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Speaker 1: Pushkin. Welcome back to Risky Business, a show about making

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Speaker 1: better decisions. I'm Maria Kanigogo.

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Speaker 2: And I'm Nate Silver.

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Speaker 1: So today on the show, Nate, we're gonna first revisit

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Speaker 1: our predictions about the conclave. They were wrong, as was

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Speaker 1: basically everyone else's, and then talk a little Coker and

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Speaker 1: my recent trip to Monte Carlo.

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Speaker 2: And I'll try to slip in a few New York

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Speaker 2: Knicks references you may notice on the show. But we'll

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Speaker 2: also talk about the rampant use of chat GPT to

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Speaker 2: cheat on college campuses, inspired by a recent article in

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Speaker 2: New York Magazine.

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Speaker 1: So with that, Nate, let's dive in. I'm so sorry

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Speaker 1: that Pizza Bala did not end up becoming pope. That

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Speaker 1: would have been fun. However, pizza is definitely on everyone's

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Speaker 1: minds because the pope is from Chicago, and we all

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Speaker 1: know that Chicago is famous for its deep dish pizza.

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Speaker 1: In fact, Nate, the last time we had a meal

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Speaker 1: together was over Chicago style people.

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Speaker 2: You know, the last time we talked about Chicago, you

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Speaker 2: actually encouraged me to get peaquads pizza, which I know

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Speaker 2: and love and like, I had the whole it was

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Speaker 2: a lunch sized pizza. Right. I have not had that

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Speaker 2: accumulation of like that much dairy, I don't think in years.

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Speaker 2: Pick Quads is amazing. You should visit it.

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Speaker 1: This podcast is sponsored by Peaquad's Pizza use our affiliate length.

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Speaker 2: I'm just kidding, No, I found this very interesting because, like,

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Speaker 2: I lived in Chicago. The guy's a Chicago White Sox fan.

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Speaker 2: He's a Villanova a basketball fan, and attended Villanova, has

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Speaker 2: a mathematics degree. So it's like, you know, neither of

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Speaker 2: us are Catholic. We're not going to shock you with that,

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Speaker 2: I don't think, but like, it's very strange to have

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Speaker 2: a pope that's kind of like memeable and relatable to Americans.

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Speaker 2: And this was not well predicted at prediction markets. He

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Speaker 2: had had around a one percent chance of becoming the pope.

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Speaker 2: If you look at various shortlists and long lists published

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Speaker 2: by various userganizations. You know, the New York Times mentions

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Speaker 2: him in like the twentieth paragraph. The Washington Post doesn't

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Speaker 2: mention him at all, for example, and yet he won,

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Speaker 2: I believe after just the second day of the conclave.

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Speaker 2: Do you know how many ballots there.

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Speaker 1: Were we don't, but it was just over twenty four hours,

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Speaker 1: so it could not have been more than four ballots.

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Speaker 1: That would have been I think the maximum given the

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Speaker 1: amount of time, if I remember correctly about how the

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Speaker 1: ballot process works.

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Speaker 2: So once this decision came quickly, markets assumed that one

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Speaker 2: of the front runners is going to win, right, which

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Speaker 2: is a dynamic we had talked about on the program beforehand,

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Speaker 2: and that was you know, maybe he was a front runner,

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Speaker 2: but nobody knew it. So I think it was a

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Speaker 2: pretty big failure of both the conventional wisdom and crediction

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Speaker 2: markets right where. I guess the conclave is pretty good

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Speaker 2: at keeping secrets, maybe more than like, you know, than

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Speaker 2: the United States Congresses for example. There weren't a lot

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Speaker 2: of leaks, and I think it reflects the kind of

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Speaker 2: changing global climate toward the United States, right. You know.

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Speaker 2: One of the few outlets that did it in an

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Speaker 2: article about him was Axios, and they're like, well, this

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Speaker 2: would never happen because the Catholic Church doesn't want to

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Speaker 2: give the US government more influence, or the United States

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Speaker 2: and not the government, I guess, more influence. It's like, well,

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Speaker 2: what do they want to influence the United States, right,

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Speaker 2: and have some counterweight to President Trump. You know what's

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Speaker 2: a good counterweight, you know, probably not the Speaker of

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Speaker 2: the House. Maybe the pope is like the only person

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Speaker 2: who can be like on a stage as a counterweight.

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Speaker 2: And you know, Greemost had had an active Twitter account too, right,

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Speaker 2: He had criticized mostly through retweets, not things he wrote himself,

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Speaker 2: criticized JD. Vance criticized the deportation of Kilmar Abrego Garcia

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Speaker 2: Marilyn Man who was accidentally sent to an l Salador

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Speaker 2: in prison. And so it's making a.

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Speaker 1: Statement, Yeah, And I think that I think that we

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Speaker 1: see that psychologically something happened here and also something that

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Speaker 1: you and I have talked about night that you write

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Speaker 1: about in terms of kind of how betting and prediction

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Speaker 1: markets work. So the first part of the psychology part,

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Speaker 1: I think people had kind of bad priors, right, and

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Speaker 1: let kind of their biases in an historical precedent influence

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Speaker 1: this a little bit too much, saying oh, you know, well,

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Speaker 1: an American could never be pope and you can't have

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Speaker 1: that sort of blanket statement rights, that's a bias where

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Speaker 1: you are you're actually kind of anchoring yourself to a

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Speaker 1: really incorrect starting point, which gets into my second point

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Speaker 1: that you've written about, which is that this is not

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Speaker 1: an event where we have tons of data and statistics. Right,

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Speaker 1: this isn't the super Bowl that happens every single year.

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Speaker 1: Like the last time that we had a papal election

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Speaker 1: was what twelve years ago? And you know, there have

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Speaker 1: been decades where there haven't where there hasn't been one,

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Speaker 1: and the world changes and different things change, and people

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Speaker 1: don't know much about what happens inside the Vatican and

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Speaker 1: all of that, and yet we think, right, we're a

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Speaker 1: little bit overconfident in thinking that we know more than

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Speaker 1: we do and that we have more data than we do.

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Speaker 1: It's always incredibly incredibly risky to make predictions based on incomplete,

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Speaker 1: faulty data.

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Speaker 2: Yeah, and look, prediction markets can accentuate that when people

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Speaker 2: are like, well they're pretty smart, someone must do something right,

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Speaker 2: and they are smart in many circumstances. Right, In general,

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Speaker 2: there is in markets various kinds of a long shot bias,

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Speaker 2: meaning people are actually a little bit under confident relative

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Speaker 2: to the favorite usually prevailing. But if you have no

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Speaker 2: information to go off, right, you know, there are what

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Speaker 2: a two hundred and fifty one cardinals in the College

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Speaker 2: of Cardinals. Right. You know, technically speaking, any baptized Catholic

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Speaker 2: male is eligible to become pope. Right. I'm not saying

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Speaker 2: you just want to spin a wheel one in two

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Speaker 2: hundred and fifty one or whatever. But but you know,

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Speaker 2: especially after the white smoke came out and people like, oh,

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Speaker 2: now we know for sure, right, this is a case

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Speaker 2: where the conditions were not in place for prediction markets

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Speaker 2: to be particularly wise.

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Speaker 1: Yeah, and you actually you write on the edge a

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Speaker 1: little bit about how prediction markets and sports betting falters

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Speaker 1: and certain events where there's dumb money as well, right,

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Speaker 1: where there's a proliferation of people who don't know as

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Speaker 1: much about it that some events are much easier to

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Speaker 1: bet on than others, just depending on who the betters are.

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Speaker 1: And I think from a psychological standpoint, you also get

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Speaker 1: into these groups think echo chambers, where you start amplifying

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Speaker 1: things that are already kind of front runners, et cetera,

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Speaker 1: et cetera. Not for any good reason, right, but oh well,

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Speaker 1: because he said so, I guess I think so. And

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Speaker 1: then on and on it goes. It's like those psych

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Speaker 1: studies right where there's a number of statistic that's been

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Speaker 1: cited thousands of times, and then you actually try to

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Speaker 1: unravel it and figure out, way, where did we get this?

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Speaker 1: And you find the study from nineteen sixty four that

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Speaker 1: was based on twelve people, and that's where the number

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Speaker 1: came from, and you're like, whoa, whoa, whoa. This number

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Speaker 1: that has now become gospel is actually incredibly suspect. That

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Speaker 1: has happened to me so many times where I've actually

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Speaker 1: tried to kind of retrace the steps of how it happens.

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Speaker 1: But especially with social media and kind of the way

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Speaker 1: information spreads these days, it's very easy to create those effects.

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Speaker 2: And if you actually make sports bets, especially I'm betting

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Speaker 2: the NBA playoffs a little bit go Nix, by the way,

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Speaker 2: you'll sometimes see lines where you're like, this doesn't make

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Speaker 2: any sense, right, So somebody must know something, or the

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Speaker 2: market must be accounting for some psychological factor or some

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Speaker 2: injury that like I'm not accounting for, right, And if

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Speaker 2: that were always true, then you could say, Okay, even

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Speaker 2: though my model says that Nick's have a forty percent chance,

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Speaker 2: the market applug, you just have a twenty percent chance.

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Speaker 2: So maybe the twenty percent actually of the good bet here,

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Speaker 2: and if you're making our sports bets, you learn that

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Speaker 2: it's not predictable when the market knows something and when

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Speaker 2: it doesn't. Obviously, markets are tough to beat in general,

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Speaker 2: but sometimes it is full of shit, right and many

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Speaker 2: times it's not, And you're the one feeling embarrassed after all.

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Speaker 2: Instead you say, boy, you know Vegas is so smart,

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Speaker 2: but like it's not always smart? Right if it was

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Speaker 2: always smart? Yeah, piggyback off it and you kind of can't.

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Speaker 1: Dude, I have a question for you, what you know

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Speaker 1: if if you were to say, okay, there's a skill

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Speaker 1: set and maybe the answer is no to figuring out

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Speaker 1: other than what we've already talked about, right events that

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Speaker 1: happen frequently, versus not to figuring out, Okay, these are

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Speaker 1: things that prediction markets are probably smarter on and these

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Speaker 1: are where they're not right. Is there is there a

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Speaker 1: way that you think about that, like how to figure

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Speaker 1: out you know what, I shouldn't be listening to the

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Speaker 1: experts in this particular case, I shouldn't be listening to

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Speaker 1: the markets particular case, because I think that's actually a

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Speaker 1: really interesting question.

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Speaker 2: I mean, you've touched on some of this, right, Like,

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Speaker 2: you know, question one is how much domain knowledge does

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Speaker 2: the average trader have? I mean, the average person's betting

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Speaker 2: on the NBA of the NFL probably knows more about

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Speaker 2: the NBA and the NFL, And the average person betting

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Speaker 2: at polymarket on the identity of the pope knows about

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Speaker 2: the Catholic church. Frankly, I don't think the kind of

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Speaker 2: church following personality type overlaps much with the you know,

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Speaker 2: crypto adjacent prediction market startup betting type person Right. Next

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Speaker 2: is is there are there institutional investors professional class of

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Speaker 2: investors who are who are sucking up the week money

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Speaker 2: to make the market balance?

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Speaker 1: Right?

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Speaker 2: Or you know, so for example for elections, investment banks

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Speaker 2: and hedge funds and rich gamblers like all our betting

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Speaker 2: serious money, there's a professional class. Certainly that's true for

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Speaker 2: the Super Bowl or anything like that. Right. Again, the

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Speaker 2: pope doesn't probably have action geopolitical consequences in the same way,

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Speaker 2: so he probably don't have that. Right. Is it a

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Speaker 2: repeated thing where people can calibrate their models? Is it

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Speaker 2: even mathematically modelable by anything beyond like very naive methods?

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Speaker 1: Right?

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Speaker 2: And I mean, you know, models are hard for a

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Speaker 2: lot of things, but that puts like some bumpers on

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Speaker 2: how far unmored a prediction can get right. And so

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Speaker 2: all these boxes are not checked for papal predictions, whereas

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Speaker 2: they might be forbidding in the playoffs in the NBA.

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Speaker 1: Yeah, that makes a lot of sense. And by the way,

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Speaker 1: I saw someone was writing about kind of did anyone

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Speaker 1: predict this? And there was one publication that actually had

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Speaker 1: Robert Privost as one of the top contenders, and it

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Speaker 1: was a Catholic like it was a niche Catholic publication,

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Speaker 1: I don't remember which one it was. Didn't have them

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Speaker 1: as the front runner, but it at least mentioned his name.

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Speaker 1: You and I, by the way, didn't even mention his name. Right,

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Speaker 1: he wasn't on our radar because he wasn't on the

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Speaker 1: radar of any of the sources that we actually well.

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Speaker 2: If anything, you think there might be a bias for

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Speaker 2: we're saying, oh, there's just cogo guy might become pope, right,

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Speaker 2: you think there might be more coverage and moves might be,

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Speaker 2: Oh you got to short him, They're gonna, you know,

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Speaker 2: not pick an American guy. But I he just kind

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Speaker 2: of didn't really enter the conversation very much, except you know,

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Speaker 2: I did be done a see article, you know for

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Speaker 2: like a Catholic source. They kind of said, oh, it's

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Speaker 2: interesting that people are betting on the pope. We're not

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Speaker 2: sure how we feel about that as Catholics, but they're

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Speaker 2: way over confident because nobody knows anything right and that

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Speaker 2: proved to be prescient.

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Speaker 1: Yeah, absolutely, all right, so so let's let's see how

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Speaker 1: he ends up doing and let's see how how this

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Speaker 1: all ends up going.

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Speaker 2: So America is winning, Maria. Uh the Knicks are winning.

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Speaker 1: Which makes it I'm doubly happy because as an ex Bostonian,

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Speaker 1: I hate Boston sports fans. Really, they just suck, and

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Speaker 1: so I'm i anti sweat the Celtics, and as a

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Speaker 1: New Yorker, I'm pro next. So I'm just I'm deliriously happy.

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Speaker 1: I'm actually interested in the outcome of these games today.

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Speaker 2: But you're winning too, So tell me about, uh our

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Speaker 2: telling me and the audience about this win you had

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Speaker 2: in Monte Carlo.

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Speaker 1: Yeah, So I just came back from EPT Monte Carlo,

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Speaker 1: which is the Poker Stars signature stop on the European

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Speaker 1: Poker Tour. Beautiful venuinate. I hope you come next year.

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Speaker 1: But I had not been having a good trip at all.

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Speaker 1: I've never cashed in the main event there. I still

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Speaker 1: did not cash in the main event, ended up playing

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Speaker 1: a twenty five K, did not cash in that. When

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Speaker 1: you don't cash those big events, it doesn't feel good,

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Speaker 1: and just was running horribly right. I kept getting two

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Speaker 1: out at three out and four outed. For our non

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Speaker 1: poker playing fans, that means, you know, improbable combinations of

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Speaker 1: cards kept getting there against me, and so I was

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Speaker 1: just very discouraged. And I ended up winning the final event,

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Speaker 1: which was a really really nice way to end the trip.

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Speaker 1: And the final that was actually a turbo structure, which

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Speaker 1: is very different from kind of your standard tournament. It

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Speaker 1: means that the blind levels aren't increasing quite quickly, and

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Speaker 1: so your strategy actually has to change a little bit, because, yes,

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Speaker 1: you might start with two hundred big blinds, and whereas

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Speaker 1: you know, in a normal tournament you might have that

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Speaker 1: for forty minutes, half an hour, an hour, whatever it is.

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Speaker 1: Here like suddenly, if you don't do stuff in twenty minutes,

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Speaker 1: you look and you have thirty big blinds left, right,

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Speaker 1: Because the blind structure is moving so quickly. It's such

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Speaker 1: a dynamic tournament, and so in situations like this, you

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Speaker 1: need to be first of all, more aggressive, right. You

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Speaker 1: need to play. You can't just sit around waiting for

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Speaker 1: good hands, because otherwise you will blind out. This is

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Speaker 1: one of those cases where doing nothing is doing something,

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Speaker 1: and it's not a good thing, and you have to

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Speaker 1: actually be a little bit different with the hand combinations

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Speaker 1: that you choose to play because very quickly, this is

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Speaker 1: not deep stacked poker, this is short stacked poker. So

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Speaker 1: the value of hands changes. So you need to play

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Speaker 1: high card hands much more, low suited connectors much less,

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Speaker 1: because you'll get into situations where people are going to

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Speaker 1: get very short, especially people who didn't play correctly right

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Speaker 1: and who now find themselves with very few chips, and

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Speaker 1: they're going to shove on you, which means they're going

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Speaker 1: to put all their chips in the middle. And you

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Speaker 1: have to know that in advance and know how you're

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Speaker 1: going to respond and be in a situation where you

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Speaker 1: can have a hand that can call those shoves, because

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Speaker 1: otherwise you're also going to bleed chips right if you

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Speaker 1: open too much and then keep folding when people are

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Speaker 1: aggressive against you, and so it's a slightly different mindset,

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Speaker 1: and it does require I think a lot of preparation

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Speaker 1: ahead of time because you don't have much time to think.

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Speaker 1: You just need to know your range as well. You

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Speaker 1: need to know your cards well, you need to know

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Speaker 1: your response as well. We had a ten second shot

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Speaker 1: clock in this tournament, so you had ten seconds to

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Speaker 1: make every single decision, no matter what street you were on.

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Speaker 1: And we had a few time banks, and each of

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Speaker 1: those time banks and it was ten seconds. So it's

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Speaker 1: actually kind of beautiful. It's a very it's fun because

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Speaker 1: it's so dynamic and so much happens, but there's also

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Speaker 1: an element of luck when you get into a fast

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Speaker 1: structure like that.

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Speaker 2: This is a one day tournament or yes, okay, yeah, Look.

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Speaker 2: The other thing that's tricky about these events I want

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Speaker 2: to ask you about is like, Okay, typically if you

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Speaker 2: have a big tournament series, you're toward the end of

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Speaker 2: the series and you have these turbos for people that

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Speaker 2: you know have busted out of the big events they're

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Speaker 2: hoping to play. There's also typically a lot of tilt, right,

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Speaker 2: people are trying to place very high to make up

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Speaker 2: for their entry fees. Right, we're getting the plane and

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Speaker 2: go home. So how do you balance that? I mean, again,

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Speaker 2: I'm not saying you have tilt. You can tell us

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Speaker 2: about that if you do right. I'm saying the fact

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Speaker 2: that like people are maybe calling down lighter and bluffing

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Speaker 2: a little bit more. At the same time, with a

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Speaker 2: turbo structure, you do need to widen your rain, which

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Speaker 2: is quite a bit, right, So how do you how

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Speaker 2: did you manage that?

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Speaker 1: Yeah, so you have to widen your ranges, but also

305
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Speaker 1: widen them correctly, so I you know, raggedy aces go

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Speaker 1: up in value, et cetera, so you need to kind

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Speaker 1: of know also what hands people will be undervaluing. So

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Speaker 1: I got quite lucky early on where I ended up.

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Speaker 1: Someone opened and I called a pocket pair. I call it,

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Speaker 1: you know, it was a pair of deuces, a tiny

311
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Speaker 1: pocket paar and someone else called and the flop came

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Speaker 1: with a deuce in it, which means that I had

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Speaker 1: flopped a set. But there was also an ace, and

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Speaker 1: there was one guy who was clearly very tilted. Because

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Speaker 1: this for older French gentleman who just wanted chips right,

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Speaker 1: he clearly just was frustrated. This was very early on

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Speaker 1: in the tournament, so we still had a lot of

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Speaker 1: chips and no one had busted out yet, right, like

319
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Speaker 1: this is how early we are. I think we're level one,

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Speaker 1: maybe level two. And you could tell that like he

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Speaker 1: just like he had been playing every hand, like he

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Speaker 1: just really wanted chips, and so he bet, I raised,

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Speaker 1: he called, and anyway, he ended up losing right and

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Speaker 1: busting and was the first player to bust out of

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Speaker 1: the tournament to me. And he had like I don't

326
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Speaker 1: even remember, it was like ace three off suit, right,

327
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Speaker 1: he didn't even have a good ace. It was a

328
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Speaker 1: shitty ace, but he just didn't believe me, and I

329
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Speaker 1: think he was tired of people picking on him. And

330
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Speaker 1: he was definitely tilting. And I've played with him before,

331
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Speaker 1: like he's not that bad of a player, but it

332
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Speaker 1: was just an awful play and he just gave me

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Speaker 1: all his chips, which was a great start obviously to

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Speaker 1: the to the tournament. But I think that you need

335
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Speaker 1: to look for spots like that and be willing to

336
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Speaker 1: kind of take full advantage of them. So like, for instance,

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Speaker 1: some people would say, oh, you know, don't get greedy

338
00:18:00,764 --> 00:18:02,724
Speaker 1: on the river, don't go all in because he's not

339
00:18:02,764 --> 00:18:05,564
Speaker 1: gonna call I was like, no, actually he will. You know,

340
00:18:06,204 --> 00:18:10,924
Speaker 1: do get greedy because in those in those spots, you're

341
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Speaker 1: going to get lucky against people who are just done

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Speaker 1: right and they don't want you to bully them. And

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Speaker 1: so especially because I'm female, that dynamic is very strong.

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Speaker 1: People don't want me to bully them.

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Speaker 2: Yeah. Look, and to the older frenchmen out there, I'd say,

346
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Speaker 2: you know, we understand that you're not always going to

347
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Speaker 2: play your A game and when you're tired in a

348
00:18:32,564 --> 00:18:35,204
Speaker 2: long series, even the B game can be asking a

349
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Speaker 2: lot avoiding the f game right where you you know, look,

350
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Speaker 2: I'll be honest, right, you know, I think I know

351
00:18:41,284 --> 00:18:42,764
Speaker 2: my range is pretty well in a lot of spots, and

352
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Speaker 2: I'll know when I can like loosen up just slightly,

353
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Speaker 2: you know, be a little bit more aggressive. You can

354
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Speaker 2: bluff sometimes, but like the multi street desperate call downs

355
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Speaker 2: are like the most easy way to like literally burn money.

356
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Speaker 1: And you know, by that stage in the in the

357
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Speaker 1: tournament series, when it is kind of one of the

358
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Speaker 1: last events this happened to be the last event, but

359
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Speaker 1: when it is kind of one of the last events,

360
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Speaker 1: people are tired and a lot of people are playing

361
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Speaker 1: their C game their D game, and if you're one

362
00:19:12,564 --> 00:19:15,044
Speaker 1: of the people who's not and who can actually take

363
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Speaker 1: advantage of that, I think that can be a huge

364
00:19:17,204 --> 00:19:20,044
Speaker 1: advantage if you're willing to be aggressive in the right

365
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Speaker 1: spots and also don't have ego and willing to fold

366
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Speaker 1: right in the right spots. So like be willing. I

367
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Speaker 1: did this as well to kind of throw your cards

368
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Speaker 1: away in a heartbeat. So I had a few very

369
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Speaker 1: successful bluffs that got through, and then I got very

370
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Speaker 1: lucky at the final table. When we got to the

371
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Speaker 1: final table, I had a good amount of chips, but

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Speaker 1: the chip leader, so the person with the most chips

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Speaker 1: was to my immediate left, and we got into a

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Speaker 1: big hand. So this was it's not good ICM. So

375
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Speaker 1: ICM is we've talked about this on the show. It's

376
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Speaker 1: the independent chip model. So basically, you know when they're

377
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Speaker 1: big pay jumps and when you're down to the final table,

378
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Speaker 1: you don't really want to tangle with the chip leader

379
00:20:03,124 --> 00:20:05,044
Speaker 1: when there are lots of people who are shorter than you,

380
00:20:05,084 --> 00:20:09,124
Speaker 1: because you could be committing ICM suicide. But in this

381
00:20:09,404 --> 00:20:12,924
Speaker 1: particular case, someone had opened, someone else had flatted, and

382
00:20:13,044 --> 00:20:16,164
Speaker 1: I had pocket jacks and like thirty big blinds something

383
00:20:16,204 --> 00:20:18,844
Speaker 1: like that, and so I jammed right because there was

384
00:20:18,924 --> 00:20:21,924
Speaker 1: dead money in the pot and I had you know,

385
00:20:22,204 --> 00:20:25,004
Speaker 1: I had a very strong hand, and I didn't want

386
00:20:25,044 --> 00:20:27,444
Speaker 1: that many people in the in the pot because pocket

387
00:20:27,564 --> 00:20:30,124
Speaker 1: jacks are a strong hand. But you don't want it

388
00:20:30,284 --> 00:20:33,604
Speaker 1: five way pot with pocket jacks because you know, Ace

389
00:20:33,724 --> 00:20:35,964
Speaker 1: King queen. There are lots of things that can happen.

390
00:20:36,524 --> 00:20:40,084
Speaker 1: And then the chip leader rejammed over me and I

391
00:20:40,124 --> 00:20:43,044
Speaker 1: was like, oh no, right, that's the one person that

392
00:20:43,084 --> 00:20:46,684
Speaker 1: you want to fold, and he had Ace King and

393
00:20:46,724 --> 00:20:49,444
Speaker 1: I ended up holding and winning that race, and so

394
00:20:49,604 --> 00:20:51,884
Speaker 1: he was still in, but that put me into the

395
00:20:51,964 --> 00:20:55,644
Speaker 1: chip lead and that's huge, right that hand.

396
00:20:55,444 --> 00:20:57,324
Speaker 2: You're praying for the ace King there. You're not going

397
00:20:57,404 --> 00:20:59,844
Speaker 2: to see pocket tens. I don't think or anything anything.

398
00:20:59,884 --> 00:21:02,124
Speaker 1: No, no, I'm praying for the ace King once he

399
00:21:02,404 --> 00:21:04,844
Speaker 1: once he went all in, I was like, oh no,

400
00:21:05,244 --> 00:21:07,804
Speaker 1: I am going to be out and whatever it is,

401
00:21:07,844 --> 00:21:13,324
Speaker 1: you know, eighth place and I that would have been horrible,

402
00:21:13,404 --> 00:21:16,444
Speaker 1: but yeah, the Ace King is the best case scenario.

403
00:21:16,964 --> 00:21:21,284
Speaker 1: And luckily my handheld. So I think that that's those

404
00:21:21,324 --> 00:21:23,684
Speaker 1: spots like you have to get lucky right, and I

405
00:21:23,804 --> 00:21:25,844
Speaker 1: was technically a little bit ahead. But it's really a

406
00:21:25,884 --> 00:21:28,724
Speaker 1: flip when you have a pocket pair against ace King.

407
00:21:29,484 --> 00:21:30,404
Speaker 2: So how much did you win?

408
00:21:31,364 --> 00:21:33,084
Speaker 1: So I didn't you know, it wasn't it. It wasn't

409
00:21:33,084 --> 00:21:37,324
Speaker 1: a huge win. It was around twenty thousand, so not

410
00:21:37,444 --> 00:21:39,884
Speaker 1: definitely not one of my you know, biggest scores, but

411
00:21:39,964 --> 00:21:41,404
Speaker 1: it was a small buy in and it was a

412
00:21:41,484 --> 00:21:46,124
Speaker 1: really nice way to uh to end the end the week. Well,

413
00:21:46,124 --> 00:21:50,404
Speaker 1: congratulations Maria, Thank you so much, Nate, And yeah, I

414
00:21:50,484 --> 00:21:53,644
Speaker 1: look forward to uh playing with you in the world

415
00:21:53,724 --> 00:21:55,644
Speaker 1: series that's coming up in just a few weeks.

416
00:21:55,804 --> 00:21:59,644
Speaker 2: It's shockingly soon. I mean I'm not playing until like

417
00:21:59,684 --> 00:22:01,244
Speaker 2: the second or third week of the series.

418
00:22:01,364 --> 00:22:03,404
Speaker 1: There am I Neither am I? But I hope that

419
00:22:03,444 --> 00:22:05,524
Speaker 1: I hope that we both win all of our flips,

420
00:22:05,804 --> 00:22:08,324
Speaker 1: or at least most of our flips, that we run

421
00:22:08,364 --> 00:22:12,444
Speaker 1: better than music a less. Yeah, let's take a quick

422
00:22:12,444 --> 00:22:15,244
Speaker 1: break and then let's talk a little bit about chat GPT.

423
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Speaker 2: Nate.

424
00:22:30,924 --> 00:22:34,444
Speaker 1: So, there was a big piece in New York magazine

425
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Speaker 1: last week about cheating on college campuses and chat GPT,

426
00:22:38,444 --> 00:22:41,364
Speaker 1: and I know that you are writing about this for

427
00:22:41,724 --> 00:22:45,204
Speaker 1: your Substack Silver bulletin. So do you want to just

428
00:22:46,044 --> 00:22:49,204
Speaker 1: set the scene a little bit and tell us kind

429
00:22:49,204 --> 00:22:50,804
Speaker 1: of about some of the concerns here.

430
00:22:52,244 --> 00:22:55,644
Speaker 2: Yeah. I mean, look, if you have any friends who

431
00:22:55,644 --> 00:22:57,924
Speaker 2: are college professors of any kind, they'll probably tell you

432
00:22:57,964 --> 00:23:01,644
Speaker 2: the same concerns, right, which is that, you know, a

433
00:23:01,764 --> 00:23:05,644
Speaker 2: lot of classes rely on a model where students have

434
00:23:06,084 --> 00:23:08,044
Speaker 2: homework they can do at home. And for a long time,

435
00:23:08,044 --> 00:23:09,964
Speaker 2: obviously you can, you know, you can go on the

436
00:23:09,964 --> 00:23:12,604
Speaker 2: internet and look up information that way. There have always

437
00:23:12,644 --> 00:23:17,044
Speaker 2: been services that would offer to do your homework for you.

438
00:23:17,124 --> 00:23:21,164
Speaker 2: Right there are you know, ancient and modern versions of

439
00:23:21,244 --> 00:23:24,404
Speaker 2: cliffs notes and things like that, if you uh, you know,

440
00:23:24,484 --> 00:23:26,644
Speaker 2: the line between working with a friend on a problem

441
00:23:26,804 --> 00:23:30,044
Speaker 2: set and copying your friend's answers has always been blurry,

442
00:23:30,084 --> 00:23:33,484
Speaker 2: I think, but like but now chat chipetem makes it

443
00:23:33,764 --> 00:23:40,484
Speaker 2: very very tempting to cheat, and especially for like written essays,

444
00:23:40,484 --> 00:23:44,164
Speaker 2: but also you know problem sets for economic classes and

445
00:23:44,204 --> 00:23:46,204
Speaker 2: things like that, and and so yeah, I tried to

446
00:23:46,244 --> 00:23:50,044
Speaker 2: actually I imagine that I had given myself an assignment.

447
00:23:50,404 --> 00:23:55,484
Speaker 2: You know, the philosopher Michelle Fuco. Of course, French guy

448
00:23:55,844 --> 00:24:00,204
Speaker 2: weird into s and m into lots of stuff ball

449
00:24:00,364 --> 00:24:03,644
Speaker 2: you know, but like very famous philosopher. My whole mo

450
00:24:03,884 --> 00:24:08,244
Speaker 2: in college was to always mention, always named up Fuco right,

451
00:24:08,244 --> 00:24:09,964
Speaker 2: And every time I named up put then I would

452
00:24:09,964 --> 00:24:12,164
Speaker 2: get at least an a minus on the paper. Right,

453
00:24:12,164 --> 00:24:15,484
Speaker 2: But like I gave myself an assignment to compare the

454
00:24:15,524 --> 00:24:19,164
Speaker 2: concept of the panopticon, which is this all seeing prison

455
00:24:19,204 --> 00:24:21,524
Speaker 2: where there's like a guard tower in the center. Right,

456
00:24:21,684 --> 00:24:24,324
Speaker 2: it was Bentham's idea who co wrote a lot about

457
00:24:24,364 --> 00:24:27,684
Speaker 2: this is a metaphor for modern surveillance states. And to say,

458
00:24:27,684 --> 00:24:30,724
Speaker 2: how does this apply to like modern day China? Right,

459
00:24:30,764 --> 00:24:34,524
Speaker 2: it seems like the kind of prompt that a student

460
00:24:34,644 --> 00:24:37,404
Speaker 2: might be asked in a class about China or a

461
00:24:37,444 --> 00:24:40,684
Speaker 2: class about pukou or whatever else. Right, And like, you know,

462
00:24:40,764 --> 00:24:44,884
Speaker 2: first of all, if you ask chat ChiPT to cheat

463
00:24:44,924 --> 00:24:47,644
Speaker 2: for you, it doesn't push back at all, Right, and

464
00:24:47,724 --> 00:24:49,564
Speaker 2: you can say things, can you like, please remove any

465
00:24:49,604 --> 00:24:52,484
Speaker 2: traces of this is GPT, you know, please make the

466
00:24:52,604 --> 00:24:55,124
Speaker 2: essay a little reugh around the margin, but have one

467
00:24:55,204 --> 00:24:56,644
Speaker 2: or two good points of insight.

468
00:24:56,724 --> 00:24:56,884
Speaker 1: Right.

469
00:24:57,004 --> 00:24:59,924
Speaker 2: At one point in the version I eventually ended up with, Right,

470
00:24:59,964 --> 00:25:02,124
Speaker 2: it's like, you know, my Chinese friend, so it made

471
00:25:02,244 --> 00:25:05,404
Speaker 2: up a fake Chinese friend to testify to a point

472
00:25:05,724 --> 00:25:10,364
Speaker 2: that it was making, and I have no idea da

473
00:25:10,804 --> 00:25:14,044
Speaker 2: quite how detectable this would be. But you know, but

474
00:25:14,084 --> 00:25:16,244
Speaker 2: the students can kind of take that as an intermediate

475
00:25:16,284 --> 00:25:19,084
Speaker 2: point and then remove further traces of it. But anyway,

476
00:25:19,124 --> 00:25:22,324
Speaker 2: it's it's very hard to have an assignment now that

477
00:25:22,404 --> 00:25:25,244
Speaker 2: you can confidently predict was not written by chat GPD,

478
00:25:25,364 --> 00:25:29,604
Speaker 2: any type of written homework assignment that's not kind of

479
00:25:29,644 --> 00:25:34,564
Speaker 2: done with active supervision, and the article is very gloomy.

480
00:25:34,644 --> 00:25:38,324
Speaker 2: A lot of students are pretty open about their cheating

481
00:25:38,324 --> 00:25:40,124
Speaker 2: and say, hey, this is great, right now, I can

482
00:25:40,164 --> 00:25:42,764
Speaker 2: save a lot of time. Right. A lot of professors

483
00:25:42,804 --> 00:25:45,804
Speaker 2: are very despairing of it. Right, you know, you were

484
00:25:45,804 --> 00:25:48,124
Speaker 2: in an era where because it's hard to prove, like

485
00:25:48,164 --> 00:25:52,204
Speaker 2: you might be ninety percent sure that a student cheated,

486
00:25:52,564 --> 00:25:55,204
Speaker 2: but ninety percent is probably not good enough to flunk

487
00:25:55,284 --> 00:25:58,404
Speaker 2: similar to kick them out of college or things like that.

488
00:25:58,484 --> 00:26:01,564
Speaker 2: But like I will say to me, it seems like

489
00:26:01,604 --> 00:26:04,724
Speaker 2: there are some methods that you could use to prevent this,

490
00:26:04,884 --> 00:26:07,004
Speaker 2: which require more work. So you know, you know, when

491
00:26:07,004 --> 00:26:09,004
Speaker 2: I went, I took my junior year abroad at one

492
00:26:09,124 --> 00:26:12,164
Speaker 2: school economics in the UKSES, and you just take one

493
00:26:12,204 --> 00:26:14,404
Speaker 2: big exam at the end of the year and that's

494
00:26:14,404 --> 00:26:16,604
Speaker 2: your whole grand and that's in person. Back then, we

495
00:26:16,724 --> 00:26:19,564
Speaker 2: use notebooks. I'm sure you can use you know, iPads

496
00:26:19,644 --> 00:26:22,564
Speaker 2: or something like that now, right, but that's quite hard

497
00:26:22,644 --> 00:26:24,324
Speaker 2: to cheat. If you want. Students have the internet. You

498
00:26:24,324 --> 00:26:25,764
Speaker 2: could say you can have the Internet, but we're monitoring

499
00:26:25,764 --> 00:26:28,564
Speaker 2: you're internet access, right and so, like if you use chatchipt,

500
00:26:28,764 --> 00:26:32,884
Speaker 2: we will know, right. Or you can say, okay, well

501
00:26:32,884 --> 00:26:35,324
Speaker 2: we're going to have you submit a paper and I'm

502
00:26:35,324 --> 00:26:39,284
Speaker 2: going to have a fifteen minute conversation with you about

503
00:26:39,284 --> 00:26:41,964
Speaker 2: the paper. I imagine it'd be hard to fake your

504
00:26:42,124 --> 00:26:44,804
Speaker 2: way through even like five or ten minutes if you

505
00:26:44,844 --> 00:26:46,844
Speaker 2: really didn't know the subject matter at all, if you're

506
00:26:46,844 --> 00:26:50,404
Speaker 2: being quizzed about your own paper, right and so, But

507
00:26:50,444 --> 00:26:52,204
Speaker 2: professors don't seem to want to do it in anyway.

508
00:26:52,204 --> 00:26:54,764
Speaker 2: What are your thoughts here, Maria, Yeah.

509
00:26:54,524 --> 00:26:57,164
Speaker 1: Well I have I have a number of thoughts. First

510
00:26:57,164 --> 00:26:59,804
Speaker 1: of all, I mean, obviously you know students have been

511
00:26:59,924 --> 00:27:03,204
Speaker 1: cheating for a long time, and that you were saying

512
00:27:03,284 --> 00:27:05,884
Speaker 1: ninety percent isn't enough. And I will actually go further

513
00:27:06,044 --> 00:27:09,004
Speaker 1: and say one hundred percent isn't enough to fail someone

514
00:27:09,164 --> 00:27:13,044
Speaker 1: off times. So when I was when I was teaching

515
00:27:13,844 --> 00:27:17,204
Speaker 1: back in my grad school days, I had a student

516
00:27:17,924 --> 00:27:22,524
Speaker 1: hand in a paper that just looked suspicious, and it

517
00:27:22,564 --> 00:27:25,284
Speaker 1: was a word document that was kind of scrolling down

518
00:27:25,324 --> 00:27:28,524
Speaker 1: and all of a sudden, my, you know, the cursor

519
00:27:28,644 --> 00:27:31,684
Speaker 1: changes to kind of a you know, the way that

520
00:27:31,684 --> 00:27:34,724
Speaker 1: the cursor changes when there's a hyperlink. And so he

521
00:27:34,844 --> 00:27:38,484
Speaker 1: had copied and pasted directly from Wikipedia, and he had

522
00:27:38,524 --> 00:27:42,484
Speaker 1: removed the visual hyperlink, but he hadn't actually removed the hyperlink,

523
00:27:42,644 --> 00:27:45,164
Speaker 1: so I could actually click on the text to get

524
00:27:45,204 --> 00:27:48,764
Speaker 1: to the Wikipedia article. And I was like, wow, right,

525
00:27:49,324 --> 00:27:52,484
Speaker 1: like that that is uh, that is like the people

526
00:27:52,524 --> 00:27:56,044
Speaker 1: who these days hand in essays that start with as

527
00:27:56,084 --> 00:28:01,404
Speaker 1: an ai I And I brought this, you know, to

528
00:28:01,484 --> 00:28:06,084
Speaker 1: the department and said, you know this, this kid cheated.

529
00:28:06,364 --> 00:28:08,004
Speaker 1: I want to fail him. And they didn't let me

530
00:28:08,364 --> 00:28:11,404
Speaker 1: because they said that, you know, there were parent issues

531
00:28:11,444 --> 00:28:13,124
Speaker 1: and all these things. And I was allowed to give

532
00:28:13,204 --> 00:28:15,084
Speaker 1: him a D minus, but I could not give him

533
00:28:15,084 --> 00:28:18,524
Speaker 1: an F because that's not how Columbia did things. And

534
00:28:18,604 --> 00:28:20,484
Speaker 1: it was very disparaiting to me. Right. It was one

535
00:28:20,484 --> 00:28:22,804
Speaker 1: of the things that one of the reasons there were

536
00:28:22,844 --> 00:28:24,764
Speaker 1: lots of reasons I didn't want to go into academia,

537
00:28:24,804 --> 00:28:26,764
Speaker 1: but I was like, fuck this, right, like, you need

538
00:28:26,804 --> 00:28:29,964
Speaker 1: to have consequences for cheating, so that it has happened

539
00:28:30,004 --> 00:28:33,244
Speaker 1: for a long time and it's obviously only getting worse.

540
00:28:33,484 --> 00:28:37,244
Speaker 1: But I completely agree with you, Nate, that you should

541
00:28:37,404 --> 00:28:41,644
Speaker 1: change in response to this, how you grade and how

542
00:28:41,684 --> 00:28:45,604
Speaker 1: you create assignments. When I went even kind of as

543
00:28:45,764 --> 00:28:49,924
Speaker 1: an undergrad, we had so many in class exams right

544
00:28:49,924 --> 00:28:52,844
Speaker 1: where you had to write essays in class. And then

545
00:28:52,844 --> 00:28:54,804
Speaker 1: when I was a grad student, we had oral exams

546
00:28:55,164 --> 00:28:58,364
Speaker 1: where you know, as part of your degree you have

547
00:28:58,404 --> 00:29:02,004
Speaker 1: to pass orals where you are interviews. It's very stressful

548
00:29:02,004 --> 00:29:04,324
Speaker 1: for a lot of people. Right. There are people who

549
00:29:04,404 --> 00:29:07,124
Speaker 1: ask you questions. When you defend your dissertation. You have

550
00:29:07,164 --> 00:29:11,204
Speaker 1: an entire committee, right who's pepper you with questions about

551
00:29:11,244 --> 00:29:13,964
Speaker 1: your work and about your research. And if you're not

552
00:29:14,044 --> 00:29:16,084
Speaker 1: the one who knows the data and who knows what

553
00:29:16,124 --> 00:29:18,484
Speaker 1: you did, then you're going to get screwed, right, You're

554
00:29:18,524 --> 00:29:20,684
Speaker 1: not going to pass. And people have failed, by the way,

555
00:29:20,764 --> 00:29:25,764
Speaker 1: different dissertation defenses. People have failed oral exams. People you know,

556
00:29:25,844 --> 00:29:28,604
Speaker 1: fail these types of assessments all the time, and so

557
00:29:28,684 --> 00:29:31,164
Speaker 1: I think what we need if we want to actually

558
00:29:31,524 --> 00:29:34,004
Speaker 1: first of all, like what's the point of higher education?

559
00:29:34,084 --> 00:29:37,204
Speaker 1: I would say, you know, to create critical thinkers and

560
00:29:37,244 --> 00:29:41,244
Speaker 1: people who actually are educated human beings and have well

561
00:29:41,324 --> 00:29:44,564
Speaker 1: rounded who know about you know, history and all of

562
00:29:44,604 --> 00:29:46,964
Speaker 1: these different things. How do you make sure that they're

563
00:29:47,004 --> 00:29:50,604
Speaker 1: actually learning what? You change the You change the way

564
00:29:50,644 --> 00:29:53,884
Speaker 1: that you that you have your class. You change the

565
00:29:53,924 --> 00:29:57,924
Speaker 1: incentives right so that they can't cheat their way through it,

566
00:29:58,084 --> 00:29:59,684
Speaker 1: because it's not going to go away. It's only going

567
00:29:59,764 --> 00:30:02,764
Speaker 1: to get worse. And so you can't just pretend that

568
00:30:02,844 --> 00:30:05,644
Speaker 1: it doesn't happen. And you can't rely on cheating detection

569
00:30:05,804 --> 00:30:08,644
Speaker 1: software because it doesn't matter anyway. Instead, you need to

570
00:30:08,724 --> 00:30:13,364
Speaker 1: kind of create an environment where your students learn and

571
00:30:13,404 --> 00:30:15,844
Speaker 1: I would say, you know, are motivated to learn, right,

572
00:30:16,004 --> 00:30:19,244
Speaker 1: So make it worth their while, like make them understand

573
00:30:19,284 --> 00:30:22,804
Speaker 1: why this is important. One of the students, Nay, in

574
00:30:22,844 --> 00:30:26,124
Speaker 1: that New York magpiece. He first he got into Harvard,

575
00:30:26,164 --> 00:30:28,884
Speaker 1: then he said they rescinded his admission and he ended

576
00:30:28,964 --> 00:30:33,044
Speaker 1: up transferring to Columbia and was kicked out within a

577
00:30:33,124 --> 00:30:36,684
Speaker 1: year because he cheated on everything and he openly admitted

578
00:30:36,724 --> 00:30:41,044
Speaker 1: it and created cheating software and said, well, I don't care, Like,

579
00:30:41,844 --> 00:30:43,924
Speaker 1: I don't care about actually any of this. The only

580
00:30:43,964 --> 00:30:45,364
Speaker 1: reason I want to go to a good school is

581
00:30:45,404 --> 00:30:47,364
Speaker 1: to meet my future spouse and co founder.

582
00:30:48,444 --> 00:30:52,164
Speaker 2: Yeah, look, I mean students learn from well, anyone learns from,

583
00:30:52,204 --> 00:30:54,724
Speaker 2: like to Terrence, right that if you do see a

584
00:30:54,764 --> 00:30:57,884
Speaker 2: student who was kicked out of college for cheating, then

585
00:30:58,084 --> 00:31:00,964
Speaker 2: as going to have a much bigger deterrent effect. Right,

586
00:31:01,004 --> 00:31:02,764
Speaker 2: But like, yeah, look, I mean I was going to say,

587
00:31:03,364 --> 00:31:06,124
Speaker 2: you know, is the purpose of higher education really learning?

588
00:31:06,164 --> 00:31:10,204
Speaker 2: Because you can obviously take a much more cynical approach, right,

589
00:31:10,204 --> 00:31:14,084
Speaker 2: which is that it's a factory to produce degrees and

590
00:31:14,164 --> 00:31:17,084
Speaker 2: to kind of, you know, make a lot of money

591
00:31:17,164 --> 00:31:20,684
Speaker 2: running these very expensive institutions that have now very large

592
00:31:20,804 --> 00:31:24,324
Speaker 2: non academic stabs. A lot of the time that the

593
00:31:24,404 --> 00:31:28,044
Speaker 2: kids are coddle, that there is a ton of great inflation,

594
00:31:29,324 --> 00:31:33,484
Speaker 2: that during the pandemic, that colleges were so concerned about

595
00:31:33,524 --> 00:31:37,244
Speaker 2: angering highly neurotic moms and dads and maybe professors to

596
00:31:37,244 --> 00:31:41,684
Speaker 2: some extent, right, and so they're totally undermining the educational experience, right,

597
00:31:41,724 --> 00:31:44,604
Speaker 2: But like, it doesn't stop the factory from like churning

598
00:31:44,604 --> 00:31:47,404
Speaker 2: out degrees, even if classes are easier and easier to gain,

599
00:31:47,524 --> 00:31:50,444
Speaker 2: and so, yeah, I don't know. I also think that

600
00:31:50,564 --> 00:31:53,844
Speaker 2: like you wind up with students in a kind of

601
00:31:54,044 --> 00:31:57,964
Speaker 2: prisoner's dilemma type situation where it's a really pretty rational

602
00:31:58,084 --> 00:32:02,084
Speaker 2: to cheat if everyone else is cheating and it can't

603
00:32:02,124 --> 00:32:04,444
Speaker 2: really be detected. And by the way, like I think that,

604
00:32:04,604 --> 00:32:07,084
Speaker 2: you know, when I write essays for Silver Bulletin, then

605
00:32:07,244 --> 00:32:11,844
Speaker 2: I ask chech GPT question, right, I will run my

606
00:32:11,924 --> 00:32:13,604
Speaker 2: copy through j just P and say do you correct

607
00:32:13,604 --> 00:32:18,284
Speaker 2: any typos or errors? Right? And things like that. Right,

608
00:32:18,764 --> 00:32:20,684
Speaker 2: Sometimes it all flag errors that are fake because I

609
00:32:20,684 --> 00:32:23,644
Speaker 2: can't believe how dumb things are. It's like we can't

610
00:32:23,644 --> 00:32:25,924
Speaker 2: really have one hundred and third percent tariff on China, right.

611
00:32:25,964 --> 00:32:29,244
Speaker 2: People might take that exaggeration seriously, Nate, So you have

612
00:32:29,284 --> 00:32:31,044
Speaker 2: to remove that from your estley. I'm like, no, things

613
00:32:31,044 --> 00:32:34,764
Speaker 2: are really that dumb. But like so and working with

614
00:32:34,884 --> 00:32:36,764
Speaker 2: AI is important. I mean, it's kind of intrude to

615
00:32:36,804 --> 00:32:40,324
Speaker 2: I mean, I'll stay that like interpersonal skills become more

616
00:32:41,044 --> 00:32:44,244
Speaker 2: important in a world where CHECHPD do is kind of

617
00:32:44,244 --> 00:32:48,804
Speaker 2: like the cognitive tasks easier. It's probably more about sales, right,

618
00:32:48,804 --> 00:32:50,524
Speaker 2: who are you going to hire to be the nice

619
00:32:50,564 --> 00:32:52,364
Speaker 2: person to brought you the services that you could probably

620
00:32:52,404 --> 00:32:55,604
Speaker 2: do yourself with chet GPT, your group assignments and things.

621
00:32:55,764 --> 00:32:59,364
Speaker 2: People feel charmed by humans. So but yeah, I think

622
00:32:59,364 --> 00:33:02,924
Speaker 2: colleges are on the way to being less relevant and

623
00:33:02,964 --> 00:33:06,404
Speaker 2: that they seem not to have particularly much urgency for

624
00:33:06,684 --> 00:33:09,724
Speaker 2: This is kind of lame. But like I said, if

625
00:33:09,804 --> 00:33:11,644
Speaker 2: you were a student, would you use chet cheapet if

626
00:33:11,684 --> 00:33:13,284
Speaker 2: you Let's say you let me set this up for you. Right,

627
00:33:13,844 --> 00:33:15,844
Speaker 2: Let's say you know for a fact that eighty percent

628
00:33:15,844 --> 00:33:19,484
Speaker 2: of the students in your class are using chat cheapt.

629
00:33:19,564 --> 00:33:21,724
Speaker 2: I'm trying to make a sympathetic set of facts. Right,

630
00:33:22,444 --> 00:33:26,444
Speaker 2: Let's say you don't think the class is well taught,

631
00:33:26,604 --> 00:33:30,124
Speaker 2: and so you don't think you're really getting that much

632
00:33:30,444 --> 00:33:32,404
Speaker 2: out of it. Let's even say that you kind of

633
00:33:32,444 --> 00:33:36,364
Speaker 2: done half the reading and so you're kind of using

634
00:33:36,444 --> 00:33:39,924
Speaker 2: cheapt chechpeeding way. It's like clearly over the line, but

635
00:33:39,964 --> 00:33:43,644
Speaker 2: you're adding some original inputs and insight yourself. But it

636
00:33:43,684 --> 00:33:46,764
Speaker 2: goes against the nominal recommendations of the professor. Would you

637
00:33:46,884 --> 00:33:49,044
Speaker 2: cheat in that circumstance or use chec ChiPT or not?

638
00:33:50,684 --> 00:33:53,604
Speaker 1: I would like to think no, because I never I

639
00:33:53,684 --> 00:33:57,404
Speaker 1: was someone who could have always took that pretty seriously.

640
00:33:58,044 --> 00:34:01,724
Speaker 1: And for me, like my incentives were like most of

641
00:34:01,724 --> 00:34:04,284
Speaker 1: my classes I was really interested in, Like I wanted

642
00:34:04,324 --> 00:34:06,684
Speaker 1: to learn, right, Like I went to a school that

643
00:34:06,804 --> 00:34:10,124
Speaker 1: I thought would teach me things that I realized. You know,

644
00:34:10,164 --> 00:34:14,124
Speaker 1: I sound like a very you know, uh do ie

645
00:34:14,684 --> 00:34:18,284
Speaker 1: bushy tailed student, but like to me, that was that

646
00:34:18,404 --> 00:34:21,044
Speaker 1: was the whole point. Like I wanted to read these books.

647
00:34:21,364 --> 00:34:24,124
Speaker 1: I want to think through you know, I wanted to

648
00:34:24,204 --> 00:34:28,204
Speaker 1: be kind of a better, you know, a better person,

649
00:34:29,004 --> 00:34:33,724
Speaker 1: someone who who has that knowledge, you know. I wanted

650
00:34:33,764 --> 00:34:36,004
Speaker 1: to kind of have it in my head, like if

651
00:34:36,004 --> 00:34:39,324
Speaker 1: you're on a desert island right with no CHATPT and

652
00:34:39,364 --> 00:34:41,604
Speaker 1: you just have kind of the stuff that's in your head.

653
00:34:42,084 --> 00:34:46,204
Speaker 1: I wanted to kind of have good things in there.

654
00:34:46,284 --> 00:34:49,364
Speaker 1: And so I never I mean I never even like

655
00:34:49,724 --> 00:34:52,004
Speaker 1: gray Zone cheated when I was in college, Like I

656
00:34:52,044 --> 00:34:56,204
Speaker 1: didn't collaborate on assignments. I didn't do anything like that.

657
00:34:56,204 --> 00:34:59,084
Speaker 1: That said, like I never told on anyone either, right,

658
00:34:59,244 --> 00:35:02,444
Speaker 1: Like I was not someone who would be like Nate

659
00:35:02,564 --> 00:35:05,964
Speaker 1: use chat GPT, right, Like, if you want to use

660
00:35:06,044 --> 00:35:08,884
Speaker 1: chat rept, fine, but even if everyone was using it,

661
00:35:08,924 --> 00:35:14,004
Speaker 1: like I I think I wouldn't I wouldn't feel right

662
00:35:14,204 --> 00:35:18,124
Speaker 1: about myself if the teacher actually said, do not use

663
00:35:18,284 --> 00:35:21,244
Speaker 1: chat GPT. And like I said, for most of the

664
00:35:21,284 --> 00:35:23,844
Speaker 1: classes I took, a huge chunk of the grade was

665
00:35:23,964 --> 00:35:29,004
Speaker 1: in class, in class, exams and assignments, and so that

666
00:35:29,164 --> 00:35:31,804
Speaker 1: was something where you know, chat GPT wouldn't be helpful.

667
00:35:32,004 --> 00:35:34,244
Speaker 1: But I also I wanted to be a writer, Nate, like,

668
00:35:34,644 --> 00:35:36,724
Speaker 1: I wanted to learn how to write well, and I

669
00:35:36,804 --> 00:35:38,924
Speaker 1: wanted one of the reasons that I wanted to go

670
00:35:38,964 --> 00:35:41,364
Speaker 1: to Harvard was to study with very specific writers. I

671
00:35:41,404 --> 00:35:44,804
Speaker 1: wanted their feedback on my writing. It would just completely

672
00:35:44,844 --> 00:35:47,364
Speaker 1: defeat the purpose, right if I took a fiction writing

673
00:35:47,404 --> 00:35:50,484
Speaker 1: seminar and had chat GPT write my short story, Like,

674
00:35:51,124 --> 00:35:53,004
Speaker 1: what am I even doing? Well?

675
00:35:53,004 --> 00:35:55,004
Speaker 2: What if you sound stupid? What if it's a let's

676
00:35:55,044 --> 00:35:59,204
Speaker 2: say that you're taking a physics class and it's part

677
00:35:59,244 --> 00:36:01,604
Speaker 2: of a requirement for some hard sciences, right, and the

678
00:36:01,644 --> 00:36:07,964
Speaker 2: professor is unintelligible and boring, and these assignments are unnecessarily

679
00:36:08,804 --> 00:36:12,644
Speaker 2: hard for students who are not going into the science concentration. Right.

680
00:36:14,084 --> 00:36:17,244
Speaker 1: Yeah, So I think that I can see using chat

681
00:36:17,244 --> 00:36:20,684
Speaker 1: GPT to help me explain to help explain stuff, right,

682
00:36:21,084 --> 00:36:24,444
Speaker 1: use other aids outside of class to try to get

683
00:36:24,644 --> 00:36:27,044
Speaker 1: to try to get oriented and try to figure it out.

684
00:36:27,364 --> 00:36:29,964
Speaker 1: But I would still, I think, do my own final

685
00:36:30,004 --> 00:36:32,604
Speaker 1: assignment in the end, like there was one class. This

686
00:36:32,764 --> 00:36:36,604
Speaker 1: is one of my biggest regrets, and so I don't

687
00:36:36,604 --> 00:36:38,844
Speaker 1: want students to have regrets like this. One of my

688
00:36:38,884 --> 00:36:43,844
Speaker 1: biggest regrets from undergrad was I took this course AX ten,

689
00:36:43,964 --> 00:36:48,004
Speaker 1: which was you know, your introductory economics class my senior year,

690
00:36:48,044 --> 00:36:50,964
Speaker 1: because I needed it as a requirement, and I took

691
00:36:50,964 --> 00:36:55,444
Speaker 1: a pass fail because I could write and I didn't.

692
00:36:55,524 --> 00:36:57,284
Speaker 1: At that point, I thought that I didn't really care

693
00:36:57,284 --> 00:37:00,364
Speaker 1: about economics, want to know any of this. And it

694
00:37:00,404 --> 00:37:01,964
Speaker 1: was really early in the morning. I think it was

695
00:37:02,004 --> 00:37:04,764
Speaker 1: like at nine am or something, you know, a time

696
00:37:04,804 --> 00:37:07,524
Speaker 1: that was just ungodly for me even today, but as

697
00:37:07,564 --> 00:37:10,684
Speaker 1: a college student like, no, no way, And so I

698
00:37:10,764 --> 00:37:14,484
Speaker 1: ended up skipping a ton of lectures and almost fail

699
00:37:14,564 --> 00:37:17,324
Speaker 1: the class. I really regret that because, first of all,

700
00:37:17,404 --> 00:37:22,164
Speaker 1: the class was taught by legendary professor, and the speakers

701
00:37:22,204 --> 00:37:25,124
Speaker 1: we had in that class were insane, right, We had

702
00:37:25,204 --> 00:37:28,204
Speaker 1: like secretaries of State, We had the things that I

703
00:37:28,364 --> 00:37:31,164
Speaker 1: missed right now, when I look at our syllabus, I'm like,

704
00:37:31,724 --> 00:37:32,484
Speaker 1: what an idiot?

705
00:37:32,604 --> 00:37:32,764
Speaker 2: Right?

706
00:37:32,804 --> 00:37:35,924
Speaker 1: I wish I could go back in time and actually

707
00:37:36,404 --> 00:37:39,924
Speaker 1: learn this information. So the one time where like I

708
00:37:40,004 --> 00:37:43,524
Speaker 1: obviously wasn't cheating or using chat gibta, I almost failed,

709
00:37:43,524 --> 00:37:45,564
Speaker 1: for God's sake, the one time I tried to like

710
00:37:45,964 --> 00:37:48,044
Speaker 1: glide through a class because I didn't think it was

711
00:37:48,044 --> 00:37:52,284
Speaker 1: irrelevant or interesting. I really really regret it because I

712
00:37:52,324 --> 00:37:55,364
Speaker 1: realized now just how relevant and interesting it was and

713
00:37:55,404 --> 00:37:58,444
Speaker 1: how much I missed. So kind of looking back at

714
00:37:58,524 --> 00:38:01,044
Speaker 1: college me, I want to shake myself and say, hey,

715
00:38:01,444 --> 00:38:03,804
Speaker 1: you know, take advantage of this. There is not going

716
00:38:03,844 --> 00:38:06,644
Speaker 1: to be another time where you get like an hour

717
00:38:07,164 --> 00:38:09,364
Speaker 1: one on one with Larry Summers to ask him quite

718
00:38:09,724 --> 00:38:11,684
Speaker 1: about the economy.

719
00:38:11,724 --> 00:38:14,724
Speaker 2: You know. I asked my Twitter followers did they cheat

720
00:38:14,764 --> 00:38:18,004
Speaker 2: even a little tiny bit in college? And it was

721
00:38:18,044 --> 00:38:22,724
Speaker 2: almost exactly fifty fifty yes and no, which means on

722
00:38:22,764 --> 00:38:26,564
Speaker 2: the show, if you are avowing Maria never to have

723
00:38:26,764 --> 00:38:31,524
Speaker 2: even a tiny bit cheated, does that imply that I

724
00:38:31,604 --> 00:38:32,644
Speaker 2: therefore did cheat.

725
00:38:34,684 --> 00:38:37,004
Speaker 1: I wouldn't. I wouldn't say that. I would say that

726
00:38:37,084 --> 00:38:38,004
Speaker 1: you probably did not.

727
00:38:38,764 --> 00:38:41,324
Speaker 2: I think I did. I think this counts. So I

728
00:38:42,684 --> 00:38:47,844
Speaker 2: was in an econometrics class, and ironically, econometrics is like

729
00:38:47,884 --> 00:38:50,524
Speaker 2: actually pretty relevant to my day to day work now, right,

730
00:38:50,964 --> 00:38:55,444
Speaker 2: But the class was taught terribly. The professor was a

731
00:38:55,444 --> 00:38:58,724
Speaker 2: good scholar who was very disengaged in University of Chicago

732
00:38:59,004 --> 00:39:02,964
Speaker 2: was maybe more tolerant of that than they should have been, right,

733
00:39:03,044 --> 00:39:05,204
Speaker 2: and you know, my very good friend, I mean, I would,

734
00:39:05,324 --> 00:39:08,324
Speaker 2: you know, ask to copy off a couple of those

735
00:39:08,364 --> 00:39:11,564
Speaker 2: problem sets with his mission sometimes? Right, that's cheating, isn't it,

736
00:39:12,364 --> 00:39:14,604
Speaker 2: I think, Solia, Yeah, it's funny because like if you're

737
00:39:14,604 --> 00:39:17,004
Speaker 2: doing the homework together, it's probably not. But like I

738
00:39:17,004 --> 00:39:19,204
Speaker 2: think it's cheating. And I don't regret it because the

739
00:39:19,204 --> 00:39:23,924
Speaker 2: class sucked and and still most of the grades based on

740
00:39:23,924 --> 00:39:26,204
Speaker 2: on the end of the year, right you still, I mean,

741
00:39:26,284 --> 00:39:29,324
Speaker 2: you know, so if I fucked myself over, then that's fine,

742
00:39:29,364 --> 00:39:31,564
Speaker 2: But I don't I think that was a rational decision.

743
00:39:32,204 --> 00:39:34,004
Speaker 1: You know what, now that you say that, I realized

744
00:39:34,044 --> 00:39:35,284
Speaker 1: that I did cheat.

745
00:39:35,564 --> 00:39:36,044
Speaker 2: There you go.

746
00:39:36,164 --> 00:39:39,964
Speaker 1: If in school, so when I was in eighth grade,

747
00:39:40,684 --> 00:39:46,404
Speaker 1: I had this science teacher who liked to basically we

748
00:39:46,444 --> 00:39:49,444
Speaker 1: had our science curriculum and then he also taught birds

749
00:39:49,524 --> 00:39:53,724
Speaker 1: and stars, so basically we would get pop quizzes all

750
00:39:53,724 --> 00:39:56,604
Speaker 1: the time where he would play bird calls and we'd

751
00:39:56,644 --> 00:39:59,444
Speaker 1: have to say what bird it was. However, as part

752
00:39:59,564 --> 00:40:03,724
Speaker 1: of the bird stuff, he would give us these basically

753
00:40:03,804 --> 00:40:08,804
Speaker 1: you know, like coloring book sketches of birds, and we

754
00:40:09,044 --> 00:40:12,924
Speaker 1: had color them in for homework and we were graded

755
00:40:13,124 --> 00:40:15,644
Speaker 1: on how well we colored them in. And I was like,

756
00:40:15,764 --> 00:40:19,524
Speaker 1: this is bullshit. I have zero artistic ability, like I

757
00:40:19,564 --> 00:40:22,684
Speaker 1: hate you know, I can't draw, stick figure, I can't color.

758
00:40:22,844 --> 00:40:25,124
Speaker 1: I was like, this has nothing to do with science, right,

759
00:40:25,164 --> 00:40:27,324
Speaker 1: this has nothing to do with what I'm learning. This

760
00:40:27,404 --> 00:40:30,244
Speaker 1: is insane. And my sister is a beautiful artist. So

761
00:40:30,844 --> 00:40:34,324
Speaker 1: she actually, first of all, I had she had taken

762
00:40:34,324 --> 00:40:36,684
Speaker 1: the class, you know, six years before I did, so

763
00:40:36,724 --> 00:40:39,564
Speaker 1: she gave me her birds to like help me figure

764
00:40:39,564 --> 00:40:41,684
Speaker 1: out how to how to color them in, and then

765
00:40:41,724 --> 00:40:43,684
Speaker 1: when she had time, she would color them for me.

766
00:40:44,004 --> 00:40:46,404
Speaker 1: And then I had another friend who was who loved drawing,

767
00:40:46,684 --> 00:40:48,724
Speaker 1: and she would color my birds for me. And I

768
00:40:48,764 --> 00:40:52,604
Speaker 1: hardly ever did my bird coloring in myself because I

769
00:40:52,644 --> 00:40:53,364
Speaker 1: just thought it was the.

770
00:40:53,324 --> 00:40:55,724
Speaker 2: Most too cheaters mister business here.

771
00:40:56,204 --> 00:40:58,524
Speaker 1: So now that you now that I think about it,

772
00:40:58,924 --> 00:41:03,044
Speaker 1: that was that was definitely problem not above board, but

773
00:41:03,164 --> 00:41:05,724
Speaker 1: it was just because I made the decision that this

774
00:41:05,844 --> 00:41:08,324
Speaker 1: was an incredibly bad use of my time. And I

775
00:41:08,364 --> 00:41:10,644
Speaker 1: stand by that just like thank you. I have no regrets.

776
00:41:10,964 --> 00:41:13,564
Speaker 1: I do not care that I don't know how to

777
00:41:14,884 --> 00:41:19,844
Speaker 1: color in a downy woodpecker or whatever. It was toughted mouse.

778
00:41:22,324 --> 00:41:36,884
Speaker 2: And we'll be right back after this break. I mean,

779
00:41:36,924 --> 00:41:42,284
Speaker 2: there's an argument against assigned homework in general, and do

780
00:41:42,324 --> 00:41:44,684
Speaker 2: the readings you can participate in class right and or

781
00:41:44,764 --> 00:41:47,324
Speaker 2: past your final at the end of the year. Right.

782
00:41:47,444 --> 00:41:51,524
Speaker 1: Yeah, I'm actually I'm actually very sympathetic to the no

783
00:41:51,684 --> 00:41:56,324
Speaker 1: homework type of thing because you know, if you, I

784
00:41:56,364 --> 00:42:01,564
Speaker 1: think homework often incentivizes cheating, right when people feel like

785
00:42:01,564 --> 00:42:03,924
Speaker 1: like the homework assignment is stupid or dumb, or you

786
00:42:03,964 --> 00:42:06,484
Speaker 1: have too much of it, like there the incentives for

787
00:42:07,004 --> 00:42:11,444
Speaker 1: homework are not often the correct incentives. And when you

788
00:42:11,484 --> 00:42:13,804
Speaker 1: have those exams so I had, I took a lot

789
00:42:13,804 --> 00:42:16,924
Speaker 1: of seminars where class participation was a huge part in it, right,

790
00:42:17,004 --> 00:42:19,044
Speaker 1: and if you are one of the people who did

791
00:42:19,044 --> 00:42:21,444
Speaker 1: not do the reading that week, it becomes very clear

792
00:42:22,564 --> 00:42:26,684
Speaker 1: pretty or pretty soon in the discussion that, like you,

793
00:42:27,124 --> 00:42:30,764
Speaker 1: you are not adding much value and that like this

794
00:42:30,964 --> 00:42:34,564
Speaker 1: was just this is a week that you were mentally

795
00:42:34,604 --> 00:42:37,284
Speaker 1: not there. And if the purpose of learning is to

796
00:42:37,364 --> 00:42:42,724
Speaker 1: create individuals who have deeper knowledge, critical thinking abilities, kind

797
00:42:42,724 --> 00:42:48,244
Speaker 1: of the ability to synthesize information, to analyze information, the

798
00:42:48,284 --> 00:42:52,364
Speaker 1: types of skills that we want right in our citizens,

799
00:42:52,404 --> 00:42:56,404
Speaker 1: I would hope then homework assignments are much worse at

800
00:42:56,444 --> 00:42:58,884
Speaker 1: assessing those than your ability to kind of have a

801
00:42:58,884 --> 00:43:02,124
Speaker 1: class discussion, your ability to kind of think through things

802
00:43:02,204 --> 00:43:04,444
Speaker 1: and reason through things. So I think that we need

803
00:43:04,484 --> 00:43:07,084
Speaker 1: to figure out how do you kind of create an

804
00:43:07,204 --> 00:43:11,164
Speaker 1: education system that incentivizes the sorts of thinking and behaviors

805
00:43:11,524 --> 00:43:13,564
Speaker 1: that you want your students to emerge with.

806
00:43:13,964 --> 00:43:16,804
Speaker 2: Yeah, look, I think you know maybe as solicials, you

807
00:43:16,804 --> 00:43:21,684
Speaker 2: actually need more actual classroom hours. Right. I had a

808
00:43:21,684 --> 00:43:24,924
Speaker 2: friend who used to work at Amazon, and the culture

809
00:43:24,964 --> 00:43:27,244
Speaker 2: there is that if there's a meeting where there's a

810
00:43:27,284 --> 00:43:31,404
Speaker 2: briefing to read, right, they assume that you did not

811
00:43:31,764 --> 00:43:34,284
Speaker 2: take the time out to read that briefing, right, So like,

812
00:43:34,564 --> 00:43:37,004
Speaker 2: take twelve minutes now and read this briefing and then

813
00:43:37,004 --> 00:43:38,364
Speaker 2: we'll talk about it, right, And it's like kind of

814
00:43:38,404 --> 00:43:40,364
Speaker 2: a part of the meeting, you know, obviously, like I'm

815
00:43:40,364 --> 00:43:43,764
Speaker 2: a big fan of reading in general, but maybe it

816
00:43:43,764 --> 00:43:45,364
Speaker 2: doesn't have to be as Zidak to like prove that

817
00:43:45,404 --> 00:43:47,004
Speaker 2: you read this, Like no, I mean, look, can you

818
00:43:47,004 --> 00:43:49,924
Speaker 2: hold intelligent discussion in class? And then I don't know.

819
00:43:50,004 --> 00:43:52,004
Speaker 2: People always talk about the EDU cases of students who

820
00:43:52,044 --> 00:43:56,564
Speaker 2: are introverted or neurodiversient or English is a second language,

821
00:43:56,604 --> 00:43:59,804
Speaker 2: and yeah, it sucks, but life isn't always fairer, you

822
00:43:59,844 --> 00:44:04,364
Speaker 2: know what I mean? And if colleges become less effective

823
00:44:04,404 --> 00:44:09,164
Speaker 2: at differentiating which students were more effective and when we're

824
00:44:09,164 --> 00:44:10,844
Speaker 2: on it, I mean, you know, then the whole signal

825
00:44:10,844 --> 00:44:14,764
Speaker 2: becomes less valuable and college degrees become worth less, particularly

826
00:44:14,844 --> 00:44:17,844
Speaker 2: the most elite degrees. Right, all of a sudden's just

827
00:44:17,884 --> 00:44:21,004
Speaker 2: now basically like a signal that four years ago you

828
00:44:21,004 --> 00:44:25,044
Speaker 2: were considered a talented student by an emissions committee. Right, yep,

829
00:44:25,244 --> 00:44:26,324
Speaker 2: I completely agree with you.

830
00:44:26,644 --> 00:44:29,284
Speaker 1: I think that this is a very very urgent question

831
00:44:29,844 --> 00:44:32,124
Speaker 1: and one that has huge implications for the future of

832
00:44:32,164 --> 00:44:35,204
Speaker 1: our society, right, because what kind of adults are we

833
00:44:35,244 --> 00:44:38,564
Speaker 1: creating with? What kinds of skills, what kinds of ability,

834
00:44:38,844 --> 00:44:42,924
Speaker 1: what kinds of actual background and knowledge? I think these

835
00:44:42,964 --> 00:44:45,964
Speaker 1: are really important questions we do not want to be

836
00:44:46,004 --> 00:44:49,964
Speaker 1: creating a functionally illiterate society, which is what's going to happen.

837
00:44:50,004 --> 00:44:53,004
Speaker 1: By the way, if you don't actually do any learning

838
00:44:53,124 --> 00:44:56,764
Speaker 1: and instead outsource everything all the time and using.

839
00:44:56,564 --> 00:44:59,604
Speaker 2: Chat, GPT or other LM's other AI tools, well, is

840
00:44:59,644 --> 00:45:02,244
Speaker 2: actually a pretty important life skill. I can imagine some

841
00:45:02,284 --> 00:45:06,204
Speaker 2: assignments where and say yes, we not only you know, allow,

842
00:45:06,404 --> 00:45:09,324
Speaker 2: but maybe encourage you for this particular assignment to do

843
00:45:09,524 --> 00:45:11,244
Speaker 2: this right. And so I mean the other irony I

844
00:45:11,244 --> 00:45:13,364
Speaker 2: think this is becoming true and more and more domains

845
00:45:13,404 --> 00:45:16,404
Speaker 2: evolving AI is that like, if you are pretty smart,

846
00:45:17,004 --> 00:45:19,644
Speaker 2: then your productivity is enhanced by the AI, Whereas if

847
00:45:19,644 --> 00:45:22,244
Speaker 2: you don't know what you're doing then and maybe you

848
00:45:22,284 --> 00:45:24,404
Speaker 2: can kind of fake your way through it up to

849
00:45:24,484 --> 00:45:27,324
Speaker 2: a point, but you may be more fooled by the hallucinations,

850
00:45:27,484 --> 00:45:30,764
Speaker 2: You may be susceptible to misinformation, you may just not

851
00:45:30,804 --> 00:45:32,604
Speaker 2: have any retention for the things that you're having it

852
00:45:32,684 --> 00:45:35,284
Speaker 2: do right. And so, like, you know, if I were

853
00:45:35,364 --> 00:45:38,324
Speaker 2: using chat schipt to write a paper or I could

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00:45:39,484 --> 00:45:40,724
Speaker 2: I don't know. I think I can write better than

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00:45:40,764 --> 00:45:42,644
Speaker 2: chet chip Bet by a long shot still, but like,

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00:45:42,764 --> 00:45:44,404
Speaker 2: but I could figure out ways if I were allowed

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00:45:44,444 --> 00:45:47,324
Speaker 2: to that to make my work to summarize long reading

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00:45:47,484 --> 00:45:52,684
Speaker 2: like that seems like a potentially legitimate use for a student. Right,

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00:45:53,044 --> 00:45:55,924
Speaker 2: here's this very long reading that you have to pay

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00:45:56,004 --> 00:45:59,564
Speaker 2: way too much for the fucking textbook anyway, Right, can

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00:45:59,644 --> 00:46:04,044
Speaker 2: you extract the important parts from this? And guess what

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00:46:04,044 --> 00:46:05,644
Speaker 2: you can do if you're Chinese, Nat, and now you

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00:46:05,684 --> 00:46:08,804
Speaker 2: can have it translate to Chinese. Right, you can up

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00:46:08,884 --> 00:46:12,524
Speaker 2: and down the world level of complexity. Right, you can

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00:46:12,564 --> 00:46:15,364
Speaker 2: say this point might seem obvious to you. Can you

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00:46:15,404 --> 00:46:18,204
Speaker 2: explain this point another way? Right? So, like, you know,

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00:46:18,364 --> 00:46:21,404
Speaker 2: there are a lot of ways that llm's II tools

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00:46:21,444 --> 00:46:23,644
Speaker 2: could be quite helpful for the educational process. But I

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00:46:23,684 --> 00:46:26,884
Speaker 2: just think academia is moving too slow. You know, the

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00:46:26,884 --> 00:46:30,444
Speaker 2: opportunity costs of four years in college given how the

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00:46:30,444 --> 00:46:32,484
Speaker 2: world is changing. I mean, there's a cohort of students

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00:46:32,524 --> 00:46:33,964
Speaker 2: for which it might not be the right decision.

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00:46:34,844 --> 00:46:37,204
Speaker 1: I completely agree with that, and I do think that

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Speaker 1: academia needs to just wake up to what's happening and

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00:46:41,244 --> 00:46:49,244
Speaker 1: figure out how to stay relevant. Risky Business is hosted

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00:46:49,284 --> 00:46:51,644
Speaker 1: by me Maria Kanakova.

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00:46:50,964 --> 00:46:53,324
Speaker 2: And by me Nate Silver. The show is a co

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00:46:53,404 --> 00:46:57,484
Speaker 2: production of Pushkin Industries, and iHeartMedia. This episode was produced

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00:46:57,524 --> 00:47:01,284
Speaker 2: by Isabelle Carter. Our associate producer is Sonya Gerwitz. Sally

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00:47:01,324 --> 00:47:04,324
Speaker 2: Helm is our editor, and our executive producer is Jacob Goldstein.

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00:47:04,844 --> 00:47:06,044
Speaker 2: Mixing by Sarah Bruger.

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00:47:06,444 --> 00:47:08,844
Speaker 1: If you like the show, please rate and review us

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00:47:08,844 --> 00:47:11,204
Speaker 1: to other people can find us too. Thanks so much

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00:47:11,244 --> 00:47:11,764
Speaker 1: for tuning in.