:03,844 --> 00:38:08,444
Speaker 3: optionality cost. I think, you know, in general, people ought

727
00:38:08,444 --> 00:38:11,004
Speaker 3: to think more abouttionality. We're can I put myself in

728
00:38:11,044 --> 00:38:13,604
Speaker 3: a place where I'll have more options? That's related to

729
00:38:13,644 --> 00:38:17,844
Speaker 3: the idea of opportunity cost. But yeah, but it's it's

730
00:38:17,884 --> 00:38:21,604
Speaker 3: like splitting tens in black check. If you already make twenty,

731
00:38:21,964 --> 00:38:23,284
Speaker 3: you're like, oh, I can get even more of this

732
00:38:23,324 --> 00:38:25,604
Speaker 3: fi Splitting No. Twenty is already a hard totally get.

733
00:38:25,604 --> 00:38:28,764
Speaker 3: So it's like it's a fish move to split tens

734
00:38:28,844 --> 00:38:31,564
Speaker 3: in blackjack. But yeah, I don't, I don't know. I

735
00:38:31,764 --> 00:38:35,884
Speaker 3: I actually kind of carve out a lot of time

736
00:38:36,124 --> 00:38:40,204
Speaker 3: for for non productive work, and kind of what happens

737
00:38:40,244 --> 00:38:42,964
Speaker 3: sometimes I wind up backing into doing productive work. Anyway.

738
00:38:42,964 --> 00:38:44,564
Speaker 3: You come home from aren't you going to shirt the

739
00:38:44,564 --> 00:38:46,684
Speaker 3: web a bit? And then all you're like writing a

740
00:38:46,764 --> 00:38:49,564
Speaker 3: post or collecting some data for a spreadsheet.

741
00:38:49,124 --> 00:38:49,604
Speaker 1: Et cetera.

742
00:38:50,284 --> 00:38:55,004
Speaker 2: Yeah, Well, actually that that dovetails very nicely with what

743
00:38:55,084 --> 00:38:57,564
Speaker 2: I was just about to say, which is that for

744
00:38:57,684 --> 00:38:59,644
Speaker 2: people like us Nate who write you know, who are

745
00:38:59,764 --> 00:39:04,844
Speaker 2: journalists who actually you know, are constantly thinking about about

746
00:39:05,244 --> 00:39:08,364
Speaker 2: about writing about what we're working on. I find that

747
00:39:08,404 --> 00:39:10,884
Speaker 2: a lot of times that I'm being quote unquote unproductive

748
00:39:11,284 --> 00:39:13,404
Speaker 2: is when I end up coming up with ideas, coming

749
00:39:13,444 --> 00:39:16,724
Speaker 2: up with connections, reading something because you know, I'm just

750
00:39:17,484 --> 00:39:19,844
Speaker 2: like I'm tired, and so I end up you know,

751
00:39:19,924 --> 00:39:23,484
Speaker 2: watching a show or or reading reading something that I

752
00:39:23,484 --> 00:39:27,324
Speaker 2: wouldn't otherwise read because it's not strictly speaking for work,

753
00:39:27,604 --> 00:39:30,004
Speaker 2: and that ends up inspiring something and it ends up

754
00:39:30,044 --> 00:39:33,324
Speaker 2: being productive work. And so I actually, you know, I

755
00:39:33,364 --> 00:39:35,844
Speaker 2: think that sometimes you just don't know where things are

756
00:39:35,884 --> 00:39:37,564
Speaker 2: going to lead, and you do need to just give

757
00:39:37,604 --> 00:39:40,324
Speaker 2: yourself that freedom, and sometimes that ends up being very

758
00:39:40,364 --> 00:39:44,884
Speaker 2: productive time because otherwise, I think burnout takes a huge toll.

759
00:39:45,204 --> 00:39:47,564
Speaker 2: And I've burned out before, like I've given myself a

760
00:39:47,604 --> 00:39:51,324
Speaker 2: nervous breakdown before like that. It's not fun and it

761
00:39:51,404 --> 00:39:55,764
Speaker 2: actually it really cuts down on your productivity and your

762
00:39:55,804 --> 00:39:58,004
Speaker 2: ability to do things. So I think if you have

763
00:39:58,084 --> 00:40:00,564
Speaker 2: the privilege to kind of step back, I think that

764
00:40:00,564 --> 00:40:01,884
Speaker 2: that's a really good thing to do.

765
00:40:03,244 --> 00:40:05,484
Speaker 3: No, absolutely right, And sometimes I think, you know, the

766
00:40:05,564 --> 00:40:09,164
Speaker 3: last thing i'd say or maybe I'll moveless is now.

767
00:40:09,524 --> 00:40:12,764
Speaker 3: Then you do get in situations where you have a

768
00:40:12,804 --> 00:40:17,124
Speaker 3: much more explicit ev calculation, you know, I need to

769
00:40:17,164 --> 00:40:19,724
Speaker 3: pay for this flight that's more expensive because otherwise it'll

770
00:40:19,764 --> 00:40:22,684
Speaker 3: fuck up my calendar for the next two days. Right.

771
00:40:23,004 --> 00:40:24,804
Speaker 3: You know, sometimes people that want to take either the

772
00:40:24,844 --> 00:40:28,204
Speaker 3: early morning flight or the or the or the PM

773
00:40:28,244 --> 00:40:30,284
Speaker 3: flight back in California, for example, it's like, well, you

774
00:40:30,324 --> 00:40:32,884
Speaker 3: know what, if I wake up for the six am flight,

775
00:40:32,884 --> 00:40:34,964
Speaker 3: it's going to fuck up my sleep schedule. Right if

776
00:40:35,004 --> 00:40:36,364
Speaker 3: I take the PM flight, it's going to fuck up

777
00:40:36,364 --> 00:40:37,844
Speaker 3: the next day. So I want to pay this extra

778
00:40:37,884 --> 00:40:40,204
Speaker 3: three hundred and five hundred bucks because like that's definitely

779
00:40:40,244 --> 00:40:44,124
Speaker 3: worth expditional hours of productivity. So like, don't be don't

780
00:40:44,124 --> 00:40:46,684
Speaker 3: be a cheap skate when you are and where of

781
00:40:46,684 --> 00:40:51,724
Speaker 3: these kind of narrowly solvable problems, you know, when when

782
00:40:51,764 --> 00:40:54,764
Speaker 3: there's a direct trade off from from losing productive time.

783
00:40:56,164 --> 00:40:57,884
Speaker 2: I think about it the exact same way. And I

784
00:40:57,924 --> 00:41:01,684
Speaker 2: have absolutely taken the most expensive flight because it is

785
00:41:02,124 --> 00:41:03,724
Speaker 2: the one that's going to actually put me in the

786
00:41:03,724 --> 00:41:05,484
Speaker 2: best frame of mind to do what I need to do.

787
00:41:06,244 --> 00:41:08,244
Speaker 3: So there's at least it's the most expensive too. I mean,

788
00:41:08,284 --> 00:41:12,364
Speaker 3: they know what they know what they're doing, is the Yeah.

789
00:41:11,404 --> 00:41:13,484
Speaker 2: The reason it's the most expensive is because it's the

790
00:41:13,564 --> 00:41:16,444
Speaker 2: most gonvenient flight. But yeah, I think I think that

791
00:41:16,484 --> 00:41:18,844
Speaker 2: those types of things are very important because at the

792
00:41:18,924 --> 00:41:20,844
Speaker 2: end of the day, don't be a cheap skate about

793
00:41:20,884 --> 00:41:21,324
Speaker 2: your time.

794
00:41:21,684 --> 00:41:22,364
Speaker 1: Is actually a.

795
00:41:22,404 --> 00:41:25,164
Speaker 2: Very good way to end this, right, don't be nitty

796
00:41:25,164 --> 00:41:27,724
Speaker 2: about that, because as we know, Nate, you do not

797
00:41:27,964 --> 00:41:28,524
Speaker 2: like knits.

798
00:41:30,044 --> 00:41:32,364
Speaker 3: No, and it often comes from a feeling of guilt.

799
00:41:32,844 --> 00:41:35,804
Speaker 3: I think right that, like, yeah, if you are successful,

800
00:41:37,484 --> 00:41:39,644
Speaker 3: but you're not really you know, you're not really helping

801
00:41:39,644 --> 00:41:43,244
Speaker 3: anybody by just you know, laterally less productive than you

802
00:41:43,284 --> 00:41:43,684
Speaker 3: could be.

803
00:41:44,564 --> 00:41:47,964
Speaker 2: Exactly exactly, So don't do that. And I think all

804
00:41:47,964 --> 00:41:51,044
Speaker 2: these calculations are different for everyone, but do think about it,

805
00:41:51,124 --> 00:41:53,724
Speaker 2: because I think this is something that's important to think

806
00:41:53,724 --> 00:41:56,324
Speaker 2: about and important to realize that, you know what, some

807
00:41:56,364 --> 00:41:59,284
Speaker 2: cliches are there for a reason. Time actually is money.

808
00:41:59,484 --> 00:42:02,244
Speaker 2: Figure out how you value your time. I'm not going

809
00:42:02,284 --> 00:42:03,764
Speaker 2: to oh, am I gonna do it? Nate, Am I

810
00:42:03,764 --> 00:42:07,164
Speaker 2: gonna end with how are you going to live your

811
00:42:07,644 --> 00:42:09,004
Speaker 2: one wild and beautiful?

812
00:42:12,884 --> 00:42:13,244
Speaker 1: No?

813
00:42:13,244 --> 00:42:16,044
Speaker 2: No, we're not gonna We're not gonna do the cliche

814
00:42:16,164 --> 00:42:17,484
Speaker 2: poetry ending to this.

815
00:42:18,324 --> 00:42:20,084
Speaker 1: We'll just say see.

816
00:42:19,924 --> 00:42:22,644
Speaker 2: You next week, and we hope that you use your

817
00:42:22,684 --> 00:42:27,404
Speaker 2: time productively and start off by listening to our Pushkin Plus.

818
00:42:28,044 --> 00:42:30,844
Speaker 3: That is the actually the best pop please of your time?

819
00:42:31,404 --> 00:42:32,404
Speaker 1: Yes, definitely.

820
00:42:39,524 --> 00:42:42,284
Speaker 3: That's all for this week. Premium subscribers can seeker bund

821
00:42:42,324 --> 00:42:44,724
Speaker 3: for our answer to one of your burning listener questions

822
00:42:44,764 --> 00:42:47,804
Speaker 3: after the credits. This week, it's from Easton Lewis on

823
00:42:47,844 --> 00:42:51,524
Speaker 3: how to manage funny incentives in prediction markets. If you're

824
00:42:51,564 --> 00:42:53,924
Speaker 3: not subtrapping yet, consider signing up for just six twenty

825
00:42:54,004 --> 00:42:57,124
Speaker 3: nine a month. You get access to premium content from

826
00:42:57,204 --> 00:43:00,724
Speaker 3: us every week and add free listening across Pushkin's entire

827
00:43:00,764 --> 00:43:04,164
Speaker 3: network of shows. Risky Business is hosted by me Nate.

828
00:43:04,124 --> 00:43:07,484
Speaker 2: Silver and me Maria Kanakova. The show is a co

829
00:43:07,564 --> 00:43:11,244
Speaker 2: production of Pushkin Industries and iHeart Media. This episode was

830
00:43:11,284 --> 00:43:15,324
Speaker 2: produced by Isabelle Carter. Our associate producer is Gabriel Hunter Chang.

831
00:43:15,884 --> 00:43:19,284
Speaker 2: Sally Helm is our editor, and our executive producer is

832
00:43:19,364 --> 00:43:21,884
Speaker 2: Jacob Goldstein. Mixing by Sarah Bruguer.

833
00:43:22,364 --> 00:43:24,564
Speaker 3: If you like the show, please rate and review us

834
00:43:24,564 --> 00:43:34,324
Speaker 3: so other people can find us too,