In short
Win-Win Podcast Episode #30 Summary
Episode Title
Nate Silver - Predicting Elections in Chaotic Times
Host
Liv Boeree
Guest
Nate Silver
Podcast Theme
Exploring solutions to complex societal issues through game theory.
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Episode Overview In this episode, Liv Boeree speaks with Nate Silver, a renowned election analyst and founder of FiveThirtyEight, about the unpredictable nature of contemporary elections, the role of prediction markets, and the intricacies of political forecasting amidst chaos.
Key Themes Discussed
- Polling Accuracy: An exploration of how well polls can predict electoral outcomes, especially in a highly polarized political environment.
- Prediction Markets: The viability and future potential of prediction markets as a tool for news and decision-making.
- Game Theory Application: Insights into how game theory can inform political strategies and decision-making processes.
- Political Polarization: Discussion on the divide in political beliefs and its implications for elections and governance.
- Cultural Perspectives on Risk: Nate introduces his concepts of "The River" and "The Village," which describe differing worldviews regarding risk and decision-making.
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Key Takeaways
- Current State of Political Forecasting
- Uncertainty and Volatility: Nate emphasizes the unpredictability of elections, particularly with unique circumstances such as the recent assassination attempt on Trump, suggesting that while polls can be inaccurate, they often self-correct over time.
- Polarization Impact: The current political climate leads to a lack of movement in polling data, as many voters are entrenched in their partisan affiliations.
- The Role of Prediction Markets
- Emerging Trends: Prediction markets like Polymarket are becoming increasingly relevant as they provide real-time insights and actionable intelligence quicker than traditional media.
- Wisdom of Crowds: By leveraging the collective knowledge and instincts of traders, prediction markets can often provide a more accurate assessment of political outcomes than conventional polling methods.
- Nate’s Concepts of "The River" and "The Village"
- "The River": Represents those who are analytical, competitive, and individualistic, often skeptical of conventional wisdom.
- "The Village": Describes a community focused on collective ideals, often found in academia, government, and media, potentially leading to a more centralized power structure.
- Risk Perspectives: These groups differ fundamentally in how they approach risk, with "The River" advocating for decentralized, individual decision-making and "The Village" promoting collective responsibility.
- Information Dynamics and Decision-Making
- Noise vs. Signal: In an age flooded with information, distinguishing between valuable insights (signal) and unhelpful distractions (noise) is critical for effective decision-making.
- Need for Plurality: A variety of opinions and approaches enables better decision-making and prevents any single ideology from dominating.
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Conclusion Nate Silver's insights on election forecasting, prediction markets, and the cultural divides in decision-making underscore the importance of adaptability in understanding political landscapes. The discussion highlights the potential for evolving electoral processes through innovative methodologies while emphasizing the need for robust systems that respect plurality and agency.
Final Thoughts The episode concludes with a reflection on how the lessons learned from poker, risk management, and game theory can apply not only to politics but also to broader societal challenges.
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For more information about Nate Silver and his insights, you can visit his blog at [natesilver.net](https://www.natesilver.net/) or follow him on [Twitter](https://x.com/NateSilver538/).
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00I think we've kind of reached an inflection point where prediction markets are going to be an important part of news coverage. When Joe Biden had that awful debate, I was watching with a well-informed group of people, and we were all kind of looking at each other like, we know this is really bad for Biden, but then you see polymarket and others shifting right away, right? Kind of before even the conventional wisdom had sucked in the media, traders were like, yeah, this is really bad. I know we don't have any data yet, but this is actionable intelligence. Hello, friends, and welcome to the Win Win podcast.
0:29Now, I try and keep this show as apolitical and timeless as possible, And sometimes you just got to talk about the current thing. So what better time than to speak to Nate Silver? Nate is one of the most successful election analysts of modern times. So as well as talking about politics, we also talk about ideological differences between the gambling community and the non-gambling establishment. We bet on things, right? There's an actionable way to know who's right and who's wrong. It's not about your credentials. It's like, do you have the right answer and can you make money on it? A little bit of game theory.
1:02The lesson of the prisoner's dilemma is that if we don't trust one another, we get worse outcomes collectively. And of course, lots of discussions on win-win solutions to ongoing societal problems. Have government behave in ways that are more entrepreneurial? If you're really good at your job, you should be able to make a lot of money for the government if you increase expected value for taxpayers. Let's dig in.
1:34Nate, welcome to the Win Win podcast. Thank you for having me. So to get started, obviously, the big thing everyone is thinking about right now, certainly here in America, is the election, which is nearly, I mean, we're nearly two months away from it now. And it seems like this is probably the most hectic election cycle thus far. You know, there's been incumbents dropping out, an assassination attempt. So I'd love to understand a bit how you are accounting for all this, like, what seems like excessive volatility. And especially like, given the 2016 election, the polls seem to drastically underrepresent the actual likelihood of Trump winning.
2:22So do you think that same phenomenon is happening again in 2024? Or is there something else going on? Yeah, so several good questions there. um one thing i'd say is that in elections i mean we're used to doing things like poker where you get to a larger sample size relatively quickly and even in poker you know we did some simulations in the book over a 10-year period like a live tournament poker player they still it's still a lot of variance that might even out after like 10 years um so our view is that trump over performed his polls in 2016 and 2020 um but we don't make any particular adjustment for that in 2024.
2:57The reason being that it's N equals two. I mean, this audience will understand what that means. And also that in general, the market tends to be a little bit self-correcting where pollsters are aware that Trump did way better than the polls. They were embarrassed by that. They changed their methodologies. And so you kind of count on the market to correct itself. However, we also account for the fact that the polls could be wrong in either direction. So basically you take a forecast and have like pretty wide error bars around it. We think if anything, our assumptions are a little bit conservative about that.
3:27It's based on data all the way back to the 1930s, back when polling was very old-fashioned and you'd have to mail somebody a ballot and things like that. So yeah, the short answer is people should definitely be worried about the chance that the polls are wrong, but they could be wrong in either direction. In 2022, Democrats in some of the key Senate races did better than their polls and not worse, for example. In terms of volatility, I mean, one good thing from a model standpoint is that Americans are so polarized and so partisan that 90 % of people are going to vote the same way no matter what, right?
4:00So you don't have as much swings as you would have in the UK, for example, which is less polarized. You'd never have like a landslide election like Labour won, for example, in the US. It might top out at like an eight or nine point win. Obama won by seven points in 2008, for example. You know, I mean, there are always challenges for when a candidate drops out, how do you adjust your model in general i believe in like kind of minimally invasive procedures when you have a model um you know if you built a system that's robust and it's trained back to you know 50 years ago where you have funky circumstances in the past like ross perot running and dropping out or races where the candidate was chosen very late so you try to not make too many adjustments because then you introduce more subjectivity and of course inherently a model does involve some degree of subjectivity in terms of design choices that you make every kind of node in your decision tree you can often play it either way um but once you kind of commit to a solution i think it's important as a modeler to try to try to stick with it because you can get emotionally invested in your forecast or emotionally invested in the campaign potentially um and making major changes in the middle of a cycle kind of defeats the purpose in some ways of having like a model to begin with, I think.
5:15Do you feel personally that you are like more or less emotionally invested in this cycle than the last one? I think a little bit less. I mean, I don't know. I used to be very afraid of what happens if the model is 70-30 and the 30 % wins, which is what happened in 2016. And now I kind of don't care. You have a, you know, you have top set against a flush draw and the flush draw is going to come through sometimes. And I can't imagine people being any more unreasonably angry at you than they were last time because it was insane how people reacted. It's like it was, your model was the one that gave Trump the highest chance.
5:48So you did the best job out of anyone and somehow you got the seat. Well, just the market, we were long Trump. So if you had bet on the forecast, you would have bet you could get six to one odds for two and a half to one shot. And so that would have been a pretty good bet to make. But one thing is that with the book and now the model is kind of at my newsletter, I thought it would have like a smaller audience. It still has a really big audience, which is good, I guess. But I'm framing it in a way where, yeah, the goal of this is to be probabilistic. We're not trying to tell you who to vote for.
6:17We used to be at ABC News, which is the largest media organization in the U.S. and very mainstream. It's a lot of 70-year-old grandmas watching ABC News and things like that. This is more of a medium-sized niche product, and it's from a former professional gambler. That's the mentality that we take. the way we describe it in the newsletter post is often pretty technical. I mean, we take care to write it well. But I think it's framed in a way that we'll have a more understanding audience if that happens. Why is it that the polls barely seem to move when Trump's assassination attempt happened? Because I think polymarket went from, was it 60 to 70 percent?
7:02But then a week later returned and the polls barely moved at all. what's going on there this is where i will throw a little bit of shade on competing products um i mean there's two answers well i mean one is that because people are so polarized that even trump getting shot or even trump being convicted of various felony counts or even biden being 82 years old that only moves a handful of voters um however one thing we spend a lot of time on in the model is how aggressive you should be when you encounter new data um and we think some of the other models are not tuned that well where they're actually too conservative they're using old data when it's clearly time to to update your priors a little bit faster so it's a technical answer but like so we did begin to see um polling after the assassination attempt and after the republican convention where biden was down by about four points on average which doesn't sound like a lot um but biden won by four and a half points last time so you have a net eight nine point swing which in the uk would not be a big deal but in the us is enormous i mean trump is not a popular candidate um and he's lost a popular vote twice the fact that he was winning by this pretty chunky margin meant that people were moved by that so you mentioned how the models would adjust to the this event for example but um as i understand polling is like they can choose who whether they get a representative sample or not.
8:27But otherwise, it's still mostly just whatever people tell they would vote for, right? And now the new 538 also just does polling, right? It's not really a model. Yeah, well, so the old-fashioned way to do it in the golden age of polling is that everybody has a landline phone, and they're really excited when there's a phone call. They're like, oh my gosh, a phone call. I have something to do now. And they'll pick up the phone. And so you'll randomly dial people in the phone book. Of course, it's like no longer a realistic assumption. Some people don't have landline phones at all. In fact, most people don't use their landlines.
9:00You know, people screen their calls a lot and have caller ID. So pollsters have to basically turn this flawed data into models. So every poll is kind of like a model unto itself. And we're kind of like a meta model that aggregates these models and puts some uncertainty estimates around it. Because like, you know, old white people really like answering polls still. And people who are really enthusiastic about their candidates, like right now, if you call today, Democrats had their convention, Kamala is already moving up in the polls, so they're more likely to answer the phone, and that could create bias in the polls.
9:34I wasn't aware that the polls already include a little bit of adjustment, basically. Quite a bit. Oh, interesting. And in fact, I think one lesson they've learned from 2016 and 2020 is that the old-fashioned gold standard way doesn't work anymore when you have severe selection bias in who responds to surveys. What do you make of the explanations that were given back then in 2016 about why maybe the polls seem to under-represent the chance of Trump or whether it was just a normal event? One of those was that people assumed that maybe on a poll people weren't as willing to answer at the time because it came with stigma to say that you're voting for Trump.
10:11Do you think that was a legitimate explanation or is that just something people made up? I mean, it's a logical theory. I think the evidence mostly points against that. For one thing, it's kind of like how a Democrat might think of a Republican, but Republicans are very proud of Trump, or at least Trump voters are. They wear the MAGA hats and they have lots of yard signs and things like that. Also, Americans tend to be pretty honest about sharing their opinions with strangers, which is kind of unusual in other cultures. For a consulting project, I did a little bit of work on the Indian election.
10:44and in India the polling is just a disaster. There are so many languages and so many ethnic groups, but there are also so many social classes in India, and so some classes don't feel comfortable giving their honest opinion about politics when a pollster calls. In the U.S., we don't have that as much. It's more that the people don't answer the polls to begin with. There's like, you know, I'm calling from the New York Times. Would you like to take a poll? If you're a Trump supporter, then you probably hang up the phone. Right. That makes sense then why the model adjustments would be rather minor and you would expect the market to kind of having adjusted for it.
11:19Yeah. And again, I mean, it's worth worrying about. Although there's also other data. I mean, you see, for example, Kamala Harris's fundraising increasing a lot. The fact that she's a few points ahead. I mean, Democrats have usually won the popular vote. The electoral college is closer. So in some ways, it's a very non-dramatic, non-provocative forecast to say, yeah, it's 50-50 with a slight edge for Harris, which is what our model says now, basically. You recently joined Polymarket as an advisor. Can you explain for the audience who I think some might not be that familiar with what prediction markets actually are, why they are a sort of novel technology and what is it they are actually doing?
12:00So prediction markets are kind of what they sound like. they're like a stock market, essentially, where you can make bets based on whether events will occur. So for example, at the Democratic National Convention, there were rumors that there would be a special guest like Beyonce. It turned out they were false. But of course, there were lots of DGENs like betting on Polymarket and other markets about this. So it's an idea that's been around for a long time. And like you said, I'm an advisor. I think now there's been a critical mass where you have actual liquidity in the market. So you have like real price discovery.
12:32There's like actually quite a bit of money that's being bet on these markets. And they're very useful at times when there's not a good way to quantify something with a model and you need kind of people's intuition instead. When Joe Biden had that awful debate, I was watching with a well-informed group of people and we were all kind of looking at each other like, we know this is like really bad for Biden. But then you see polymarket and others shifting right away, right? Kind of before even the conventional wisdom had sucked in in the media, traders were like, yeah, this is really bad. I know we don't have any data yet, but this is actionable intelligence.
13:10And it was funny if you look at like things like Bitcoin, for example, because Bitcoin is thought of as being, you know, it's good for Trump is thought of as being good for Bitcoin. So rises for Trump in the polls tend to produce with a lot of noise increases in Bitcoin. At some point, the markets, both the crypto markets and the prediction markets thought, oh no, this is going so bad now for Biden that they might actually have to withdraw his candidacy, which could hurt Trump because then you get a better nominee instead. And so you got a big bounce for Trump and it kind of flattened out actually toward the end of that night.
13:41But like that's an example of where it's much faster to collect that data. And the intuitions that people have are usually pretty good. I mean, it's a whole notion of price discovery and the whole notion of consensus estimates. It won't be perfect. I mean, if it were perfect, you'd have like no incentive to trade. But I think we've kind of reached an inflection point where prediction markets are going to be an important part of news coverage. If I'm writing a blog post and I want to make sure in a newsletter, I want to make sure nothing major happened in the campaign that would cause me to like update my headline, I'll just go to Polymarket and be like, oh yeah, this number's the same.
14:16Nothing huge happened in the past five minutes. We can go ahead and publish and then et cetera. So it sounds like they are essentially capitalizing on the wisdom of the crowds. For sure. Yeah. As a form of truth seeking. Truth seeking or I mean, it's, you know, in our gambling adjacent world, sometimes having a financial incentive gets you closer to the truth. Right. Some skin in the game. Which makes some people uncomfortable. Look, I think you have like pretty smart people. I mean, one of the problems before with political forecasting is that unlike sports, where you can kind of make a living, oh, it's really hard, is the sports better?
14:50There was not a professional class of politics forecasters, but now between the prediction markets on the one hand, and also every investment bank and every hedge fund is trying to price macro risk. And so they're more interested too in what effect would Donald Trump versus Harris have on interest rates or different sectors of the economy and so forth. How much of an issue is it, though, that, you know, let's say you're using you're looking at prediction markets to get an estimate, see what the latest probability of Trump versus Kamala is. Aren't the majority of I would expect the majority of users of a prediction market, people who are actually betting on this stuff to be more likely.
15:32You're very risk tolerant gamblers who maybe swing more Trump. So is there any kind of like, how do you, how can that be factored in essentially the selection effect going on of the users? I mean, in principle, when a market's robust, right, if there are a bunch of Trump bias bettors in the market, then I stand to have a very high expected value by being a well calibrated bettor. um yeah look in practice um especially for the less liquid stuff they're probably a little bit a little bit trump leaning they're probably also a little bit kind of third party crypto independent minded contrarian libertarian leaning on all these things right they might over it the importance of rfk jr for example um it is funny there's another market which is free but also pretty good called manifest or manifold rather they have a conference called manifest um and like a little bit more kind of crunchy granola effective altruist adjacent kind of left-leaning and so there's often a delta between polymarket and manifest or manifold um where manifold's like a little bit more democratic um the polymarket folks like people say well it's because it's not real money so it's less reliable but there's probably like a little bit of of cultural differences on both sides there's also a multiple point difference between polymarket and predicted currently, which is the more right-leaning and left-leaning.
16:50I think over time, you would expect that the accurate better is the one that will still drive, well, the price will still be discovered, basically, in the end. But initially, the right-leaning ones might actually kind of bias, I think, a whole side a little bit, right? And then after many iterations in the limit, you would expect that those have money that have been more accurate over time. But this over time thing just needs to set in. I mean, even in sports betting markets, when you have a lot of public money, then the market can actually have an exploitable bias because there's not enough smart money to eat up all the dumb money, basically.
17:26In the Super Bowl, you probably, if you, you know, if you fade the public in the Super Bowl, meaning bet on the unpopular side of what the average Joe thinks, then it's probably plus CV enough to clear the house's rake. but probably not like in an everyday Major League Baseball or NBA game only in like the big special events where there's an uncanny amount of public interest but an election would qualify there. I mean I think these markets can be off because like there are a lot of people with opinions about Trump or Harris. Some of them have money maybe more of the Republican leaning ones and so you know it probably is there still probably is expected value to be gained from those markets I think.
18:05Yeah people who are opposed to prediction markets on elections, their sort of core argument is that, well, if someone has money on it, then it's going to influence the way they vote. And then this is going to mess with democracy. Is that just nonsense? I mean, like there isn't a lot of money in elections anyway, right? Each campaign is going to raise, you know, a billion dollars. And it's kind of, it's kind of, I mean, it's kind of school marmish objection, right? I mean, you know, there are some concerns about inside information. If you knew, for example, that Beyonce wasn't going to come to the DNC, then you could like make a lot of money on that, for instance.
18:38But at the same time, the prediction markets benefit from inside information, right? Like, insofar as a prediction market's value is providing information to the outside world rather than only for the betters, you kind of want the insiders. Yeah, there's some radical transparent view that why do we want to rely on the New York Times, the Washington Post to report the news? Instead, we can kind of learn that through prediction markets. You can sometimes have this funky thing where people think there's inside information when there isn't. It's kind of like a self-fulfilling doom loop. But, like, the way I put it is, like, you already have people making bets on these outcomes anyway, in the stock market and in, you know, bond markets and things like that.
19:17People are making big bets, but it's inefficient because you have a lot of, to get the bucket of things that you want to trade, you're fading a lot of other risk, for example. So it's very noisy. So, like, why not let people price political risk directly, I would think. I wonder if it's a little bit, people hate the idea of someone benefiting. Yeah. You know, oh, this person's making money from this insider knowledge they have. Okay, yes, it happens to make the market more accurate, which is a very anti-win-win mindset. Like actually, like, okay, but they're improving the information ecosystem for others by making money from this insider knowledge.
19:57I don't know. I can see it's a little bit of a moral quandary. but yeah but look i mean again i think it's very hard to separate out any objections you have about political prediction markets from the stock market for example and there is insider trading maybe you could say that people in the prediction markets community should be more hawkish and crack down more on insider trading there instead of kind of cavalier idea that i find attractive igor but like but you know you can understand that that can be objectionable but by the way also in like in sports betting um you're allowed to bet for example on who will be the first pick in the NFL draft.
20:32If you are a beat reporter for ESPN, you 100 % for sure have extremely actionable inside knowledge about that based on talking to teams and things like that. And so, you know, so why politics gets separated out? I think people are a little bit precious about that. But in general, I think markets are good. I mean, it's kind of like probably the core neoliberal proposition is that like on balance markets work because people are flawed and and experts are flawed too. And so putting money in the line is kind of what creates a actionable consensus. I mean, it ties in quite nicely with these, this concept that you talk about in your new book.
21:11Here it is. On the edge, which is basically all about risk. Frankly, I've never read a book that is more like my own personal, like life story than this. Cause it's got, it starts off about round poker. Like that's our whole thing, me and Igor for 10 years. And then Then it goes into investing, tech and Silicon Valley, who we've sort of been adjacent to in many ways. And then effective altruism, rationality, all of this stuff. And it was a very fun read. So its core concept is about that there are these kind of like two categories of people in terms of their risk tolerance. You've got the river and the village.
21:54Can you explain what those are? Yeah, so the river is people like you guys or people like us, I guess. It's people who combine two qualities, one of which is they're very analytical. They know all these concepts like expected value and game theory and Bayes' theorem, all that stuff. We kind of speak the same language. Plus, they're really competitive. They want to win. They can be a little bit contrarian sometimes. They tend to be skeptical of the conventional wisdom. um they're also maybe with the exception of the effective altruists are very individualistic right um kind of classic liberalism emerging from the enlightenment where we believe in individual rights and we believe in in free markets and we believe in democracy and things like that and kind of decentralized solutions in some ways um whereas the village is a community of of people who kind to produce ideas for a living but with a slant toward government, academia, and media.
22:52So more concentrated on the U.S. East Coast, you know, Harvard and the New York Times and Yale are classic village institutions. And the village is more about the collective, right? What's the collective good? It's maybe, I think, less truth-seeking, although in theory it's supposed to be. Academia and journalism are supposed to be truth-seeking, but it's kind of maybe moved toward being a little bit partisan, but it's kind of like the credentialed expert class, I guess you'd say. Yeah, kind of like when people talk about the establishment. The establishment's another entirely appropriate term for it.
23:22Yeah. So it's interesting you mentioned decentralization for the river, because that's what sort of, I think if you had to like distill what the essence of the two things are, is that Riverians very much, you know, their religion is the idea of let the decentralized intelligence do its thing, let markets emerge, and that's a way of truth-seeking. And the village is more, expertise is important. Some things require more centralized structures. It's a little bit more control-oriented in that way. So they're almost like different mechanisms of power aggregation, something like that. For sure, yeah.
24:04I mean, you know, if you lose a little bit of faith in central planning, it probably makes you more reverian. as I call it. I should say these are both groups of elites. 1 % versus the 1 % and the 98 % is somewhere or nowhere, or maybe they encounter the river in a casino in Las Vegas occasionally and things like that. So they're competing for power and influence when you had Bill Ackman, the hedge fund manager, trying to get the president of Harvard and MIT ousted in Penn. That's a very river versus village confrontation, for example. Or the New York Times suing open AI is an interesting one.
24:41Although the New York Times is like unusually entrepreneurial for a village institution. So that's a little bit more understandable, I guess. But you do see this kind of clash explicitly. You also see some parts of the river in Silicon Valley having become more Trump-pilled. Obviously Elon Musk, for example, Peter Thiel kind of got the Trump religion in 2016, and they're both big figures in the book. That's probably not typical. I mean, I think if you kind of had a survey at like, um, some, you know, elite world poker tour tournament, I think you'd have more Harris voters and Trump voters. I don't know.
25:19Yeah. I think it would skew about, it'd be close, but 60, 40, something like that. With a lot of third party votes of different kinds, probably two. Um, yeah, but, but you have had like a permission structure in the river to vote for Trump that I don't think you had as much, you know for a you go to like these finance poker games in new york and you know i was like yeah i'm a vote for trump and like i thought just in my experience that was less likely maybe they were actually voting for him and not talking about it um but that was less likely to occur for four eight years ago i think how much do you think the distribution of people sort of leaving the village for the river or vice versa changed over the last few years.
26:00Because it seems like, certainly for me, the entire COVID experience was just like, oh, wow, our institutions suck. People call it getting red-pilled or whatever. I don't particularly like that term because it makes it too much about Democrats and Republicans. And it's not so much that. It's more about being like, oh, these centralized institutions, even though I think they're incredibly important and valuable because they provide like stability and continuity. We can't be too chaotic and decentralized, but at the same time, they're clearly like woefully ill-equipped for the modern day challenges.
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26:38What direction are people flowing in more? Look, if you look at where influence has been moving, it's toward the river for sure. I mean, you know, academia, you know, the most important development technology today, many people would say is AI, which is being done almost entirely in the private sector. and open AI and anthropic and Google will poach people from academia. So you have like a little bit of a talent drain or brain drain. That's one issue. Um, and then, yeah, when you have a loss of faith in like every institution from like the Catholic church to the media, especially higher education in the U S is declining in trust.
27:12Um, so they've been losing status. Um, and the river, at least for like, we bet on things, right? We can kind of, maybe we're right. Maybe we're wrong, but we actually, there's an actionable way to know who's right and who's wrong. And it's not about your credentials, it's like, do you have the right answer and can you make money on it, basically? Which is a very capitalistic attitude to be sure, but seems to be prevailing in this world where there's a loss of trust. And then there's some like particular impetuses. I mean, yeah, for me, I think I have very moderate views on COVID, but like it was a loss of faith in these institutions to be able to think about uncertainty, calculate cost benefit analysis, but also be truly impartial um that it seemed like there was a thumb on the scale where okay everyone's supposed to um uh stay inside and socially distance but then there's a set of political protests which have like a left-leaning cause and then it's okay to go out you know which it was i think it was fine i think it was good to go out and be politically active it was probably also okay to like go and visit your like dying grandma right it was the hypocrisy that was that was what frustrated me so much it was like no yeah no no one can go outside this guy's getting arrested for wakeboarding by himself or you know or like you know he's on a paddleboard out in the middle of the ocean he's getting arrested but then a few weeks later yeah please go out and protest for george floyd it's like you can't have both and the fact that they were so unselfaware of how how hypocritical it looked you know um it's also like when fauci said at first don't wear masks they don't really do anything and then they flip-flop and say, oh, actually, we really need masks.
28:48They're really important. You might want to double mask, for example. Like people notice that and the, and both sides, but especially the village tends to treat other people as non-player characters, meaning people that have like no agency or intelligence and can't like understand that it's a, to use a game theory term, like a repeated game where credibility matters. And like, we adjust our strategy based on what you did last time. This is why I think some people in the village were so uncomfortable, for example, when Elon Musk took over Twitter, which has had, to be clear, positive and negative effects.
29:18But that was kind of their safe space to enforce the conventional wisdom. And it was actually important. I mean, the kind of pandemic version of Twitter was really important for enforcing discourse norms and for punishing people like me who are like, yeah, maybe we should think about this a little bit more, right? And like just asking questions became stigmatized as a right-leaning or conservative leaning behavior which I don't think it should be I mean I think liberalism always involves a degree of skepticism of institutions um but but yeah so we've seen a shift for sure you mentioned that some the village sometimes tends to treat people like non-player characters NPCs they also yeah it's it comes together with this like basically gaslighting around some of these issues right where it it doesn't even seem like a good strategy though from the outside for them to employ.
30:06So it seems if Fauci or the Surgeon General at the time had said, hey, yeah, we kind of reset that mask are not necessary because we wanted to keep some for the critical care workers, sorry about that. Now they are actually more useful. I feel like a lot of people would have treated that better than if they just pretend like it never happened and constantly kind of try to change what they have said in the past or why they did that. Why do you think this strategy, though, prevails still? I think they maybe have never had to put anything of actual value on the line, which I know sounds harsh, but in the poker world or in venture capital, whatever else, then everyone's had losing bets where they were embarrassed by that and lost money and had to correct for that and hopefully improve their process next time.
30:56If there's no self-improving mechanism, I mean, in principle, the scientific method's supposed to be a self-improving mechanism within within um the village but like that's also pretty broken in the era of the replication crisis and the politicization of certain branches of science um yeah so they don't really pay a consequence for being wrong and therefore they have no incentive to to be right right they they have insufficient skin in the game like they would say that they have some skin in the game in terms of oh well i'm pursuing this job and i want to keep the job but actually the institutions are designed such that tenure, for example, like they will just keep the bottom can't really fall out.
31:34The bottom is pretty high. So the skin in the game is kind of not the same as really putting your... Yeah, or they'd be rational to lie to themselves or lie to others. You know, if you, especially in the village where consensus and community are really important, there's a price to pay for bucking the conventional wisdom on COVID or things like that, right? you'll be ostracized or even canceled potentially and so you know i think they're kind of narrowly rational but have a different function that they're trying to solve for i think that's by the way also an example where prediction markets are particularly useful which would have been another methodology to get to truth answers outside of twitter being bought and now actually discussing it at the time like if if you had a prediction market on the question of where was Fauci and the surge in general at the time just lying to keep the right we'll be later find out about it probably the prediction market would very highly show that it's I know a guy I think he's talked about this publicly so like named Alex Washburn who is a scientist who studied COVID dynamics carefully and there was a big wave in South Africa I think it was the Delta variant or some variant a couple of years ago where cases were increasing very very fast so people getting worried again and financial indicators that um traded based on this were going down right um he realized that like actually yes cases are going up really fast however hospitalizations are not and deaths are not um so it's actually good news that we now have this like new dominant strain of covid that's potentially less lethal so he made a bunch of contrarian bets in the market and won a lot of money um by betting this is actually going to be good in terms of like medium-term COVID forecasting, when all the public health people were like, oh, you have to be really careful now, and we're going to have Omicron 3.0 or whatever.
33:26So yeah, there are sometimes opportunities to profit from those people being wrong. I mean, one argument for why strategically the village don't incorporate probabilities and predictions and grayscale thinking into their speech and their general approach to life is because it's hard to rally people around your cause and get group cohesion if you're saying, well, this is only 80 % likely to be true, which actually is very, you know, that's high confidence. But if you use any kind of granularity and seeming low certainty, then you might lose people, even though actually, so i mean i i don't know it it's based upon the game they're in it's sort of a game theory optimal strategy to do that right yeah this is kind of classic the classic pundit problem where if i go on you know nbc news like nate's what's your latest forecast says and i say kamala harris is going to win that gets a lot more hits and saying oh it's 52 to 48 so there's that incentive um also there's a lot of sloppy heuristics like things like um what's it called the precautionary principle like oh do no harm it's like well you're gonna do harm either way in kobe either people gonna die or all or all school children in america are out of school for a year right these are two pretty bad harms and we have to have like some way of of calibrating them and weighing them against one another so um and you have this kind of strategic bargaining where it is a game theory we're like so on dating sites um you know every man you know under six foot will add like an inch to their height or something, or maybe two inches, because everybody else does anyway, right?
35:10So therefore you're even, you're becoming like shorter effectively to the dating pool unless you lie. And so the equilibrium involves like a degree of fudging up to the point where if your date encounters you, they're not like, you're not six foot three, you're five foot eight. You can't do that. That like is, you know, negative EV, but you can lie within certain boundaries. Where does the river go wrong? Like what are their blind spots or weaknesses that concern you? I think there are, you know, quite a few, actually. You know, one is that they tend to be a little bit cocky and overconfident because kind of by definition, especially the people we talk about in the book where, you know, there is a bias when you're writing kind of a narrative book toward speaking with the success stories and not writing about the failure stories as much.
35:53but if you're somebody who has you know made a couple of really good investments and you're kind of a winner or a poker player who early in your career you run really good and win a couple of big tournaments or make several big final tables you're probably due for some mean reversion and you know and you may be a little bit of an asshole until that happens until you've kind of had the shit kicked out of you a couple of times you're probably a little bit cocky and overconfident you know look there are certainly there are certainly anti-capitalist critiques of the river. It is making a lot of money.
36:26It's very individualistic. So if you're from the left, there are good critiques you can make. You know, the river, I think, has issues with gender diversity and racial diversity to some extent. Poker is very male. We can talk about the reasons for that. VC is very male. It's, you know, white and or Asian for the most part, most of these communities. So that's, I think, a valid line of critique. I think the river is often has poor political instincts. Candidates who have been chosen, like Michael Bloomberg was like a reverian running in the village. Although he runs a media empire too, so he's a little bit more ambiguous.
37:02But he was a terrible candidate. He ran and spent a billion dollars on the presidential race and won one territory, American Samoa, and that was it. So why was he a terrible candidate? Because when you're trying to win elections, the grayscale stuff doesn't work, right? You want big ideas that you can frame around that are unambiguous you know democracy and honor and truth and freedom and things like that and it just it's just sound bites basically you want sound bites basically and also like most people aren't paying a lot of attention to politics so you need simple heuristics that um that can sell to people yeah i think a thing that i feel that particularly silicon valley have a little bit of a i don't want to use a word as strong as hypocrisy but just like a little bit of disingenuousness around, or at least a blind spot around, is that, you know, they talk about, we're all about decentralization and, yeah, not having any kind of top-down control that these bottom-up things emerge through the market.
38:04And yet they make all these strategic plays such that the net result is that they end up accumulating a huge amount of power. Oh, yeah. And even as someone who, you know, I'm not Elizabeth Warren or somebody, but I think it's concerning when an Elon Musk or when Andreessen Horowitz, if they're growing at 20 % per year and the evidence is that their IRRs, their rates of return are actually quite high. I mean, you know, 20 % per year compounding makes you extremely rich and extremely powerful. I mean, the 10 most rich people in the world are twice as wealthy now as they were 10 years ago. So even if you're like, yeah, you're going to have a few huge winners and maybe in some moral sense, Jeff Bezos doesn't deserve it and it's anti-utilitarian, you'd rather redistribute his income somehow.
38:53You know, I mean, it's a classic capitalist thinking. On net, capitalism lists people out of poverty and it's been good. And so therefore we live with that. um but when you have people who have so much money and also are very interested in political power you know personally maybe going back to more of an arm's length distance say hey look our job is to make great products right um and of course we'll preserve our self-interest when we're debating regulation in congress but we're not going to try to influence political outcomes as much right we're the great tribe we're aloof we're a little libertarian maybe we're a little anti-trump because of threats he presents to institutions but we're not going to be big sticks in the mud about it Like that's an attitude that I wish there were more of, I guess.
39:33And instead people get very, they do get pilled, I think, by politics. I think one of the interesting things going on in Silicon Valley as well around like where the river is perhaps not being as responsible with its risk taking as it could be is where, for example, with VC, you are, they kind of have like an asymmetric payout thing going on. where like they get with their gambles they get to kind of internalize all the benefits but their you know their downsides are sort of capped out at just okay well i lost my investment here but they can also externalize the actual true externality you know negative effects can be externalized sort of onto the public you know they've got this very much move fast and break things mentality it's like okay fine that makes sense if if the externalities are don't exist or They can internalize all the harms with whatever technology they are building, but that's not actually the case.
40:33They're often running experiments on the general public, like, for example, social media algorithms. It's just like they're just putting them out there and like, oh, shit, that turns out that made people unhappy or bad. Oh, whoops. What incentive structures could be designed such that those harms are more internalized? Yeah, I mean, maybe. So, for example, Sequoia Capital was sued by some investors over their investment in FTX. As far as I know, I don't think that's going very far. But like, because you'll hear over and over again, this thing you were saying before, right? They'll say, well, you can make a thousand X your investment, but you can only lose one X.
41:06So it's a really good, really good business, right? We are encountering more technologies now that have maybe more downside than the classic kind of semiconductor and computer industry that was once the heart of Silicon Valley. Social media, I think the net utilitarian effects in society are deeply ambiguous, maybe skewing negative, for example. and with AI then even like Sam Albin will say yeah this could actually eat all the universe and turn it into a paperclip factory but the benefits outweigh the harms but it's a little asymmetric because he stands to benefit and open AI stands to benefit in the world where it turns out well but we all die anyway in the paperclip world and so yeah I don't know I mean certainly the EU takes an attitude toward having greater regulation but you know if you have more tolerance in the U.S.
41:55and China and other places, and regulation can be very hard to enforce. You kind of have like an arms race or prisoner's dilemma dynamic. But no, it's a valid question. You know, look, we need one takeaway of the book is that we need these two communities to communicate and understand one another better. I mean, we need to have smart regulators monitoring AI. I don't have any policy recommendations in the book, but like this is technology that has the power based on the people who are actually creating the technology to like destroy the world um nuclear weapons when they're developed were developed by governments right if you had like raytheon developing and testing nuclear bombs you'd probably want to have a lot of regulations about that so we should think about that with ai stuff as well right and it's it's a little frustrating to see that for example sam altman has previously said yes we we need to have some kind of regulations uh because this is a potentially very powerful and dangerous technology and there's now an incredibly watered down bill the SB 1047 right which has as far as I can tell incorporated a lot of like the big people's complaints but there's still very strong quite organized lobbying against it coming from VC and OpenAI and some of the other companies I I think Anthropic have now said they're okay with it, but it's like, if not that, then what would they ever allow?
43:18They've been talking a big game of allowing regulation, but if they won't even allow this, then it's like, I don't think it's going to happen. You can't trust them to self-regulate, you know, because, look, in some ways, I think, you know, if you look at the three major labs as Google, Anthropic, and OpenAI, I mean, in some ways you have leaders that are relatively safety conscious compared to just a random grab bag of, you know, qualified people from Silicon Valley. But we saw with like the OpenAI board, failed board coup that like the engineers and the capital and everyone else are going to flow to the providers that are more aggressive.
43:54Right. And now we're lucky that they're only three and a half, depending on how you count meta. Right. You know, important players in the space that will, I think. Well, actually, I don't know if that's true. You might think there's more proliferation, or if models get cheaper, then you can have more people who are capable of building dangerous models kind of in their garage. I think it's probably not true, but I'm not quite sure where the thresholds are for where compute gives you X amount of power. But yeah, I mean, we need to get smart regulators on this problem right now. I think there's kind of been a little bit of a plateau in LLM capabilities, which is good, but now is a good time to start having adult conversations which specific regulations are the right regulations is a hard question i think it's a interesting to note that the assumption of why people who are in the river their methodologies work is also because they have skin in the game it's one of the benefits right but skin in the game doesn't quite work at the point when the at the point which we discussed where you lose one x whether it is now you're creating a pandemic because you did some pathogen research or whether the company just fails.
44:59Probably the CEO of the company, they actually have faced liability but investors not that frequently. And Sequoia, despite the probably nowhere going lawsuits, they're still the most reputable investor that exists, even though they like as much went down on their knees in front of SPF as I've seen anyone ever do. They gave him the best blowjob of his life. Yeah, yeah. Full hawk tour to SPF. And frankly, others as well right yeah no it wasn't just ea is also like everybody was yeah like was really down on their knees in front of spf but so were vcs but the thing is ea has taken massive reputational hit in part obviously deserved and uh sequoia not so much which is kind of interesting because alfred linds like yeah we'd invest in it again yeah which in some ways is a refreshingly honest response i suppose but but it also makes sense if you like as an lp in sequoia i'm i'm i'm looking future investor into sequoia even though i don't even know if they manage outside funds actually but uh you're like well you've had this miss but if you had like 10 100x hits i'll just keep going like the the in the way how investors work is not measured by the failures it's measured by their successes yeah maybe in principle if you had like a once a decade scandal so like uh like ftx or like enron maybe there's some threshold in principle you could have some extra degree of liability, like a penumbra of liability that goes beyond just the principles in the company toward the early investors?
46:32I don't know. You mean it as a suggestion? Because currently it doesn't look to be the case. No, as a conceptual idea, I don't know how, I'm not an expert on regulation by any means at all, right? I'm just saying like, if you had some super, super high threshold where for the extraordinary frauds and things like that, the Bernie Madoff type, SPF type frauds, that there is some expanded liability to people who enabled them just create like a little bit of a just a little bit of a deterrent right so it's not purely so it's not purely 100x versus 1x yeah i'm also kind of uh on the side similar to uh the people who are anti-regulation that man if we can find a non-government intervention solution to this i'd prefer that for sure and and that could be just hey can we through journalism or like kind of uh reputational damage make make it sure that yeah the reputational impact actually kind of um occurs on the basis of people seeing what what what happened right because i get to just take down the blog um yeah and which is fine they should be able to but uh it's i think the reputational damage effect though is just it's become so capped because as you said like yeah the internet has such a short memory Like everyone's just has amnesia these days because it's just so much going on.
47:47You can create a little cult and bubble around yourself, right? And people like comeback stories and reinvent yourself. So, you know, I mean, caft is a good term we're borrowing from poker here, I think. But yeah. Well, Frank, probably if they did another extremely bad thing like FTX, then maybe they would suffer more. Yeah, it's hard to judge actually how much reputation damage they've faced, right? I wonder if you can leverage, particularly about making reputational damage within the river, so that other Ravarians are like, okay, well, that was just bad. You played bad poker there, essentially.
48:23You played the equivalent of going all in every hand, just like blindly and dumbly. That could be some kind of error-correcting mechanism? Maybe because Ravarians are hesitant to be as judgmental as the village, they err too far on side of being of tolerating bad behavior right so in the poker world to me people who are known scammers or known cheaters still come and play they just turn up yeah kind of like this six month probationary period and then they come back and play and like that seems quite irrational and in some ways right so what do you think are the most promising paths to building a nice rainbow bridge between the reverians and the village so that they actually do work together because there are there's real wisdom and value in both camps and part of the problem is that like as you described like the world is becoming sort of my more bifurcated in its risk you've got people who are willing to like double or nothing the light cone of the universe on a slight plus ev edge and then you've also got people who won't walk down the street without a covid you know without a mask on.
49:30How can we bring the two communities together such that there's like a sort of more win-winny? It's less, it's less rivalrous. I think one thing that might seem like a minor point, but, but to have government behave in ways that are more entrepreneurial in terms of the staffing, right? So like, if you're really good at your job, you should be able to make a lot of money for, for the government. If you increase expected value for taxpayers, basically, right? And you should have less bureaucracy in government, for instance. Some of the smaller countries, the Scandinavian countries or Singapore or whatnot, have this and they have higher kind of state capacity as a result.
50:04I do think you do see some self-correction though in the village. The fact that, for example, colleges are bringing back standardized tests, I think, shows some ability to self-correct. I don't know that I want to talk too much about wokeness, quote unquote, and that cluster of topics, but you've seen a retreat from that. I thought it was a particularly village way of looking at the world that's now, I think, in some degree of decline. And you've seen, I think, you know, I think you've seen the river kind of get arrogant and make certain types of mistakes recently. And so you do have some kind of rebalancing.
50:39I hope the book in some small way can help to facilitate that. Are there like any promising technological solutions? You know, I mean, prediction markets are a good way. And I think to normalize them is probably helpful to encourage. Because people have no problem with like the weather forecast, right? If there's a 30 % chance of rain, then you bring an umbrella or maybe you don't if it's a short trip that you're taking. So to like normalize that as a way to kind of just kind of tempt people into grayscale thinking a little bit where it just seems natural, I think that would be helpful. Yeah, I mean, I went on a whole campaign like five years ago talking about let's try and quantify our uncertainty, like telling the story of when JFK was being briefed by his chief of staff prior to the Bay of Pigs invasion.
51:23apparently the military advisors are told the bay of pig his uh chief of staff that it was only about 25 chance of success but then the chief of staff told jfk uh oh it's a fair chance of success oh yeah and he interpreted that because a fair chance is such a subjective phrase he presumably interpreted that as something much better than 25 because we know he went ahead with the invasion and then that um created essentially the cuban missile crisis right and you actually give some estimates on what the likelihood of uh the cuban cuban missile crisis could have ended in a nuclear war in the in the toby ord book uh the precipice um which does try to be very quantitative about these different catastrophic existential risks jfk thought there was like a one third to one half chance it could provoke a nuclear war so in the range of 33 to 50 percent um you know post facto maybe we have some information now and and i don't know i haven't really kind of studied that particular case in detail but yeah look i think the fact is that probability is a number which is bound between zero and one right um so yeah sometimes when you put a number on things people take it like a little bit too seriously um it's important to distinguish between like hey it's just kind of my back of the envelope estimate versus this is from a very reliable model, right?
52:44I kind of think people should use like different fonts when they communicate online, right? So like Comic Sans, like a goofy font for like, I just pulled this out of my ass, I'm giving you a number versus like Times New Rowan for like a proper actual model. Very formal, yes, rigorous. I like that idea. It's just like another dimension of information. Essentially, you're giving a style of font. Yeah, it's a bit of a pet peeve of mine as well when people say like, oh yeah, I'm just, I'm guessing it's 27.6%. It's like, well, now you're communicating something entirely different. You shouldn't be allowed to go into false precision when you're very uncertain, basically.
53:17Or you need to somehow highlight that with Comic Sans, I suppose. It's funny because when you're verbally communicating, you have additional tools available. You can be like, 20 % versus 20%. So you lose those tools sometimes in flattened internet communication. Yeah. It also seems that some people just stay away from probabilities because they're kind of dirty or something, where on some topics people don't want to look at it as being a probabilistic event, but rather it's something that was meant to be. And is that a reason? Do you think that the public sees probabilities as kind of, I don't know, taking away meaning or something like that?
53:59I mean, you know, Peter Thiel, who had a kind of religious upbringing, and I think if you pressed him, he would probably be maybe a determinist. He had that objection when I talked to him, right? And he, or a version of that, a more sophisticated version of it that you can find in the book. And he's like, yeah, I think kind of the quants have gone too far and they've arbitraged all possible value out of it. And now it's all about kind of vibes, right? Where if you read the vibes well, then that's actually where you gain a market advantage potentially. that's a different question though yeah no I think I think people find it taboo to speculate or bet on certain things right it's it's kind of like I mean we have this in society all the time right like if you go over to a friend's house for dinner then in 99 % of communities if the friend said oh you know these tomatoes I bought were really expensive at the farmer's market I'm going to charge you your share give me seven bucks for the ingredients for preparing this dinner and my labor time actually I'm gonna give you a discount because I'm your friend like that would seem kind of icky and taboo.
54:57And even for me, when I go to the prediction markets conferences, I'm like, okay, some of this is a little bit too much, but bet on their sex lives, right? Or bet on whether they'll still be religious 20 years from now. And I think probably having some degree of taboo is probably worthwhile or it's just human nature, but yeah. Yeah. I mean, our last episode we just recorded was about our relationship and we were making new 10-year predictions on the likelihood that we'll be together in another 10 years time uh i wonder some of some of the feedback people i've gotten when i've told people that we've done this is that that's actually why would you why would you be trying to quantify your relationship this isn't this like your soulmates or you're not um so yeah it sort of falls into that realm and there is like in part also a reason for it for us it works because we don't take it to um mean that the uncertainty one feels is inherently bad and a sign about the relationship but there is also the counter effect where you do increase the probability if you are just a full believer into the thing right like that's why people that are entrepreneurial for example and start a startup it's like is it maybe even better if they just believe not that it has a 10 chance of success but just like it can only succeed failure is not an option yeah i think many if not most irrational behaviors are rational on some higher meta level of rationality, right?
56:25That there are reasons to be strategically optimistic or pessimistic. You know, for me, I was trying to estimate how many subscribers like a newsletter would have if I did that instead of signing with a big company, for example. And I kind of way underestimated it, which is good for me, but could have led to mistakes and I took other options. But I think it was probably some like rational risk aversion, right? At this point, like you're encountering some diminishing returns you have reasons to be risk averse so like i if i had been paid to make the forecast i think and paid for that accuracy it might have been better right um but to kind of implicitly give yourself like a 20th percentile outcome when you have reasons to be cautious and an 80th percentile outcome when there are reasons to be optimistic and you have less to lose then that might be not the worst trait it's interesting the the value of delusion.
57:19Because again, you have these people, someone like Phil Helmuth in poker, he has, for those who don't know him, he's the most successful World Series of poker player by a huge margin. It's truly incredible just how... frequently he has managed to just wade through these huge lotteries, essentially, these big field tournaments and end up winning. and yet on paper like if you ask a lot of like top poker players they don't think he's a good poker player because he doesn't um he seems to play more much more intuitively and he doesn't follow he doesn't sit and work with these solvers that everyone works with to find out game theory optimal solutions yeah he just finds a way to keep on winning and it's i've never met anyone with more self-belief than him yeah to the point of delusion you're like okay it's like it's like bordering on the realms of madness and it like there are other people i think these like extreme outliers who fall into this category like an Elon people like that who almost it's like their force of will changes probabilities or they are they are operating on a level outside of normal normal probabilistic uh reality um have you ever like dabbled with that yourself like thought about like can I just try and trick myself out you know can I be do we try to like be irrational or I guess by being trying to be irrational you're now becoming irrational because you're aware of it and so it doesn't work or?
58:41I mean, I think in poker tournaments, like having the visualization, visualizing success probably is helpful when you get to the, not the elimination rounds, when you get to deepen the money in poker, right? To envision yourself, I'm going to be at a final table playing really well. I'm going to win the tournament. They'll write a nice post about me at Poker News and things like that. I think that's probably better than the other way around because, you know, having made some deep runs in the course of writing this book, you see people totally lose their shit on day three, day four, day five of the main event or something like that.
59:14And it can be self-sabotage and it can be, I think, imposter syndrome or, you know, at the World Series where everyone starts leaving and all your friends are out of the tournament, you feel like survivorship guilt, I think sometimes. So, you know, envisioning positive things, I think is generally helpful. Maintaining your optionality, I think is often very helpful, which is correlated with open-mindedness, I think, in general and extroversion and things like that. I mean, I think with Phil, I think there are some people who are on some level deeply insecure or awkward or introverted, and they kind of wear a mask, and before long, kind of the mask becomes the person, right?
59:54Because it's kind of funny. I mean, I had a long interview with Phil in Palo Alto, and he's telling stories about how he's one-upping like literally Michael Jordan and Tiger Woods and people like that and talking about Obama. I know I'm too busy to see Obama. And it's like, it's kind of a great, I mean, it's like a Seinfeld character basically. And it's kind of amusing. And I think he actually is, I know him well enough to know he's a kind-headed person, but it's kind of charming if you're kind of like in on the joke a little bit. One thing I'd love to pick your brains on is alternative structures for voting systems because I know it seems very suboptimal to me that the U.S.
1:00:31is sort of stuck in this very inadequate equilibrium that is this two-party system that seems like an inevitable result of using first past the post as as a form of voting and you know there are all these other alternatives you've got like proportional representation approval voting ranked choice so are there any of those that you think like are just an obvious thing that the U.S. should transition to to fix this or is it not a problem in the first place? I mean look the U.S. has diverged from Europe and all types of outcomes over the past couple of decades right our economy is actually doing quite a bit better than the EU but like life expectancy particularly particularly for American men has stagnated right that seems worrisome because the whole neoliberal capitalist thing was always like well yeah some people make a lot of money but people are better off as you can see intangible improvements in both quantity and quality of life right and if life expectancy begins to stagnate in the u.s it's like a you know a four or five year gap if you're in a regression of gdp versus life expectancy but we're like four now or five years in the u.s below where we should be um it's because of you know uh opioids and and cars and guns and and a very unequal health care system and lots of things like that you know it's kind of about like risk-taking behaviors so yeah Yeah.
1:01:52I mean, rank choice voting, I think most wonks, including me, tend to like it. The one flaw is that it puts a bigger burden on the voter, where now you have to rank five candidates. And what happens in practice is that, you know, if you're like a super well-informed political nerd, then you have your whole spreadsheet. If you're not, if you're someone who takes a minute to look at it, then people undervote the ballot. They'll just make their first choice. So kind of like, it gives people who are more invested in politics essentially more votes de facto which i think is probably okay but like you can argue if you're from an equity perspective is a little bit strange well if it ends up being practically that but everyone had the same choice to get themselves the position as well then yeah i guess your choice to do the research yeah i mean it's definitely again it comes down to the like whole equality versus equity thing it's like do you want equal outcomes or equal opportunity.
1:02:45And that's a very, I don't know. I mean, I think one of the biggest critiques of democracy is that by giving everyone the opportunity to have the same influence, but in practicality, those who actually do the most work and study it the most, it incorporates a form of meritocracy in with it. It's also, it's just more information into the system, right? Which is usually a good thing. I think on balance, I like rank choice voting, for sure. And some states, you know, in New York, we have mayoral elections by rank choice. The state of Maine and Alaska have rank choice for most of their elections now.
1:03:20So it's gaining ground. It helps in general, more moderate candidates get elected. It also helps the formation of different third parties. So, so I'm in favor, but I think it's worth looking at the trade-off. And I agree, like maybe to give, I mean, the thing about like the U.S. still is a fairly meritocratic place, right? You know, the economy rewards the combination of having a good idea and being in the right place at the right time. I don't think people who are intelligent are lacking for having lots of ways to make money and have high social status and enjoy their lives these days. It might be too much almost, where if you're a person with a very high agency, then the world's great, right?
1:04:01Better than ever. And if you're not of high agency, then it's hard to navigate and you're under duress a lot of the time. What do you think of approval voting? some people prefer because it has the simplicity at least right you're just marking everyone you like and if you mark one that's fine if you mark three it's fine i think it might be a good compromise for sure yeah and then you would get the moderate candidate is the theory at least because like it where they would appeal to more people similarly actually um first past the post was meant to push or at least a good version of it pushes uh both parties that result to kind of fight for the median voter it doesn't seem to be what's actually happening currently though we've seem to instead fall into a more polarized version of it, which in part also obviously comes for other reasons like the media, etc.
1:04:45Yeah, it'd be interesting. I mean, my suspicion is that the parties are probably pretty close to GTO, to Game Theory Optimal, given by the fact that, you know, both parties win elections about half the time and the coalitions are kind of shockingly close to 50-50, right? If Harris pulls away and wins 54-46 by an eight-point margin, that would be considered an amazing historic landslide. 54-46 is still approximately 50-50, right? I mean, a counter to that would be, though, that if it's the case that 90 % of people are just predetermined with their votes, have predetermined votes, and that has come maybe in part due to past polarization or past history of how they have gotten to those opinions, and then only those 10 % points in the middle are the, then actually 54-46 is landslide victory.
1:05:40For sure. I mean, you're getting like 8 out of 10 of the persuadable people in the short run. In the long run, I mean, look, parties have incentives that they want to make some trade between their ability to pass legislation they want or accomplish their ideological goals and their political goals. That's one constraint. Right. You know, again, these are village institutions, so they care a lot about consensus. And they I think parties make the mistake sometimes of, oh, we want the consensus of the Democratic Party will be our candidate when they should probably lean more toward the center and kind of left.
1:06:12Let the far left or the far right get pissed off. Right. But also, you know, also these dissident voices are often very passionate and have a lot of a lot of influence in the media. right so I don't want to talk too much about like um you know Gaza war stuff but there are lots of people who have very moderate positions on what's happening and just like this is really tragic and I you know it's really bad situation and are not polarized but they're not they just shut up about it like I never blog about Gaza stuff right um whereas the people who are more extreme will you know, we'll protest or whatever else.
1:06:49In your book, Signal and the Noise, you talk about sort of the importance of finding ways to distinguish meaningful information from whether it's random fluctuations or actual misinformation. So, you know, the noise in the system in order to make more accurate predictions. You wrote that now like 10 years ago. And it feels like since then, the world, if anything, that ratio has gotten worse because we've got like generative AI and also polarization itself has increased, which is incentivizing people to create more noise about their opponents. So how has that affected your models? Presumably it's made it harder?
1:07:30I don't know. I mean, the models are in some ways pretty robust. They're just like, we're just looking at the polls and all the other stuff filters through the polls. And then you can ask a question, are the polls getting more accurate or less accurate? You know, look, I'm sure it contributes to polarization where people can cherry pick which information they get. It is kind of funny that somehow large language models take all this crappy content on the internet and turn it into something somewhat useful with a whole ton of computing power, I suppose. But yeah, look, I think it places a premium on the few credible sources or reliably kind of high quality information, right?
1:08:10Like in this environment, in the media environment, then who's winning right now? It's like basically the New York Times, which is the single most influential organization in the United States. And like Substack, where it's like individual authenticity because it's like you're touching grass and it's very granular and reliable. Right. And the whole middle ground is kind of losing credibility, I think. So generally, more data would lead to better predictions, one would think, or at least it's a factor that can lead to it. but then the ratio also matters of signal to noise. The ratio matters, and also, you know, people have a tendency to overcomplicate models.
1:08:47More data leads to more overfitting sometimes and more wacky assumptions or more, you know, partisan assumptions embedded. Do you think the ratio of signal to noise has changed over the last 10 years? I mean, in principle, it gets worse, right? But the amount of useful information is not increasing as much as the amount of total, like, bytes of terabytes of data in the world. The thing I wonder about is whether that actually made predictions harder or easier. So if you were to spend 100 hours on a question to build a prediction in the year 2012, or you spend 100 hours on the same question in 2022, when do you think would you have gotten to a more accurate prediction?
1:09:26I mean, just for reasons of faster software and more tools available. If you're skilled, I think it kind of leads to more winner-take-all dynamics, right? If you're skilled, you have more tools than ever before, including AI tools. And if you're not skilled, then you're more likely to trick yourself, basically. So like the Gini coefficient in prediction making has worsened or something as well? I think something like that. Or when you have AI models that kind of create a rising tide where it's 100 IQ or 120 IQ, then maybe it's like a 118 IQ and 87 no longer matters as much anymore. but like although this varies a lot for different tasks i think that's one of the things i hope for a lot for sure is when um like gemini for example already has a million token context window and i sometimes just feed hundreds of pages of text into it and then get a summary of it and like yeah the compression that you can get in the future from just like looking through a bunch of data as long as there is not some consistent bias in the compression that they're doing for you then you could get really useful information for everybody.
1:10:38For the book, I mean, ChatGPT probably saved me probably maybe like 1.2x more productive. For certain types of... I don't like how it writes. I don't like its prose style. It's kind of like a language nerd. But to vet certain discussions where it has expert-level expertise about some technical topics, about AI, about crypto, and you're talking to... I talked to 200 people for the book, right? But to say, okay, as a first draft, let me kind of vet this with like a reasonably intelligent person who can check my terminology on some AI term that I think I understand, but I want another verification of that, right?
1:11:16Yeah, in particular, the thing I love using it for is it can put on the hat of pretty much anybody. So you can ask it, how would a libertarian respond to this? And just like go back and forth constantly. And that's pretty great. Yeah, I mean, you know, it helps to have this kind of understanding of these different vectors or kind of like color palettes that you're laying on top of one another and things that have that like layered texture. It's like really good at. I mean, even now you see with like some of the vocal stuff where it can do, it's like, give me a, you know, read Mary Had a Little Lamb and a Cockney accent, right?
1:11:52Like that's a very legible question for an AI where it knows the poem that has some notion of like Cockney accent in this and you create that vector. So to just like develop an intuition for like this is a good AI question and this isn't or a good machine learning question, I guess we should say. Like that's a valuable skill to have, I think. What's some advice you can give to listeners who are trying to improve their own prediction making? in terms of like mindset or certain tactics because you you talk about this idea of foxes and hedgehogs and i don't know is there like a certain um short list of of personality traits that you think people should be trying to cultivate more especially something that's like um good bang for the buck in the sense of yeah outside of just really reforming their entire personality just like a little tidbit i mean poker i i do think poker is like this er kind singular activity where it teaches both the decision-making skills and some of the people skills as well.
1:12:53What are the main things you think that you've personally learned from poker? So for me, I probably already have this kind of very Riverian mathy brain. I mean, so something I think I've gotten like, I played a lot of poker in the book, kind of half for research purposes and half for fun and maybe to make a little bit of theoretical EV. I think what I've learned from poker, I think having like a lot more mental focus and mental stamina, right? Where you go, you know, the first time or 2022, I played basically five weeks straight at the World Series for, I think, 12-hour days often, right? You'll go and enter some tournament and you bust out and play like the 2 p.m.
1:13:37tournament. And so, So, you know, when you're like kind of like solving math problems for like 12 hours a day for five weeks in a row, then like that, I think that like improves some types of processing for me at somewhat permanently. Right. I mean, I think the power to be like really observant in poker is worthwhile. I think being the most important thing is being in high pressure situations where naturally once in a while in a tournament, you make a day three, a day four of a big event and you have like actual money on the line. or maybe you're on TV or something like that. Once in a while, I'll play a high-stakes cash game where it's real money that would sting to lose.
1:14:15And so you learn to operate with this stress that is helpful in other situations, right? If I'm on national TV during an interview, you're having a stress response. Your heart rate will probably go up. But if you're used to operating in that zone, that's, I think, a quite valuable skill. So put up 10 % of your net worth in a single poker game and learn to feel that. I wouldn't strictly recommend that. It's hard to have simulated high stakes moments, but I do think, I mean, look, I think a lot of your EV in life comes from a handful of decisions that you make in times of great stress, right? When you have a great opportunity or when you have to make a, you know, when you see some tragedy unfolding, if you make a decision, do I have to like flee or remain here and things like that?
1:14:59So to kind of manufacture those in the form of poker, I think is where there's enough where it actually stings. If you lose, I think is probably good for some people okay so poker is one example anything else in terms of mindset shift yeah is there anything that you have changed yourself personally since you know when you were 20 years old to today that has been most valuable i mean if you take those personality tests like the myers briggs right um i'm very strong on the n and the t but i got more from int p to entj um okay give us some cluster of adjectives that describe those two things. Okay, so it basically means like I've gotten like a little bit more extroverted in my external life and a little bit more willing to trust my intuition.
1:15:50And the reason for the latter is that, and there's a lot about this in the book, your intuition can be very valuable when you have a lot of experience and you have implicit data that like it's hard to quantify in a model, right? But if you've played thousands of hands of poker, then you could just tell sometimes when somebody has or they don't, right? You could probably quantify it and say, okay, well, when you see this heart beating here or you see the way they put chips in the pot or, you know, but it's usually more subtle than that. It's like kind of like a semantic cluster of variables. So, like, when you have a lot of experience and you're still, as you get, you know, I'm 46 now, if you're still, like, very intellectually and mentally active and still exploring life when you're 46, then I think, like, life experience becomes, like, more important.
1:16:31It seems right now that certainly a lot of the media and anyone involved in politics and arguably extend that out to the wider world. Everyone's on tilt. Yeah. I mean, OK, yes, the election is coming up and so on. But for those who don't know, tilt is the word poker players use to describe that, like an emotionally heightened state where you're typically making bad decisions. Because everything's just so intense and you're either angry or you're upset about something and you're not thinking clearly or rationally. Uh, so yeah, I think it's pretty accurate to say that the media is on tilt. Do you have any tips for those or like messages you would like to give to those who you think have a lot of influence over the media, um, of how to reduce that from your own experience?
1:17:20Yeah. I just say like, don't let the haters get you down. Um, especially when we're kind of going back to like more of a sub stacky and content creator model where being an independent voice can be both creatively fulfilling and often a good business model. There are a lot of people that got yelled at by pandemic era Twitter that have survived and done fairly well. I do think, by the way, the pandemic itself is part of why we have this epidemic of tilt. If you'd ask me to predict, what'll happen if you tell people to be really afraid of being around other people for a year and all these institutions that create, you know, social enjoyment are shut down.
1:18:01You think people might just have like some long-term emotional damage from that and overcompensate and so, I mean, you know, when you saw Vegas bursting back to life once people felt, you know, not guilty about traveling again, like that seemed like an important moment. So I think COVID is going to have some long-term consequences, especially people in that like, kind of that were in like the age 14 to age 20 when covid peaked when it's like right in your formative coming of age years you know unfortunately we'll probably have some cohort data that will let us quantify that down the road but i think it's going to be tough on that generation because like i remember when i was 17 all i wanted to do was be hanging out with my friends and socializing you're in like search mode right you're you're search and explore that's what young adults want to do they want to expand their horizons and meet new friends and go out and have novel experiences and if you for two years can't do any of that during that very formative time I don't know I just can't I would have gone insane so yeah it's it's a lot of sympathy for the kids that got to miss out on that I guess again it's the bifurcation I expect some will be trying to like massively overcompensate for that and like try and make up for it and then others just became very very fearful like as a poker player usually how you get off tilt is also by um remembering what you've learned with a higher certainty focusing on the process not not worry about the current result etc right so that goes in line with the don't focus on the haters like just like um rely on the things that you know to work maybe in journalism it's like good old journalistic practices yeah i know if if i uh so this year play the world series but there's a lot of political news right and so i just don't have my full bandwidth when i'm at the table and in some cases probably plus it'd be for me to like totally punt and go write a blog post and get you know if you get x subscribers it outweighs the expected value of your stack and things like that um but when you're uh when you're not at your best then remembering kind of the abcs right so i'd actually play like more my impression of what gto play would be when i'm tired which means i'll like randomize more i'm like i don't trust myself in my current fatigued state to read somebody well where i can have any advantage from that so i'm going to look at the clock and oh this is a fold this time right and you get chill in the bluff or whatever and like whatever um you know when people are in there's in the book i talk people are like astronauts and mountain climbers who take physical risks as well and they're like yeah um just don't try to be a hero when you're under duress if you can remember your training and do the abcs and you'll be ahead of 95 of the population yeah i feel like similarly it also relates to what we previously talked about that fauci etc where using the gaslighting was basically kind of seems to me like an exploitative strategy rather than the very straightforward one and you shouldn't be exploitative when you're not performing well if the landscape is on tilt exploit less just go back to the abcs i think is pretty good define what you mean by exploit less so exploit and poker means basically notice what the error is that someone else has and try to adjust your strategy such that you gain from that error a bit more but whenever you do that you open yourself up to having been noticed to having adjusted away from the kind of optimal strategy.
1:21:25And then you are yourself now prone to be exploited. And then it becomes this cat and mouse game, basically, of who thinks one level ahead. But the problem is you can't really play the cat and mouse game well if you're not at your sharpest in the moment, which is what we discussed with the tilt question. For people to understand that would go a long way. Because, I mean, that's a harder concept. Like in the book, there's a lot about expected value. and like that you can kind of like explain like a mainstream podcast right um the game theory stuff is a little bit harder even though in some ways it's kind of like more important to the book but the notion that like if i'm kind of cheating the system and taking advantage of people i have like a little bit of fear in the back of my head that i'll get taken advantage of myself and the system will adjust and adapt like that i think is actually a pretty good heuristic that travels well to lots of things in life but people don't very few people like actually internalize that unless they like actually have like played poker you end the book on talking about sort of three maxims that you believe the world needs to incorporate more or at least move towards um and i love them because they're so incredibly win-winny you have that people should be looking to maximize their agency so their choice their plurality and then reciprocity can you explain what those words essentially mean to you and why you chose those?
1:22:47So agency to me, it kind of comes out of like the French revolution slogan, liberté, egalité, fraternité. You know, the book goes to this whole thing, how if AI is the equivalent to the Industrial Revolution, we also had the French Revolution and the American Revolution then and the Enlightenment, a change in philosophy. So the analog to liberty is agency, which means having robust choices that you can make, right? I mean, a lot of times online you're filling out some form and there's some opt out, but like it's really hard to find. Right. Technically, you have the choice, but like do you have agency there and kind of more broadly, do you have the power in a non-coercive way to shape your own life and make and make rational choices?
1:23:30because I worry, like I said before, that like the super capable people who are healthy mentally and physically, right, and have some means and have the right amount of cynicism and skepticism, but like are not pilled, like they do really well, but maybe that's bad for like 95 % of people. So I want to make sure that like we think about, you know, just having nominal choices is not sufficient anymore. Right. And also technology is getting better and better at removing people's agency. For sure. And not all, but some technologies in terms of you take, it's much as algorithms, for example, become more personalized and therefore better at achieving their objective function, which is, for example, in social media, keeping people scrolling.
1:24:18Over time, that's going to, as it learns more about you, even the most high agency people are increasing you know the the if you rank everyone on the on a sort of a spectrum of the lowest agency to the highest agency people that water line is going up and up of people who are able to keep their head above the the addiction parapet essentially or above the above the tide um so it sort of goes both ways people themselves need to work on finding ways to improve their own agency but also those who are in power for example the reverians who are building technologies are not building stuff that removes people's agency.
1:24:56Yeah, I think to be pretty strongly against paternalism. You know, when Google Gemini had the phase where it was like drawing like multiracial Nazis, for example, I mean, obviously Google was embarrassed by that. But the notion that like, we're going to coercively insert some particular notion of social justice into information that's supposed to be, you know, don't be evil, don't manipulate people, Like that seems like that seems quite bad. Right. That's kind of what the whole woke thing is. Right. It's about like, oh, these things it's about deeming what is safe and what isn't safe. And this is harmful and this isn't.
1:25:32And being terrified of anything that could be interpreted as harmful, particularly to a protected class. But to the point where it just like it's overfitting for everything. Yeah. And it's risk averse. Right. And and neurotic. and let people make choices, but make sure they're well-informed choices. So what's plurality? That's maybe the most straightforward one. I don't think we want any one faction to dominate. This comes out of an idea from Nick Bostrom, who is the EA-adjacent philosopher at Oxford, who has an idea for a moral parliament. So he's accused of being a utilitarian, right? And he said, actually, I'm not.
1:26:12I would want to have a moral parliament where the utilitarians have some seats and maybe the libertarians have some seats and you know classical conservatives or liberals have a say too i thought it was a really kind of beautiful idea um but also in general i mean you know we are facing you know if you're a verian you should like pluralistic decision making mechanisms like the market economy for example um or democracy i think um i worry that what if even even with ai or with or without ai either way um like what if somebody just gets like 50 % plus one of the power and the say in the world. Like what if in China, the government just gets really good at permanently suppressing political dissent?
1:26:57It might not be in its political interest to do that, but let's say it just gets really good at like, actually, we are now good enough to like, to win this battle. And you have this kind of dystopian, not that China's dystopian, but like Russia or something, right? It might be kind of dystopian. Then like, that seems potentially really bad. And also a lesson from any gambler, especially in sports betting, knows that you want consensus when you're making a bet. If one model says one thing, the other says the other, and you ever come together, if several sources point in the same direction or you kick the tires on the idea in different ways and it's robust to that, then that's very valuable.
1:27:30It's trying to incorporate the idea that you want to keep a system as complex as possible and diverse in the true meaning of diversity, not in the woke meaning, but like actual diverse opinions and groups and make the system as interesting as possible and not become, you know, collapse down into a simplified monolith. No, and by the way, I do think that Silicon Valley could do a lot better on like classical D diversity and would probably contribute to intellectual diversity too for what it's worth. Yeah. Okay, and then the third one is reciprocity. Which is kind of the most nerdy one of all. It comes directly from game theory, the notion that like not treating other people like NPCs, assuming they can adapt and be intelligent, but also like treat others how you would want to be treated, right?
1:28:16So with dignity and respect, although reciprocity also means being able to reciprocate at times, you know, I think it's important on the internet if people have repeatedly demonstrated that they're behaving in bad faith and disengaging from them or punching back as a deterrent, I think is our important concepts. But yeah, it's, you know, it kind of means that we're this together. That's kind of where the fraternity part comes from, is that we're all in this together in some ways. You know, the lesson of the prisoner's dilemma is that if we don't trust one another, we get worse outcomes collectively.
1:28:49There's a lot more about that in the book. When you have a loss of trust, the world becomes much more zero-sum, and that's a big problem. Yeah, at the same time, if you just were to press cooperate every time in the prisoner's dilemma, probably you'll be taking advantage of. So it's kind of the mixture of tit for tat, but start with cooperation. Yeah, people don't understand. I mean, again, the village don't understand how like if you give people the benefit of the doubt too much, then you like will be exploited in a world of 8 billion people that like people will find ways to take the expertise in your field and exploit it for their own project or for their own influence or political gain.
1:29:25I mean, it will happen if you don't have like adequate defense mechanisms. It's acknowledging the fact that competitive dynamics exist. You know, it's not so pie in the sky that, oh, no, everyone, if we're just perfectly tolerant of everyone, then everything will be nicely nice. It's like, no, there are psychopaths out there. There are people who try to exploit others. So you need to have some degree of incentive mechanisms such that you can punish them so that they don't take advantage of you, while at the same time rewarding those who do cooperate and or do use competition in a healthy way. Yeah, in some ways it's actually kind of quite Kantian, the categorical imperative.
1:30:02Like, if you universalize this behavior, then what's the equilibrium that results, right? You know, if you're always, I mean, Tyler Cowen, the economist, is always like, solve for the equilibrium is like his phrase, which I think is like a really, really good heuristic, right? Am I in a short-term exploitive situation where the equilibrium does not matter or in a repeated game where it does? And then what's the equilibrium that results? I mean, even in things like you know, like a relationship with a partner or, um, or with children or with your parents, right? Like, you know, you have to make decisions a lot of the time about like, am I going to let this behavior that I don't like in my partner go or not?
1:30:44And you have to sometimes, I think, be willing for there to be consequences. You know what I mean? That, no, I mean, you said this mean thing to me. And so I'm not going to go out to dinner with you now. I'm going to cancel my plan. I mean, like probably in some sense, I don't, people don't like to think about that, but I think we kind of do naturally anyway. But I think it's always worth thinking about. Because I'm somewhat not a fan of Kant's original formulation, I just wanted to pick on that. I think saying the treated, like what's the equilibrium results gives Kant more credit. Like his original writing was more about is it logically possible for there to be a world with that particular moral framework and if nature doesn't permit it, then he was against it.
1:31:30It was more like a kind of existence possibility of it where everyone wanting to be first, it's not possible for everyone to be first in something. So Kant would be against that desire, for example, as well. But I think the current notion that we have of the categorical imperative is actually much better. And the version that you described is how we nowadays treat it. Cool. I did not know that. Thank you. So he's, yeah. Final question. What's one thing that you think is obviously win-win that the world is missing out on and needs more of? I mean, maybe it's a very generic answer that's not novel at all, right?
1:32:14But I wish people knew how much technological growth has improved the human condition. um like people don't know how many more people were living in poverty in india 50 years ago and they don't know that until this idea of liberalism um not meaning left but meaning like the liberal movement that emerges out of the enlightenment um how we didn't have like progress or growth for the entirety of human civilization until about you know 1776 1800 or so right and then ever since then you have an inflection point and you have progress in life expectancy, progress in curing disease, progress in expanding freedom ever since.
1:32:57So that is one lesson I hope doesn't get lost in the book. Yeah, the idea that because someone else won and maybe has even gotten a bunch of spoils from creating a technology doesn't mean they've taken it away from someone else. They may have actually created, increased the size of the pie. Right, or you increase the size enough where even if there's some unfairness that like and by the way part of what made liberalism work is idea of like human dignity initially only properly extended to like white men who own property which is a gigantic problem obviously but like the franchise has expanded gradually um and also a social safety net where um you know the optimum level of risk taking is if you want people to take risks especially in terms of like the market economy then you don't want them to like permanently be out of the market and bust their bankroll the first time they make a mistake or a product doesn't work out.
1:33:51And so having like a welfare state is actually quite optimal, even from a capitalist perspective, as well as from kind of a humanistic perspective. I'd love to just end, given you are Mr. Predictions, with a series of rapid fire predictions. As a percentage. Okay. Just, it doesn't have to be, I mean, try and be as system one intuitive as you can be um okay likelihood that kamala wins the election 57 likelihood that neither trump nor kamala win the election one percent likelihood that tick tock gets removed from the app store in the US by the end of 2025?
1:34:4025%. Likelihood that COVID was a lab leak? 76%. Spicy. Likelihood that China invades Taiwan by the end of 2026?
1:34:5811%. Likelihood that Epstein killed himself? Oh, that he did.
1:35:0860%. That he did. Yeah. Nate, thank you so much for coming on. Thank you, Liv. Thank you, Igor.
From the publisher
Can we still accurately model elections in such chaotic times? Are prediction markets the future of news? Nate Silver thinks so - Nate is a renowned election analyst, author and former professional poker player. He's the founder of FiveThirtyEight, whose statistical models revolutionized election forecasting, earning him national acclaim. His two books "On The Edge: The Art of Risking Everything." and "Signal in Noise" are inspirations for today's Win-Win conversation with Liv and Igor. We discuss polling accuracy, the importance of prediction markets like Polymarket, poker thinking, solutions to political polarization, and of course his latest predictions on Trump vs Kamala. We also hear his theory on "The River" and "The Village" communities, defined by their opposing perspectives on risk - and how these contrasting worldviews shape approaches to everything from public health policy to technology. Chapters
00:01:34 - Predicting Elections
00:06:49 - Trump Assassination Attempt
00:11:45 - Prediction Markets
00:21:13 - Nate’s New Book on Risk
00:25:53 - Institutional screwups on COVID
00:33:30 - Why are People so Averse to Probabilities?
00:35:27 - Silicon Valley’s Blind Spots
00:40:43 - Excessively Risky Behavior
00:44:29 - Regulations
00:48:55 - Finding Common Ground
01:00:18 - Alternative Voting Structures
01:06:50 - Signal vs Noise in the AI age
01:12:15 - Advice for Sharpening Your Models
01:22:25 - Nate’s Maxims For A Win-Win Future
Links:
♾️ Nate’s Blog: https://www.natesilver.net/
♾️ Nate’s Twitter: https://x.com/NateSilver538/
Credits:
♾️ Hosted and Produced by Liv Boeree and Igor Kurganov
♾️ Post-Production by Ryan Kessler
The Win-Win Podcast:
Poker champion Liv Boeree takes to the interview chair to tease apart the complexities of one of the most fundamental parts of human nature: competition. Liv is joined by top philosophers, gamers, artists, technologists, CEOs, scientists, athletes and more to understand how competition manifests in their world, and how to change seemingly win-lose games into Win-Wins.

