The Prop-Betification of Everything, with the Forefather of Prediction Markets

Summary

Podcast Summary: “The Prop-Betification of Everything, with the Forefather of Prediction Markets”

Podcast: Pablo Torre Finds Out
Host: Pablo Torre (The Athletic)
Guest: James (“Jim”) Surowiecki (author of The Wisdom of Crowds)
Date: February 3, 2026
Main Theme:
A deep exploration into the explosive rise of legal prediction markets, the “prop-betification” of all aspects of life, and the philosophical and ethical consequences of turning every difference of opinion into tradable assets—with special insight from Jim Surowiecki, the intellectual foundation for the modern prediction market.

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1. Opening and Main Premise

• Overview:
  Pablo Torre investigates how the concept of “the wisdom of crowds” has evolved from an academic idea into the rapidly expanding world of online prediction markets, touching everything from sports to geopolitics, elections, and even public safety. Pablo's guest, Jim Surowiecki, wrote the book (The Wisdom of Crowds) that prediction market platforms now regularly cite as justification for their models. Together, they assess how this vision is playing out in reality: is it actually making society more rational, or just turning life into one giant casino?

“What I would say is almost the prop-betification of everything.”
— Pablo Torre [04:25]

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2. Key Discussion Points & Insights

Who is Jim Surowiecki, and Why Prediction Markets?

• Background:
  • Surowiecki is an acclaimed financial journalist and author who has taught at Yale and contributed to The New Yorker.
  • He was once top 100 in the world at EA Sports NHL video game. Pablo draws a metaphor between his gaming “relic” status and the evolution of prediction market ideas slipping beyond his original control.

The Origin of the Wisdom of Crowds & Prediction Markets

• Crowdsourcing Knowledge:
  • Surowiecki explains the “wisdom of crowds” — under the right conditions, group judgments can outperform the smartest person in the group.
  • Classic “jelly bean jar” example: group averages are remarkably accurate if independent, diverse, and informed [10:32].
• Original Vision for Prediction Markets:
  • Early 2000s: only play-money or small academic markets existed.
  • Surowiecki envisioned them primarily as organizational or governmental tools for better decision-making — not betting platforms.
  • “What took so long?”: A delay of more than 15 years before prediction markets exploded into popularity [04:30–06:15].

“The fact that I did not trademark the phrase the wisdom of crowds is one of the great terrible financial decisions in a lifetime of bad financial decisions.”
— Jim Surowiecki [04:32]

The Boom: From Sports to “Everything Is Bettable”

• Prop-Bet Explosion:
  • Companies like Polymarket and Kalshi are now billion-dollar valuation platforms.
  • Modern prediction markets started as a new way to forecast, but are now dominated (93%+) by sports bets [12:44–13:02].
• What makes prediction markets different than sportsbooks?
  • Exchanges match buyers and sellers; platforms themselves don’t “lose” money when an expert wins, unlike traditional sportsbooks [18:07–19:23].
  • This creates a haven for highly skilled bettors who would be banned from regular sportsbooks.
• Regulatory Loopholes & Risks:
  • Platforms claim to offer “event contracts,” arguing it’s not technically gambling, avoiding state-level regulations and being policed by the federal CFTC instead [13:34–15:54].
  • States like Massachusetts are pushing back, but the platforms have found success exploiting regulatory ambiguity.

Ethical and Practical Pitfalls

• Insider Information & Manipulation:
  • The logic of prediction markets means insiders can profit from non-public knowledge—e.g., a Polymarket trader who bet on the U.S. seizing Maduro in Venezuela just before the news broke, walking away with $400,000 [38:10–38:28].
  • There's little stopping well-placed insiders, including politicians or their associates, from profiting—exacerbated by figures like Donald Trump Jr. acting as major investors/advisors [36:54].
• Prop Bets as Incentives for Action:
  • High-profile, bettable events (Caroline Levitt’s press briefing ending right before the 65-minute mark) suggest real-world behavior can be changed to benefit bettors or participants [09:34, 39:48–41:10].
• Manipulation vs. Market Correction:
  • Attempts to buy legitimacy (e.g., massive Romney bets in 2012) don’t always alter outcomes; robust markets correct quickly—yet small, thinly-traded markets are more easily manipulated [50:03–51:28].
• Transparency vs. Alienation:
  • The shift from informative, serious markets to meme-like, highly gamified content risks alienating the public and reinforcing “hustle culture” [45:15–45:59].

Markets versus Polls

• Key Distinction:
  • Polls ask “what will you do?”, while prediction markets and specialized polls (“neighbor polls”) ask “what do you think will happen?” [32:08–34:54].
  • Financial or reputational stakes tend to incentivize more thoughtful judgment, but money isn’t strictly necessary for prediction accuracy in internal markets.

Societal Consequences & The “Financialization of Everything”

• Capitalizing on Uncertainty:
  • The vision, as stated by Kalshi’s CEO: “The long term vision is to financialize everything and create a tradable asset out of any difference in opinion” [43:51, 44:04].
  • Surowiecki worries this is a recipe for a society obsessed with side hustles, losing any sense of intrinsic motivation.
• Legitimizing Outcomes:
  • Large bets can set public expectations or even create momentum for events (“Markets that authorize reality” — Kyla Scanlon, NYT, quoted at [47:05–47:44]).
• Paradox:
  • The accuracy and integrity of prediction markets depend on crowds being large, diverse, and independent—a paradox since skepticism grows as the stakes get higher.

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3. Notable Quotes and Memorable Moments

| Timestamp | Quote/Description | Speaker | |-----------|------------------|---------| | 04:32 | “The fact that I did not trademark the phrase the wisdom of crowds is one of the great terrible financial decisions in a lifetime of bad financial decisions.” | Jim Surowiecki | | 09:48 | “If all of this just feels apocalyptic to you, I get it. But what I wanted to do here was understand how we got to this point and maybe even predict where we’re going.” | Pablo Torre | | 18:55 | “Someone else who took the opposite side of the bet, sold you the contract, losing the money... So they have nothing at stake in the outcome.” | Pablo Torre/Jim Surowiecki | | 29:04 | “The idea of a federal betting parlor on atrocities and terrorism is ridiculous and it’s grotesque. It’s a bizarre plan.” — quoting Senator Ron Wyden on the DARPA prediction market scandal | Pablo Torre/quote | | 36:32 | “We’re all living inside of a casino in which everything is bettable.” | Pablo Torre | | 44:04 | “The long term vision is to financialize everything and create a tradable asset out of any difference in opinion.” — quoting Kalshi CEO | Surowiecki/quote | | 52:51 | “If you’re not sure that you’re not the sucker, you are probably the sucker.” | Jim Surowiecki | | 52:56 | “It’s the Rounders quote. If you can’t spot the sucker in your first half hour at the table, then you are the sucker.” | Pablo Torre | | 53:18 | “What I actually found out is that Jim Surowiecki, the intellectual forefather of the thing that is eating our country, has made $0.00, it seems, on the thing that he accidentally created.” | Pablo Torre |

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4. Timestamps for Major Segments

• Introduction & Jim’s Background – [01:53–04:32]
• The Birth of Crowdsourcing and Early Prediction Markets – [04:32–10:32]
• Sports and The Dominance of Prop Bets – [12:44–17:33]
• How Prediction Market Platforms Work – [18:07–19:23]
• Government and Prediction Market Controversies (DARPA, Insider Info, Regulation) – [24:31–32:08]
• Polling vs. Prediction Markets, Incentive Structures – [32:08–36:54]
• Markets Influencing Reality, Manipulation, Legitimacy and Trust – [36:54–48:09]
• Concerns, Cultural Fatigue, and Unintended Consequences – [43:51–46:39]
• Power Imbalances & Is This Healthy for Society? – [47:05–52:51]
• Final Reflections, “Are you the sucker?” – [52:51–53:46]

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5. Tone & Style

Throughout, Pablo mixes skepticism with curiosity, and Surowiecki brings measured academic caution with self-deprecating humor about his lack of financial benefit from his idea’s spread. The conversation is candid, lively, and deeply engaging, with plenty of side-eye at both the exuberant marketing of these platforms and the ethical gray area surrounding their operation.

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In Summary

This episode offers a comprehensive, accessible exploration of how prediction markets have permeated modern life, turning almost everything into a potential bet. It shines a light on both their promise—aggregating valuable knowledge—and their perils—insider trading, market manipulation, and the erosion of trust in pursuit of profit. Surowiecki’s nuanced take, paired with Pablo’s pointed questions, reveals that the wisdom of crowds can be powerful, but not without significant risk and ambiguity in a world where “practically everything is now a prop bet.”

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Recommended Listening:
For anyone concerned about the intersection of gambling, finance, politics, and the creeping encroachment of markets into our daily sense of reality—or just anyone who wonders whether we are all, unwittingly, suckers at the new national table.

Transcript

[A]

Welcome to Pablo Torre Finds Out. I am Pablo Toure and today we're going to find out what this sound is.

[B]

The long term vision is to financialize everything and create a tradable asset out.

[A]

Of any difference in opinion right after the set.

[C]

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[A]

By the way, are you what is your NHL 26?

[B]

I don't play anymore because you don't play anymore. I don't because when the new the next generation consoles came out, EA for some reason decided to only make the NHL game for the new consoles and I just never. I haven't bought a new console just because I don't play enough.

[A]

What was the last console you owned?

[B]

The Xbox One was The last one.

[A]

They left you behind in an outmoded technology.

[B]

Yes. And so I have not played the game in two years.

[A]

Wait a minute. But the legend of you. The reason I wanted to start with this is because the legend of Gem zero Wiki is not. Not that he used to write the financial page for the New Yorker, worked is at Yale lecturing and all this.

[B]

Yeah.

[A]

It's that you were at your peak. What rank in the world when it comes to the NHL video game?

[B]

I can't remember exactly, but I think my Highest was like 92, something like that.

[A]

That's ridiculous.

[B]

Top 100.

[A]

That's ridiculous.

[B]

I don't think Megan knows that. That's actually.

[A]

God bless your partner, Megan, who is learning the depths.

[B]

That's. That's. That's not going to be a good thing. That's not good for anyone. That's not good for anyone.

[A]

But there is is a bit of a metaphor here already. Insofar as you're a person who is steeped, it seems, in what was a version of a technology, of a concept and you're sort of like watching this thing that you're as intimately familiar with as anybody now zoom into a future that I'm trying to also understand. Yeah. And look, the prediction markets dynamic that I need our audience to understand and that I personally frankly need to understand better. The reason you're on this show is because I was looking through Polymarket's website. Okay. There's a section labeled FAQs, frequently asked questions. And it says Polymarket versus polling. And the subhead is how is Polymarket better than traditional legacy polling? And I'll just read this paragraph. Studies show that prediction markets like polymarket tend to outperform traditional pollsters because participants are financially incentivized to be correct. This creates more thoughtful data driven predictions. Research by James Surowiecki, author of the Wisdom of Crowds, has highlighted how markets like these can be more accurate than polls due to the collective intelligence of diverse participants. My point is that the book that I had to read in college that you wrote, the Wisdom of Crowds, it's kind of the foundational text for the thing that is taking over not just gambling as a concept, but like now, politics and finance and the. What I would say is almost the prop. Bedification of everything.

[B]

Yeah.

[A]

How does that feel?

[B]

The fact that I did not trademark the phrase the wisdom of crowds is one of the great terrible financial decisions in a lifetime of bad financial decisions. I think. No, it's. It's the thing that strikes me first of all is, is kind of what took so long. So the Wisdom of Crowds came out in 2004.

[A]

It was on my Intro to Sociology s syllabus as it is, I think at fine colleges everywhere.

[B]

Yeah, there were already a couple of prediction markets that had, that had already been created at that point. They were smaller. One of them was a play money market, not a real money market. And even the phrase prediction markets was kind of just being formed. I mean, if you read the book, the phrase I use in a lot of it is decision markets. Because a lot of what I was interested in was how you could use these markets to help make better decisions within companies or within governments or whatever. But there was a lot of interest around prediction markets in the 2000s. There's a huge amount. If you go to like 2008, there's this famous open letter that was signed by like 22 of the most really important economists and social scientists in the world. Included like five Nobel or four Nobel laureates. Basically making the case for prediction markets as a tool that people should be using. But it took like more than 15 years after that for it to take off. So part of me is just like, yeah, what took so long? The second thing is I am very happy that this idea is gaining currency and is, you know, kind of becoming more and more popular and people are interested in it. But I do think a lot of the rhetoric around these markets is challenging and I think is kind of alienating people in a way that I think probably is not beneficial.

[A]

Yeah, I want to talk about all of this, but I also want to just underscore here that you are one of the sharpest thinkers on finance in America and you had none of the cunning or the strategy. None to profit off of this thing. You were decades early on.

[B]

None. None at all. None at all.

[A]

Poly markets quoting you and they're eating the world. Kalshi, which is by the way Arabic turns out for everything.

[B]

Yes.

[A]

Is also eating everything. Everything.

[B]

Yes.

[A]

And you're here with me just chatting. Just, just, just chatting about your EA Sports NHL career.

[B]

I say, can I give you an example? The moment where I really was struck by this was Truth Social, in a.

[C]

Major move in the crypto and social media space, is entering the world of online betting with its new product Truth.

[A]

Predict, which is aimed at prediction markets.

[C]

For politics, sports and more importantly, crypto.

[A]

Why it matters.

[C]

Prediction markets like these in aim to harness the wisdom of the crowd in forecasting.

[B]

Devin Nunez, the former congressman who is.

[A]

Now CEO, Truth Predict is. Is that what it's Called is what's called.

[B]

Yeah. So he's the CEO of, of Truth Social. And I didn't know that in his statement introducing this, he actually said, you know, it will. I can't remember the exact quote, but it was basically, it will allow us to tap the wisdom of the crowd. And I was like, oh, my God. Anyway, but it happens all the time, so. And I'm very happy.

[A]

The first line of the CBS News story, Poly Market CEO Shane Coplin is betting on the wisdom of crowds.

[B]

Exactly.

[A]

New York Times article. Again, the wisdom of crowds. Bloomberg K's analysis of prices during the NYC mayoral race doesn't back up the promise that prediction markets will aggregate the wisdom of crowds with greater accuracy and precision. It's just, it's. Yes, you are being plagiarized. You just have no legal mechanism to enforce.

[B]

And it's fine. I mean, I, whatever. I wrote the book so people would take the idea seriously and embrace them. And that's what's happened. So it's good, but it is funny nonetheless, just to, like, watch it happening.

[A]

So there is way too much happening right now. And reality itself has never been more contested, which is, you know, a hell of a combination. We're watching the federal government killing American citizens in Minnesota while millions of new Epstein files are finally getting released. And also the most watched television show in America is happening on Sunday, Super Bowl 60, Seahawks, Patriots. And now, thanks to the rise of legal prediction markets, there's a way to bet on all of this as if everything suddenly is sports betting. Which explains why prediction market companies like Polymarket and Kalshi are each worth tens of billions of dollars, apparently, while promising a better way to forecast this reality and actually predict what's going to happen next. Is the United States going to invade Venezuela?

[B]

Yes.

[A]

Or will Caroline Levitt, the White House press secretary, will her press briefing last 65 minutes?

[C]

And thank you all very much. It's great to be back with you.

[A]

And very conspicuously. And this speaks to the whole, like, what the is really happening here dynamic. She left the room seconds before the press briefing hit 65 minutes.

[B]

Yes.

[A]

And so if all of this just feels apocalyptic to you, I get it. But what I wanted to do here was understand how we got to this point and maybe even predict where we're going. So I did something that is increasingly unpopular in the world of prediction markets. I turned to an expert, my friend Jim Surowiecki, an enormous sports fan and brilliant financial writer who authored the Wisdom of Crowds, the book whose legacy has now reached into all of our pockets, literally and figuratively, while leaving one of the, you know, top 100 EA Sports NHL players in the world behind.

[B]

So the central thesis of it is that under the right conditions, groups of people can be remarkably intelligent and actually even smarter than the smartest person in the crowd. The simple example of it would be something like the jelly bean experiment. So there's this famous experiment that was done in the 80s by a finance professor named Jack Traynor at Columbia Business School. And what he would do in this finance class was he would just show his students a jar of jelly beans and just ask them to guess how many jelly beans were in the jar. And what he found consistently was that the group's average guess was always very good. So it was typically within, like, about 2% of the number of beans in the jar. And the guess was better than all but one person in the room. So that's the basic premise, and it's an idea, I think, that really underlies markets generally and that you've seen in operations, operation in other places. But a couple things. One is the key phrase in that definition is, like, under the right conditions. So what does it take? Because obviously there are tons of examples everybody can think of where markets are terrible, they have bubbles, or look at meme stocks or whatever it is. And so my argument was that you need diversity of information and opinion. People who have lots of different ideas, lots of different pieces of information they're drawing on. And you need them to be, relatively speaking, like, independent of each other, so they can be influenced to some degree. Like they can see the price or whatever it is, but they're not necessarily following each other the way you sometimes get in markets. And the idea is that if you have those things and then you have a mechanism to kind of aggregate all that information and all that knowledge, then you oftentimes can arrive at these just, like, amazing judgments. But prediction markets was a kind of new and I thought sort of interesting way to try to tap the knowledge. But, like, another example is obviously sports betting, right? Sports betting, whether it be the odds on horses at the racetrack, or in a slightly more complicated way, the point spread, that actually generally reflects the collective wisdom of all bettors as well. So these were all different ways of thinking about, like, how can you tap the wisdom of a large group of people?

[A]

But it is interesting as you look at, okay, what are people actually using Polymarket and Kalshi for? Yeah, the answer is more than 90% sports.

[B]

Yeah.

[A]

Last week there was a new record for trading volume on Sunday, $543 million. 93% was sports trading volume.

[B]

That's right.

[A]

And that was on Kalshi. And so the notion that all of this is another way to bet on sports. Yeah, it seems hard to escape that. Yes. The way that you envisioned the prediction market had these socio political functions, but in reality it's a bunch of dudes doing the thing that they were doing on FanDuel and Drafties and everything else.

[B]

Yeah.

[A]

But in this way they're doing it because it's less regulated, I guess.

[B]

So the regulation question is really interesting. What these markets have, prediction markets have done when it comes to sports betting, I think it's fair to say is they have followed a strategy somewhat similar to Uber and Airbnb, which is kind of we're going to do it and then you can try to stop us. Basically the way sports betting is regulated in the United States is it's primarily regulated at the state level. So there are some states in America even today where you can't bet on sports. So what the prediction markets have done is they have basically said what we are offering is not gambling in the strictest sense. We are offering these, what they call event contracts. And an event contract is a contract where you are betting on the outcome of an event. I just said betting, maybe speculating, whatever you want to call it, the outcome of an event.

[A]

The head of the needle. They're trying to dance.

[B]

Yes, exactly. And as a result, we are regulated at the federal level, the national level, by the Commodities Futures and Trading Commission. Right. And the Commodities Future and Trading Commission has this weird provision where if you're a recognized exchange and Kalshi is, and polymarket now is, you've provided evidence that you're reliable and you're not going to go under and leave everyone hanging and you can facilitate trades in an efficient way and all this kind of stuff. Right. If you do that, you can self certify that you're going to offer these event contracts and then basically the CFTC has to step in after you do that and say no, no, no, you can't. And if they don't step in, then they basically have kind of. It's almost as if they've given you tacit approval effectively. And so that basically is what they've done. The Biden CFTC tried to stop Kalshi from offering event contracts in elections and Kalshi won a court case. They basically got a stay and they basically said you can keep offering them, you can offer them for the 2024 election, which they did. Trump won. And its CFTC has been far friendlier to prediction markets than Biden's.

[A]

Was crypto and these other gamified casino in your pocket genre of stuff.

[B]

But on the state level, states are stepping in and have tried to step in and say like, no, you can't do this. The most successful state is Massachusetts, which just won. And the reason that decision was important was because that decision basically said regulating gambling is a state power and Congress never meant to take away that power.

[A]

Yeah, I mean, that was just last week.

[B]

The state attorney general accuses this site of offering sports betting without getting a license.

[A]

And while Kalshee is facing legal action.

[B]

From other states, Massachusetts is the first.

[A]

To actually stop operations. It's expected to appeal. This is what the Suffolk County Superior Court Judge Christopher Barry Smith in Boston said, quote, there is no real question that licensure and the consequent oversight of sports waging operations in the state serves both public health and safety and the commonwealth's financial interest. And so this was the latest development in what feels like an attempt to curb what has been this unstoppable, gravitational almost force.

[B]

Yeah. But I think when it comes to today and it comes to where prediction markets have gone, I think the main reason prediction markets have embraced sports betting is because that's where the money is. That's the main reason they are there. It's a logical place for them to go. Prediction markets are really well suited to forecasting sporting events, the outcome of sporting events. But I think the main reason is that it's just a much more stable and reliable form of revenue generation.

[A]

Right, right, right, right. And look, I've talked to now really high end sports betters, gamblers, and they love.

[B]

Yeah.

[A]

The prediction market.

[B]

Yeah.

[A]

Not least because on any sports book they get banned as soon as they demonstrate that they're any good at this. Yes, we've talked on this show before with her, all about Vulgaris, who is saying to everybody how insane it is that you could be truly blacklisted from doing the thing because they're gonna lose money by having you be a customer.

[B]

Exactly.

[A]

The moment you show an ability to win, you will be, you'll be limited.

[B]

And you'll be shown the door.

[A]

And so in this case, that is not a concern.

[B]

It's not a concern.

[A]

And can you explain just the basics.

[B]

Of why the nature of these exchanges is. They are what are called derivative exchanges. Right. So everything on these exchanges is structured as a contract. There is a buyer and there is a seller. So if you want to, let's Say right now and Kalshi, the Seahawks are favored to win the Super Bowl.

[A]

Yep. Right now it's 68 Seattle.

[B]

What the market is saying is there's a 68% chance to win. And what that means is if you want to buy that contract, you basically pay 68 cents. And if you win, you collect a dollar. Right. You make 32 cents, about 50% on your investment.

[A]

Roughly. Right.

[B]

But when you do that, someone has to be on the other end of the trade. Right. There isn't a house in the same way as if you go to DraftKings. When you make that deal, DraftKings is on the other end of the deal. That's not the case in these prediction markets.

[A]

So the premise then, just to spell it out, is the operator, yeah, polymarket doesn't give a shit if you're good at this because they're not actually losing the money.

[B]

Exactly.

[A]

Someone else who took the opposite side of the bet, sold you the contract, losing the money.

[B]

That's who's liable, that's who it is. So they have nothing at stake in the outcome. Right. Now, in theory, if a sports book is doing its job really well, it shouldn't have that much at stake either. Right. Because it should be laying off its bets and it should also be adjusting the point spread so that it has, relatively speaking, an equal amount of money on both sides and then it just collects the Commission. Right. The 4.5% commission in the middle.

[A]

The vig.

[B]

Yeah, the vig. In practice, it's, it's harder to do that at a sports book. And so a lot of times you'll sometimes read like stories in ESPN where people at the sportsbooks are like, oh, we really lucked out when, you know, X, Y or Z happened because they had taken in too much money on one side of the bet. So that does happen. Polymarket, Kalshi, prediction markets generally, they don't in theory have to worry about that. So as a result, where sportsbooks do, it seems like online sportsbooks do pretty clearly ban very successful sports bettors. Every successful sports bettor I know has talked about this happening. It does not happen on Polymarket and Kelshi because in theory they don't care. Like, what difference does it make to them? They just want the volume and they just want people to be trading and people to be offering contracts or buying contracts. And so that's one reason, I think, why, you know, really successful or big betters are gravitating to these things.

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[A]

So in the wisdom of crowds, how big a section was prediction markets?

[B]

Prediction markets, as I said, like, to me, they were most interesting at that point as a kind of proof of concept. So there were not many prediction markets that were running at the times, but the ones that existed gave us pretty good evidence that under the right conditions, these things could be very valuable. And so that was really where I talked about them. And then there was this, like, really interesting, from my perspective and from other people's perspective, very sinister experiment that the US Intelligence community wanted to run involving prediction markets.

[A]

Wait, what? What was that?

[B]

So in 2003, the intelligence community started to set up a program that it called Future Map. And as part of it, it was going to set up this thing called the policy analysis market. And the idea behind this whole project was that they were going to set up two different kinds of prediction markets. So one of them were going to be internal prediction markets inside the intelligence community. These would be relatively small markets. They would probably be open to like 20 or 30 people. They'd be open to analysts, and they would ask questions that the intelligence community wanted answered. But they would be open to people who were maybe experts in the field, but also people who were maybe experts in adjacent fields. And the idea was there's maybe stuff people know that for whatever reason, because a bureaucracy or whatever it is, is not really getting to the decision makers. And so we want to try to see if we can use these markets to tap into that. And then the other one, and this was the one that that created the uproar, was going to be a market in Middle Eastern politics and economics. It was going to be open, in theory, to the public, and it was going to offer markets in things like assassinations. Well, it's not clear that that was ever actually on the table, but because I think originally what they had in mind were much more mundane things like what will happen to Jordan's GDP in the next two years, or how stable they would find some measure of stability for Syria's government, or how likely is it that the House of Saud will fall in the next five years or whatever it is. Right. And they would offer up these things, but when they set up the site, they included things like missile launches. And so people were like, oh, my God, they're asking us to bet on, you know, like, assassinations and terrorist attacks. Terrorist attacks and the, like, coup d'.

[A]

Etat.

[B]

Yeah, exactly. And so there was this, like, massive uproar. Two senators kind of said, look, this is a nightmare. How can you allow people to bet on this stuff? It's da, da, da, da.

[A]

Yeah. This is July 28, 2003.

[B]

Yeah.

[A]

So on that note, we have discovered something that is going on at the Department of Defense, a relatively small program run by Admiral Poindexter that is almost unbelievable. They believe that having the market system, people in the market system betting or.

[B]

Buying and selling futures contract, they will be contracts.

[A]

They will be able to develop information.

[B]

About what might or might not happen.

[A]

In the Middle east in the future. This betting power on the Internet will include wagers, for example, as the. The examples on the Internet site put up by the Department of Defense would include, will Mr. Arafat be assassinated? Will there be missile attacks from North Korea? Will the King of Jordan.

[B]

And then there was one other problem with it, which was that the guy who was sort of in charge of the. The whole sort of division that was going to be running this was John Poindexter, whose name doesn't really mean anything to people anymore, but he was seen as sort of this, like, dark lord of the intelligence community.

[A]

He was the head of the DARPA unit.

[B]

Yeah, he was the head of the.

[A]

DARPA unit, the Defense Advanced Research Projects Agency, which is darpa.

[B]

Is this, like, super cool, right? Or. Yeah, yeah, like investing in all these, like, really amazing technologies and. And actually quite good basic research and da, da, da, da. But Poindexter had been involved in, like, Iran Contra and all this stuff. So he was.

[A]

Perfect name also.

[B]

Yeah, Poindexter, everything about it. And then this was also, obviously, the Iraq War. And anyway, so it was all this, like, perfect storm of. This is a disaster. And so the senators came out and literally DARPA shut it down the next day.

[A]

This is Ron Wyden, the Senator of Oregon, saying the idea of a federal betting parlor on atrocities and terrorism is ridiculous and it's grotesque. It's a bizarre plan.

[B]

One of the things that bothered people about this was that the U.S. government was running it. The U.S. government is very interested in these questions. Right. The U.S. government wants to gain more information about this kind of stuff. And I honestly think a potential assassination or a missile launch, those are not things that one would expect prediction markets generally to be good at because they really depend on the knowledge and judgment of a few people, typically. Right. So the only hope you have of getting forecasts of those things. Right. Is if you have an insider trader who's like, I'm just going to leak this information and make a lot of money by doing it. Right.

[A]

Well, let's, let's talk about that, because what is the ideal prediction market topic?

[B]

Sports is actually a good prediction market topic because they're events that are in the future that have a clear outcome. So it's, you know, at some point the rubber is going to hit the road. You're either going to be right or wrong. Forecasting them well involves a lot of different moving parts and people have lots of different pieces of information about it. Some are relevant, some are not, some are misguided, some are not. But collectively, what usually happens is that the market arrives at a pretty good forecast of what's going to happen. Not in any sense like a perfect forecast, but over time, forecasts are usually pretty good. So in politics, I would say, or economics, I would say, similarly, bigger market questions, like things like, you know, what's GDP going to be going forward, or the course of interest rates, how do we think the market will react to that? Those kinds of things where you have lots of diverse pieces of information and not information that's concentrated in the hands of one or two people.

[A]

I just want to jump in to clarify that what you're saying as ideal are these topics where the collective wisdom of all of these participants who would put money on the outcome as they see it, that helps describe reality. Yeah. More accurately than just asking.

[B]

Exactly. Or something. Yeah. And just to say one thing about to go back to the policy analysis market, it's maybe a little niche, but it's, But I think it's relevant here. I think one of the reasons why the intelligence community was interested in this was that the intelligence community has had a lot of big failures. Right. So 9, 11, most obvious one. But even failures about things that you might have thought they would have done a better job of forecasting, like the revolution in Iran in 1979. Like that's a classic one. That's a big event, a massive public uprising that led to the shah falling. Right. And the US Intelligence community pretty much missed it. It just was not ready for it when it happened. And I think if you're in the intelligence community, you have to ask yourself, like, whoa, why? How did we miss this? What did we not know? And some of it is, oh, maybe we didn't have enough people on the ground, although that seems implausible. And so I think that the idea was maybe you could use these tools to tap into knowledge that people have that just wasn't getting to the decision makers.

[A]

But I want to distinguish now between polling and a prediction market, because the whole question of, like, you could have asked more people.

[B]

Yes.

[A]

Is what polling is.

[B]

Yeah, yeah, yeah.

[A]

But this, There is something, and this brings us, I think, directly to sports and sports betting. There is something that I think when I'm watching sports debate, which I at times participate in.

[B]

Yes.

[A]

Where it's like, if you guys really felt this way, you would have the courage of your convictions.

[B]

You would put money on it. Yeah, yeah.

[A]

Otherwise, we're just talking.

[B]

Yeah, yeah, yeah.

[A]

And we're not really meaning as sincerely as we could demonstrate what we say.

[B]

Yeah.

[A]

And so with a prediction market, the fundamental dynamic, which is the thing that makes this all very uncomfortable, is money.

[B]

There is money. Yeah. So let me say a couple things about this. So I. I think one of the challenges with polls versus prediction markets has nothing to do with money. It has to do with the fact that people in polls are generally asked, what do you think? Or what will you do? They're not actually usually asked, what do you think will happen? Right. So there are exceptions, but generally speaking, that's what a poll is. Now, as it turns out, you know, you can do things to massage polls to get a good answer. But I do think just the simple change of asking people, like, what do you think will happen? Actually can make polls more accurate. And I'll give you a concrete example of this. In the 2024 election, there was this famous thing that happened in the prediction market in Polymarket, which was that there was this French guy who was betting literally millions of dollars on Trump to win. Okay. And he kept buying more like pseudonyms. Yeah. And so it became clear at some point, Pie market revealed there was this big trader, they called him the French whale. And so initially, a lot of people thought that he might be doing it just to try to manipulate the market. Right.

[A]

So.

[B]

And that's something we can talk about like that there's some concern that people will manipulate these markets to try to make it seem that a candidate is more popular or more likely to win than they actually are. And so there was this initial concern that that's what was happening, but it turned out that that was not, in fact, what happened. What happened was he really thought that Trump just was going to win and had a better chance of winning. And one reason he thought it was that he had commissioned polls of his own of Americans in swing states, like the one I remember was in Pennsylvania. But. But the thing that's interesting was he didn't just commission polls where they asked people, what are you going to do? They commissioned what are called neighbor polls, where they ask people, how do you think your neighbor will vote? And the idea is that if you do that, you get. First of all, it might be a more collectively accurate understanding of what's going to happen, because you're also kind of asking people, what do you think will happen? But you also get around the problem of people might be embarrassed or afraid to say they're gonna vote for Trump, but they're willing to say, my neighbor will vote for Trump.

[A]

Right.

[B]

Anyway, the point is, like, just shifting the question in a poll can make a difference. Right? So that's part of it. At the same time, I do think incentives matter. I think it does help when people have to put money or status or reputation. I'm actually not as convinced as a lot of people are that you need to have a lot of money at stake. There's actually a lot of evidence from internal markets, inside organizations, and also from some of these smaller prediction markets that just status and reputation can play a big role and people want to win. They want to do better than their, you know, compatriots or whatever, or that relatively small amounts of money can still incentivize people to. To render good judgments.

[A]

Right. But what does that then say about the difference between a prediction market and going to a sports book?

[B]

So part of this has to do with asking yourself the question, what is the goal of. Of a prediction market? Like, why do we have them? Why do they exist? Right. There's been this explosion of interest in them. They've become. It's. And it's not just that they've become very popular or people are really interested in them. It's also that they become much cited. Right. You certainly saw that in 2024. And which was kind of what kicked all this stuff off was the election in 2024. And so you've seen this just like, okay, big boom. Now, what's interesting is that accompanying it has also been, perhaps predictably, this kind of backlash against them. Right. A Lot of people expressing like anxiety or articulating the problems with them sort of.

[A]

Yes. We're all living inside of a casino.

[B]

Yeah.

[A]

In which everything is bettable.

[B]

Yes.

[A]

And by the way, when we mentioned Caroline Levitt, press secretary of the White House.

[B]

Yeah.

[A]

Doing that thing right underneath the wire which pays off that particular market. Yeah. It's also worth noting in terms of just what are people saying and thinking that Donald Trump Jr. Is an advisor to not just polymarket but also to Kalshi and is an investor in polymarket on top of that.

[B]

Exactly. And the interesting thing about, you know, Don, Don has always been at the forefront of these types of spaces and new technologies. He's always been very in tune with what the American people feel and want. And he understands kind of this notion that people have been ready to fire the traditional institutions and authorities and basically.

[A]

Got tired of fake news, I think.

[B]

And that's why they're going to Twitter and that's why they're going to prediction markets. And I can't think of anyone else.

[A]

Who would be better to help us.

[B]

Promote the vision of prediction markets and what they can do for society.

[A]

And I just gotta jump in here to say that I love the idea of predicting stuff more accurately, but the vision of what prediction markets can do for society, as the co founder of Kalshi Tarek Mansoor just put it on cnbc, there is also way less obvious to me than what prediction markets can do for someone like Donald Trump Jr. Or some other well connected insider who can turn real world events into the equivalent of the NBA gambling scandal that we've been covering for months on this show where someone who's about to do anything bettable allegedly tells a bunch of his boys ahead of time so that they could all do some old fashioned insider trading together. Maybe even on the invasion of Venezuela.

[B]

That's the one that obviously is most important.

[A]

An international user, a polymarket, made $400,000 with bets related to Nicolas Maduro losing power. And this was a series of wagers he made just before the news broke that in fact the United States had, you know, gone in and captured him. He bet $30,000 to make 400,000.

[B]

Yeah, exactly. And at the time, you know, the probability was very low. And of course as he bet, the odds started to adjust. So there's this question of, okay, wait, we're essentially creating an incentive for people to leak information or to use insider information to make money. It's obviously a very big deal and a problem, Right. Huge.

[A]

And yet at the same time, if another standard of success for prediction markets is their sheer ability to accurately forecast.

[B]

The future, insider information is actually kind of more of a feature than a bug. Right. Like you want to know, like, is Maduro going to fall? Well, if you want to know that, then it helps to have inside information that actually the United States is planning to do this. Right.

[A]

If truth is what the actual standard of successes.

[B]

Yeah.

[A]

Than incentivizing all of these insiders to put their money on. Yeah. What they think is the outcome is a way of getting to.

[B]

Getting to that.

[A]

But this now raises a few logical questions for all the non Donald Trump juniors out there who do not have a direct line to invasion intel. And these are questions like, are these markets infested with Donald Trump Jr's friends? Is Kalshee's stated ban on insider trading enough of a deterrent to.

[B]

And if it isn't, then wait, why am I trading? Why would I be willing to take the other side of a trade?

[A]

But that's not even the most disturbing possibility here because as suggested by that objectively low stakes Caroline Levitt example, which I like to think of as the Jontay Porter unders of prediction markets, these bets, these contracts are also incentivizing people to do stuff that they simply wouldn't do otherwise for the benefit of themselves or their personal network or their creditors, maybe even the most powerful person in the world himself.

[B]

That's where it starts to get like, very problematic. Obviously, I think if you're the president, there's a lot you can do.

[A]

But if the whole thing is, if you see this government, this administration as less serious about whatever integrity means anymore. Yeah. Which is to say that they are so transactional that they are just draining every cent they can out of their personal ability.

[B]

Yes.

[A]

To access things that the public cannot.

[B]

Yes.

[A]

Then you have created this scenario where now there's a mechanism to profit in ways that never existed. Never really at the expense of the retail investor, the common person who is only still waking up to the idea that there might be people who would in fact. John Tay Porter a press briefing.

[B]

Yeah. Yeah. And so worse or worse, the worst is the more is, the more is the more interesting question. Like, I don't know, you'd have to look at what kinds of markets could be offered.

[A]

But you go back to the scenario that the whole thing that got shut down within a day.

[B]

Yeah.

[A]

That you mentioned. Where it's like rocket launchers and coup d'.

[B]

Yeah.

[A]

But like that's all on the table. Yeah. The question I think as a as an American, you ask yourself is are we sure that the government isn't doing things just to personally get rich on a prediction market? Yes, and I have personally no confidence.

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Solve a real problem and make sure the right people hear about it.

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Promote your business with podcast ads on Acast get [e-mail] advertise guys. To fast forward in time. One concern I have is we live in a society in which none of us trust that we're doing anything without a financial incentive. Because now there is an incentive to varying degrees, thanks to prediction markets.

[B]

Yeah, there's this quote from the CEO of Kalshi or maybe one of the founders who said that the long term vision is to financialize everything and create a tradable asset out of any difference in opinion.

[A]

And I think if you do build.

[B]

A general purpose exchange that can resolve differences of opinions on anything. The TAM is quite massive. Quite a bit bigger than the current TAM of the stock market, I think. Now I'm obviously, I'm a big fan of prediction markets and I really like the idea of creating assets out of differences of opinion when it comes to like important and interesting things. Where knowing is valuable.

[A]

Yes.

[B]

The truth as the world matters. Yeah. Where it actually helps us make better decisions. It helps us solve problems and the like. But a world in which every difference of opinion is turned into a tradable asset. There is something about it that feels kind of just tiring. Right. Like it just feels tiring and. And I think it fits with this general sense of everybody kind of being on the make. Right. Everyone has a kind of hustle. Right. And yeah, there's something about that. I do think there's a kind of. This is a broader cultural idea rather than like a specific thing. But I think that that vibe is something that I think is part of why prediction marks are kind of wearing people out a little bit.

[A]

Yeah. And by the way, the way that these things have been marketed, I mean, on social media. Yeah. It's been trolling.

[B]

Yeah.

[A]

They have been trolling by circulating these posts that are designed for engagement.

[B]

Yeah.

[A]

Which are not grounded in anything resembling integrity or truth, but are just trying to get the brand seemingly as widely consumed as possible.

[B]

Yeah. I mean, I think the marketing aspecting. Yeah. No, I mean certainly Polymarket has done a lot of that and the marketing is aimed primarily, I think at a young men. Right.

[A]

But successfully.

[B]

Yeah. Kind of right wing vibe. And maybe not so vaguely, you know, like Nick Shirley, that, you know, whatever, 23 year old, the greatest investigative journalist of our time. Yeah.

[A]

Solved the problem of fraud in Minnesota trying to get into daycares.

[B]

Exactly. So, you know, he. One of the videos he made, not the initial video, but one of the ones that followed up, he had a Polymark Market sweatshirt on. And it certainly seemed like not just that it was delivered on his part, but it felt like a kind of weird sponsorship thing.

[A]

Yeah.

[B]

I think it's part of why people feel. Some people feel alienated from these things. Like prediction markets are this kind of right wing tool for. I don't know what I would characterize.

[A]

Their strategy as there is money available right now on this table. Let's grab it. Yeah. And whatever reputational harms come to us are outweighed by the fact that we are. Yes. Hoovering up young men across America.

[B]

Yeah.

[A]

To be not only our customers, but our propagandists. But speaking of truth versus propaganda, I do want to acknowledge another real world impact of the booming popularity of prediction markets here, which is that a prediction market's power to do one thing reasonably, forecast outcomes also gives the biggest buyers of these events contracts a bonus power. The power to buy legitimacy to set expectations by setting the market, normalizing a unilateral invasion or the outcome of an election, making all of this a Patriots prop bet of a different kind. Or as the author Kyla Scanlon wrote in a New York Times op ed last month calling for greater regulation of his industry, quote, quote, Markets will always influence reality, but there's a difference between markets that respond to events and markets that authorize them, end quote. And I think this is worth thinking about for both high stakes and low stakes events because social media, you may have noticed, has numbed us to how financial incentives warp and hollow out our shared reality in pretty much every way already. But in Jim's view, a view that has been energized for more than two decades by the prediction part of the term prediction market, that same power can also tell us something else.

[B]

There's one other aspect of the election prediction markets that I'm interested in. Actually there's two aspects of it and it gets to this question of like, why are these things useful? Like, why might they be useful, right? And so one way they might be useful would be to say if you see, like the prediction market is more skeptical of you than polls are, it might be a way to say to yourself, okay, wait a minute, what are we missing? So a classic example would be like 2016. If you think about if we had had robust prediction markets in 2016 and the market for the electoral vote in Wisconsin was saying, actually we think there's a, a 30 to 40% chance that Trump is going to win Wisconsin, where the polls, it felt like we're saying 10% chance. Hillary could have looked at that and said, huh, that's interesting. Should that change the way we're handling the campaign in these states? And that I think is like a concrete example of the ways in which prediction market information could be useful. Now one of the concerns people have about prediction markets when it comes to elections is can manipulation create a kind of image of success that in turn kind of creates success in the real world.

[A]

So there's an example of this, right? 2012 in trade, one of these prediction markets a better put a series of huge wagers on Mitt Romney in the two weeks before the election and it made a betting line that indicated a Tight race. And of course, look, I'm not saying that we have any proof that the better did this because of financial motive, but it certainly changed the perception of like, oh, Romney's absolutely in this. And this trader, you know, again, he lost $4 million.

[B]

Exactly.

[A]

But the premise was this is $4 million that otherwise would have been used on like ad buys.

[B]

Yeah, exactly.

[A]

And this would be more effective.

[B]

And so this is. So there it is an interesting question. My, my general sense, and I think the evidence kind of bears this out, is that that kind of attempts to influence the market are probably unlikely to work, first of all, because the market will correct relatively quickly because it creates this opportunity to make money. Right.

[A]

Someone else will see it and be like, I'm taking the other side of that.

[B]

If someone is making a really dumb bet in order to kind of inflate the prospects of someone who's not really that popular, that's creating an opportunity for other people to make money and people are going to take advantage of that. And then the second thing is, I think just generally speaking, this idea of the bandwagon effect in politics, there's just not much good evidence for it. In other words, there's not a lot of evidence for the like, oh, they're winning, therefore I'm suddenly going to change my vote and vote for them. That's why Trump was so angry about that Iowa poll that came out. Right. And why he sued about it and all this kind of stuff. Right. To essentially create his bandwagon effect. Yeah. Totally believe that. It makes sense given Trump popularity images, everything for him. But of course, Iowa voted massively for Trump and that poll had no influence.

[A]

All of which is fair. And I think the thing that's interesting that you just said on top of that is a robust market.

[B]

Yeah.

[A]

Will immediately address any attempt at manipulation.

[B]

Yeah.

[A]

Which is to say that right now we are in this kind of in between zone where we're not quite there yet.

[B]

Yeah.

[A]

For at least an array of. Of bets in this increasingly vast menu of bets.

[B]

Yes.

[A]

And so it is funny that like. And this is kind of where I see the nuance and the apparent paradox.

[B]

Yeah.

[A]

In order for these things to be healthier and less poisonous, you need more participants.

[B]

Yeah, that's right.

[A]

I mean, you need.

[B]

Yeah.

[A]

And so that's. But it's just like.

[B]

So you want markets, again, to go back to the wisdom of crowds. You want markets that are full of, of people with diverse opinions, people who are, relatively speaking, independent of each other. So you don't have a lot of people who are like listening to each other in a kind of direct way and that are liquid. So if you want to make a trade, you can make a trade. It's easy to do. And markets that don't satisfy those conditions are a more easily manipulable and they're also just more likely to not be right. They're just less likely to have an accurate forecast. So one thing I would say to people, because I'm sure a lot of people who are listening to this are people who will end up up or are already trading on prediction markets, is I do think the thing to remember when you go into a prediction market it's the same as when you invest or whatever, but is to ask yourself what do I know that the person on the other side of this trade does not know when it comes to these like more narrow small markets, if you're not sure that you're not the sucker, you are probably the sucker.

[A]

I was going to say it's the rounders quote.

[B]

It is.

[A]

If you can't spot the ucker in your first half hour at the table, then you are the sucker.

[B]

Exactly.

[A]

You know, I realized at the end here that I didn't ask you whether you've ever. Have you ever bet on a prediction market.

[B]

I think I did. I was trying to remember. I think I did make a bet on predict it in 2024. But yeah, I have not done it as much as. But again, probably another. Well, that might actually be a good financial decision.

[A]

Yeah, I love that at the end here. What I actually found out is that Jim Surowiecki, the intellectual forefather of the thing that is eating our country, has made 0.$00, it seems on the thing that he accidentally created.

[B]

Correct.

[A]

This has been Pablo Torre finds out a Meadowlark Media production and I'll talk to you next time.

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