Why the Godfather of Prediction Markets Thinks Insider Trading Should Be Encouraged

Speaker A: I started Ornod in 2013 and we make bike apparel.

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Speaker A: We run the business on Shopify. Start your free trial on shopify.com welcome everyone to the special episode of the Future of Crypto Compliance podcast. We've been discussing a lot lately about prediction markets, and today I'm very excited to have literally the godfather of prediction markets on the show, Professor Robin Hanson. Professor Hanson is an associate professor at George Mason University in economics here in Washington, D.C. and he's the author of the Age of M and the Elephant in the Brain. He's literally the godfather of prediction markets. First started talking about it in 1988, before many of you were actually born. Um, today in this episode, we're really going to talk about prediction markets, the role of insider trading and prediction markets, what the real vision could be. And I know this is a topic especially for those of you focused on crypto compliance. That has been a big topic of conversation. Hopefully today will be quite insightful. Professor Hanson, welcome on the Future of Crypto Compliance podcast.

Speaker B: Great to meet you.

Speaker A: So you've been looking at this topic since 1988. I want to talk, I want to go more in depth, but what triggered why like 40 years ago? What was the really the click that happened to start looking at this area?

Speaker B: So you've heard of the World Wide Web?

Speaker A: Yep.

Speaker B: There was a time before there was a web and I was working with a group trying to invent it, a group called Xanadu in Silicon Valley. And they had a vision for how the web was going to make public conversation better. And their vision was that it was make criticism easier to find. And I thought that was an admirable vision. And I was working with them and then I started to have doubts. I said, okay, yeah, criticism easier to find. Is that really going to help that much? And I asked myself, well, what else could we do to make public conversation healthier? And because these people I was hanging around with were kind of rabid libertarians, the idea of betting markets was accessible to me through them. And I thought, what if we just had more betting markets on stuff? Wouldn't that make for healthier conversations? Because we could just defer to the betting market odds as our consensus on important topics, and then the people who knew could go fix those odds. And that should work pretty well. So I started to think and write about that, as you said, in roughly 1988.

Speaker A: That's absolutely incredible. I mean, uh, because really they became mainstream really in the last couple of months or the last couple of years, to be fair. But it's. I think many, very few people know that, you know, prediction markets have been around for a very, very long time. And actually there were numerous attempts of having prediction markets go more mainstream, but many of them obviously didn't work out over the years.

Speaker B: Right. So betting markets are ancient. Yeah, of course, roughly a century ago, there was more money in the U.S. betting on presidential election than there was in the stock market. At the time, stock market was small. Betting on president was big. So bets are old, that declined with the rise of scientific polling. Um, but bets are old. In the last decades, we've often had people try to bet on other things. My niche, if there is one, is just that I said we could go really far with this. I thought in terms of all the different ways as an information society or whatever, that we aggregate information. I thought this is a mechanism that works really well and we're just not using it as much as we could.

Speaker A: So you just said that we can go very far with this. And I was reading one of your recent articles, I, uh, think it was in December last year, and you said, you know, we're still in the very early days and we're still very far from my vision of where things can go. So what is your vision when it comes to prediction markets? What is the nirvana that we can hit and what benefit does it give to markets and society?

Speaker B: So speculative markets can be used for a number of purposes. So one thing, they can just be fun. They can maybe let you prove yourself, have some competition, some action, some, you know, combat really. And people have wanted to use betting markets like that for a long time. Another thing they can do is hedge risk. And in fact, the standard regulators say that's the main reason for most financial markets. They only tolerate the speculation because it'll support the risk hedging. And for a long time they didn't really want to allow prediction markets because they said you can't hedge much risk there. So what's the point? There's this, uh, third function, which is information aggregation. It's long been known that that's a function that financial markets perform, but nobody pays for it. It's a side effect of people doing the other things. The main customers are the Traders who are there for fun or action or risk hedging. Nobody's paying for the information, but everybody's known. Yeah, the information is a nice side effect. And I said, we're in the information age. Information's like a big thing now. Why not have that be the main effect? That's the vision here. So the vision is why is information valuable? It's because it helps you make decisions. That's the key thing. Our world is full of people making decisions where they could make better decisions if they had better information. There's a much bigger demand for that really than there is for risk hedging and entertainment in the markets. The function of aggregating information in principle has a much larger latent demand than the demand for reallocating risk or action function. That's the huge potential. Could we make the product where the customer is the person who wants information and they're willing to pay for the information. And then the market traders are the suppliers who meet that demand for information and they get paid because the person who wants the information is there paying for it. That's the way things could be different. But we're not there now.

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Speaker B: So let me walk you through a very concrete vision.

Speaker A: Yeah.

Speaker B: So in corporate, in companies for profit companies, one of the biggest decisions they make is keeping the CEO or getting rid of the CEO. Right. That's an example of a big decision. They make lots of other decisions, but that's probably the biggest decision they mark. So here's how we could make a market to advise that decision. Should you keep the CEO, you have a stock market trade stock for cash. And when you trade in a stock market, you're supposed to ask yourself, here's the current price, is that too high or too low? And what you compare it to is you say, let's imagine all the situations a company could be in. What's the company worth in each situation? Average that out, come up with my estimate of the value of the company. And if the price is lower than that, buy price is higher than that, sell. That's what you do in an ordinary stock market. Now we're going to make two new stock markets. They're just like the regular one, except they're called off if a condition isn't made. We're going to make a trade, except we're going to cancel a trade if a condition isn't right. So one of the markets going to be we only have the trades happen if the CEO stays in power past the end of the quarter. And in the other market, we only have the trades happen if the CEO leaves by the end of the quarter. So these are conditional or called off markets. And we're going to get a conditional price. In one market, we're going to get the price of what the company's worth if the CEO stays. And the other market we're going to get what's the company worth if the CEO leaves? Those two different prices will tell us the story of whether speculators think it's worth keeping them or not. That's an example of a decision market. So here's the key structure. We have an outcome here. The stock price, that's the thing we want. And we've got an asset tracking that outcome. So we could do it for a crypto firm if they got a coin. Right. So we have an outcome that tracks pretty close with what you want for the decision next. We have some concrete choices here. Keep the CEO, get rid of the CEO, what we Ask the market is conditional on each of the choices. What's the outcome? Now that directly advises a choice. So here the customer should be the board of directors of the company. They should be willing to create and subsidize this market to tell them advice about whether to keep the CEO. But we can do this for all sorts of other big and small decisions in companies. So raising new capital, restructuring, mergers, acquisitions, any big decision, we could ask the market, well, among these options, which one looks best? So we can do this for, ah, lots of other organizations, for lots of other decisions in personal life. We could walk you through lots of examples, but start to realize there's a whole world of people and organizations making big important decisions and we could just put a market right next to them directly advising that decision.

Speaker A: So let's use the example you mentioned, right? So let's say I'm on a board of directors, a company, and we put this market, should the CEO remain or let's say get fired?

Speaker B: Right?

Speaker A: And in a way, this, this information would give us an indication of how the actual stock price would trade, depending if that decision is made, whether he's fired or not.

Speaker B: Right.

Speaker A: How would you argue? I would argue putting my lawyer hat on that if, let's say, the information clearly shows that, you know, if CEO, uh, is fired, the price of a stock will go up, for example, then there's also fiduciary duty, indeed on behalf of the board members to actually follow, follow on the solution.

Speaker B: So you asked me, how could I change the world here? Now I'm going to say if I just create these markets and let's say I do the entire Fortune 500 for five years, okay? And I track the companies that follow the market advice and the companies that defy the market advice. And I say, which pool does better if the pool that follows the market advice does better. Now, I've got a pretty strong presumption on the board to say, hey, board, you're not doing your responsibility if you defy this advice. And you could now scare the board's directors into following this advice, and you would change corporate accountability dramatically for the, you know, for civilization on the basis of this really tiny project, which was to make two markets on each for the Fortune 500 and run it for five years.

Speaker A: So I have two questions on this. Let's use the example you just mentioned, right? So technically now this happens unofficially, let's say a hedge fund that is trading a certain company will do market research, or you can survey a couple of institutional allocators and get Their perspective of how they would trade the stock depending of a certain, uh, decision. Uh, you know, in this case, you can, you can argue that the, these institutional investors have an unfair advantage because they know, and they, you know, if you have the money, you know, in a way similar to expert.

Speaker B: Unfair.

Speaker A: Yeah, well, it is what it is.

Speaker B: They spent their life learning how to do that and they get paid for it. Well, how is that unfair?

Speaker A: But on the question how we get paid, how would, let's say, how would you want to compensate the retail investor? Let's use a company example, I believe, I don't know McDonald's. I mean, just use it. Nothing to do with McDonald's. They're not sponsoring the show. But let's say, I believe that if the McDonald's CEO remains or is fired, the price of the stock should go up.

Speaker B: Right.

Speaker A: How would you compensate the person who's putting money on that prediction market on this? Cos in or out.

Speaker B: So markets that are more liquid offer more profits for informed trading. So when we calculate in our standard models how much you profit from having information trading in financial markets, the thickness of the market you're trading in is directly proportional to your profit. There's also a value in how long your information lasts, uh, and that, you know, how quickly you have to spread out your trading. But to a first approximation, it's how liquid is the market times how big is the price move times how long will your information last? That's the profit you get from trading. So all we have to do to compensate people who are going to tell us about the CEO is to just make that market thick.

Speaker A: Yeah. And then obviously they're become incentivized by, uh, doing so. You know, uh, Robin, you've been, you wrote, um, you know, it was great doing research for this episode because I went through a lot of your writings and blog posts, uh, over the years, really all the way going up to 20 years ago. When you talk about insider trading, even, uh, we have a lot of crypto compliance and compliance professionals and regulators listening to the show. It's very interesting because you advocate that insider trading in prediction markets should be encouraged in a way that actually helps prediction markets. Can you walk us through your thinking on that perspective? And why do you believe insider trading could be beneficial to such markets?

Speaker B: These markets have a number of functions, but one of the functions is information aggregation. That's what we've been talking about so far. And in that role they compete or substitute or complement other information institutions like academics or journalism or even gossip. And we should hold them to similar standards in that information role. Now, journalists, for example, have often enticed people to reveal secrets that they had promised to keep. And some of our most famous journalism stories are on the basis of that. And those are celebrated journalism cases. So journalism in general is trying to generate information that's interesting and relevant and accurate, and we celebrate that on average because they achieve that. Now, it's not always true that we always want all information revealed, but journalism is trying to reveal information and you'll have to restrain it somehow if you want to tell it. Yeah, but don't look into that. Right. So the same for these markets. Their basic habit is going to be to extract information and to collect information. And that's what they do. Well, and in general, that's what we want. We want them to collect and aggregate information. But maybe that's not everything we want. And sometimes we want something else. So that's the trade off here. I'd say all else equal, nothing special happening. Of course we want the most informed people trading because that's how we get the more informed prices. That's the whole point here. Some people who say that's unfair, it's because. Oh. Cause those people have an advantage. We could have a basketball league where everybody's 5 foot 5 and shorter and then it's fair because you don't have to play against tall people. But most people don't want to play in that league. They want to play in the league where the best people can play. Right. And the same way in the markets, if this market is about the best information, then we want the people with the best information to trade all else equal. Now we might say there's other things we care about in the world. Fine. So for example, organizations sometimes have secrets and they want to keep their secrets, and they try to use contract and other incentives to get their people to keep their secrets and all else equal, that's okay. But we don't necessarily want to recruit everybody in the world toward their cause. Other people might want to learn their secrets and they might also have a valid reason. So I think as a society, we want to stand back and don't take too strong a side here. Let's let organizations try to keep their secrets. Let's let other people try to find them. But the market in general is just going to try to extract information, and that's doing a good job from the point of view of the information it's supposed to give us. If some harm is done because we wanted organizations to keep their secrets, then we have to use the usual mechanisms to let them do that. So, for example, some people have proposed that government officials shouldn't be allowed to trade in markets because they might reveal secrets. I'd say similarly, then you shouldn't let them talk to reporters because they might reveal secrets that way. If it's so important that the government keep its secrets, then dare not let them talk to reporters because they might reveal secrets. Just have a similar policy across all these institutions. But when we go to journalism, most people think it's pretty good that journalism finds out a lot of secrets. And they think if you're an organization, you can't keep your secret from a journalist. That's too bad because it's fair game for them to try to find out what they want from you and it's your job to maybe hide it from them. And the rest of us aren't going to take a side here.

Speaker A: But if I use the same logic and same train of thought, technically then right now we have insider trading rules on stocks. Let's say if I'm a company executive, right. Uh, I'm not able to trade around my stock because I'm privy to some confidential information. With this analysis you just mentioned, uh, do you believe that those rules also should be thrown out of the window? Or there's a core framework that I think for the people that are genuine insiders, that should be kept.

Speaker B: So in a firm, a for profit firm, they could decide that they want to keep some secrets and therefore they could by contract limit their employees and associates from trading on them their inside information. That's something that could happen by contract. And again, that seems like a perfectly reasonable use of contract for them to get them to read that. But what happened is in the US Roughly a century ago, the regulators decided it shouldn't be a choice of a company whether to do this. We just require all companies to do this. And their argument was of the form, well, there's a trade off between the accuracy of prices and the quantity of trading. And we want more trading, even if that comes at the cost of less accurate prices. That's because they wanted to promote the stock market and have more stock market trading. But again, each company makes the trade off themselves. I don't see why we should force everybody to follow this one logic of it's better to require everybody to keep the secrets. But that's what the regulators decided. But even if you think there's a reason for that for stocks, it doesn't really apply to all these other markets that we have. Commodity Market, currency markets, prediction markets. There's no particular reason we should have a policy of wanting more trades there at the cost of less accurate prices. No, what we want is more accurate prices. And that's just like wanting the tall people to play basketball. We want this game to be about whoever's best, and they should win.

Speaker A: I see your perspective. Um, but let's say. Let me, Let me look at it from a different perspective. Recently we had some of the first, um, criminal, uh, investigations going on. Perfect example was, uh, this individual in the military that basically batted on the Maduro, uh, you know, uh, arrest, basically. And he made something like $400,000 betting the exact time that Maduro was going to be kicked out of Venezuela. In using your, your analogy, there's no regulatory policy, uh, incentive to bring more people on trading, prediction market. This shouldn't be a regulatory safeguard against insider trading on prediction markets.

Speaker B: Well, there's a difference here. The government has employees, and they want them to keep their secrets. So again, I'm okay with organizations using the usual tools that organizations could have to get their people to keep secrets. If they betrayed their trust, stole information from them, then their employer has a valid complaint about that. But the rest of us don't have a dog in this fight, right? Necessarily. Unless there's some organizations we should all be just supporting so much. But I'm not sure the US Military really counts for that.

Speaker A: So your argument is, okay, let's say government, if there's a certain thing or a certain company on a contractual basis, they do it. But from a policy perspective, there should not be a blanket inside of trade.

Speaker B: I mean, even for the military, we might make it a crime for someone to violate their military orders. We're willing to use stronger enforcement for the US Military, but still, that's about, you know, betraying the military. That's not about the markets, per se.

Speaker A: I understand. And you wrote. I, uh, forgot which one of your articles in recent years was that even with all the restrictions and regulatory frameworks we have and all the policy making we have around, there's still insider trading going on. I mean, uh, before announcement of a company, a lot of it is baked in already.

Speaker B: So let's just be clear. I mean, most people are terrified in the ordinary financial markets of being accused of insider trading. So I and a friend actually wanted to develop a product for people who had information, and we said, let's get a set of cases. So we offered to pay people $200 an hour or something to come tell us cases where you had some Information you traded on that and how that works so we could design a product that you would work for you. And no one was willing to tell us their stories because they're all terrified of being accused of insider. And we said decades ago, it could be long ago stories, but no, no one would tell us. And you might think, you know, that's pretty wild, how much insider trading is there really? But the fact is, on average, when a public company makes an announcement, it moves the price. And on average, half of that move happens before the announcement. And on average, about half of that's probably insider trading. So insider trading is actually rampant in ordinary financial markets. That's why all these people are terrified to tell us any stories. So, in fact, insider trading is just a huge thing, a big part of the world of financial markets as it is today. Insiders all know that, but they, um, authorize regulators to give this appearance of anytime they find it, they're going to squash it because we should all be terrified. But in fact, we just have a lot.

Speaker A: Hey, everyone. Henry here. I have one little favor to ask all of you. If you like this content, make sure to subscribe on YouTube or follow us on Spotify or any of your favorite platforms. The majority of you listening to this podcast are not subscribed. And really having subscribers really helps us. Getting better guests and getting sponsors and making more of this content possible. It costs you nothing. It's free, but it really helps us on our side. Thank you once again. Now back to the show. I mean, the argument, you know, from the compliance or regulatory perspective is that, you know, if you're using that in the Mosaic theory, you know, you get a couple of pieces of information in different places and you're not using material on public information, uh, it's okay. But, uh, of course, if you're using insider information, that's obviously a criminal, regulatory, uh, offense for. But from that perspective, professor, uh, Hanson, I mean, there was a lot of, uh, recent reports on prediction markets, you know, some of them basically showing from a data perspective the beauty of having them on the blockchain, that literally it's a 2, 3, 4, 5% of users are making the biggest percentage of the gains. Um, and the argument is these individuals may or likely have some kind of insider information on it.

Speaker B: That's just how ordinary financial markets are. This is the, this is the world of ordinary financial markets. Most people in ordinary financial markets lose money, go away, and there's a small fraction of financial market traders who make most of the money because they are, in fact, the Most informed. And that's how most financial markets work. Stock markets, commodity currency, all of that. Like, where does all the money come from? Financial markets? You ask all these hedge funds, they're making money trading against somebody. Who is the loser? Well, what it is, is mostly new young professionals, a new dentist. All of a sudden they're finally out of school, they're making a lot of money, they're hot shit. And now they're going to go to trade the market and prove how much hotter they are. And that's where most of the money comes from. In most financial markets, those people are losing, the hedge funds are winning. That's how most financial markets works and have worked for a very long time. We're just now seeing that in the prediction markets because they are just a new kind of financial market.

Speaker A: So obviously now there's a lot of, uh, policy support, not only from the current administration. We're recording this, we're in June 20, uh, 26. Um, and from a CFTC perspective as well, let's say tomorrow morning, um, CFTC Commissioner brings you on and says, design the rules that you want for prediction markets. What would you do? Uh, would you exclude them from, let's say, insider trading or market manipulation regulations? Would you make it more accessible? What about KYC requirements as well?

Speaker B: So, as you might know, when most people talk politics, what they think of is what I would do if I were a king. But politics has few kings. Most people have to compromise a lot. So you put me in a political role. I'm going to ask, how will I compromise? That's what I really have to ask. What am I willing to give up to get the things I want? So on that spectrum, I'd say I'm worried about a backlash. I'm worried that people will shut this down because they're offended by things. So what am I willing to give? And I might want to draw the line at questions that matter. I'd say, fine, if you're too much of a prude or puritan, that you don't want people to have fun betting on sports, let's put that in a category of the things that you're going to be more wary of and regulate and whatever you're going to do to it. And I'd say on the other side of that line, though, is the questions that matter and you should give those more free rein because that's this whole future potential that we could have markets that answer questions that matter. In fact, I'd say you should see that as a free speech thing. So I don't know if, you know, if you look at the free speech jurisprudence, the way it works is the courts have said, well, if you're talking about things near politics and policy, we give you a lot of deference, because that's what free speech is supposed to be about, making sure the political system could work. And in fact, we've said you can do things like protest, fill up our streets, block our traffic, cause a big mess, because that's a big cost. But there are some things you can only say that way that you can't say in other ways about politics and policy. And because of that, we're going to give you deference and let you protest. So I'd say there are things you can only say in betting markets that you can't say through protests or letters to the editor. And therefore we should allow betting markets on questions that matter as a free speech rationale, because we should let people say things through this mechanism and with

Speaker A: no KYC done as well.

Speaker B: Uh, the question is, to what extent would KYC get in the way of free speech? Like, for example, you might say, can you protest in a mask?

Speaker A: Yeah, exactly.

Speaker B: Okay. If it's okay to walk down the street and protest in a mask, then we might say, okay, we're worried that you will be hindered from protesting if you reveal your face. And therefore we're going to need you to be able to be anonymous when you protest. I might say, okay, a similar reason might be if you're afraid that you'll get face retaliation if you bet and reveal information for betting, then, yeah, we might want to by default let you be anonymous. But that's not quite the same as no possible revelation. So the ideal here is, uh, as you know, in many areas is we let you have privacy, but we allow information to be subpoenaed. In the case of especially strong criminal suspicions or lawsuits. That's how this is the default for all information in our society. I don't know if you know, all information is basically subject to subpoena. When a court says, we want to know that because it's relevant for this case, you just have to tell them there is no excuses there, almost no excuses. That's how the law works in our world. Uh, all secrets are open to courts who want to know. And that's perhaps a reasonable trade off. The question is how you implement that in crypto, and I don't have a strong answer on that, but there's a basic trade off here. Yes, it would be good if information could be subpoenaed but it can be bad if you can't keep secrets in the typical cases. And so now if we have to choose between them, that's a hard choice.

Speaker A: But I get and I agree with your argument about let's say political point of views.

Speaker B: Right.

Speaker A: And forget even the US let's say you're asking a question in your own on you ask the Iranian people do you want ayatollah in or out and you'll get a good sense of and of, of what people think. And of course if they have to kyc or identify themselves obviously with the uh, it'll be like North Korean elections or what we see in other countries. But right now when I look at the volume on prediction market at the stand today, it's 90% plus. I may be off a percent or two. Uh, on sports betting.

Speaker B: Right, right.

Speaker A: Uh, based on this then, um, do you think the prediction markets are achieving the goal towards what you believe they will reach? Because the usage is being basically for fun. The risk and information element is not happening right now in prediction markets.

Speaker B: The markets that we see today are lowering costs, creating legal precedence, customer familiarity. All of those things will help in the direction of the things I want to do, but they aren't directly mostly doing what I want to do. I don't mind that much because I don't mind people having fun. But, but if other people do, if the consensus of voters is they do mind people having fun, then I'd like to draw the line at questions that matter. That's my proposal. Interesting is to draw it there. But if I have my druthers and I'm king, I'm gonna say let people have their fun.

Speaker A: And you know, and I get the fun part and uh, obviously brings a lot of people to, you know, if they start with sports betting one day on uh, polymarket Kalshi, then they may actually also put some information in some of the other markets as well on their views on government and other stuff as well. So when obviously a couple years ago the um, you uh, know for me the aha moment to prediction markets personally was when uh, President Trump there was these last elections going on and the surveys, the old school surveys were saying one thing and Poly market and culture were very clear on the other side and of course we saw that how prediction markets were more accurate. Um and for me that was the aha moment. Okay, wow. This is actually going to be taken seriously and we're seeing now a lot of the financial networks are now using prediction market information as well on many on many, uh, facts of life as well. Do you believe also you mentioned earlier, outside of fund and risk, that's where

Speaker B: the pushback is happening now. So, I mean, a lot of people don't like these markets and they are pushing back. They're taking the opportunity on whatever they think people are going to be the most upset about. And that seems to be insider trading. So that's where all these stores, insider trading is a pretty small fraction of what's going on. And again, most of what they might call insider trading isn't really that a problem, but that's where they think they can win, and so that's what they're jumping on. But the actual reason a lot of people are bothered is the loss of authority. There was an op ed in the New York Times a couple months ago that said, look, people are going to the markets to find their news first. That's not right. They should be coming to the newspaper to get the news first. We are the proper authorities. There was just a article in Nature, the very prestigious science journal in the last few days that basically said, uh, well, on science stuff, you should be talking to scientists, not looking at these market prices. These market prices aren't the proper authorities. There's a sense that the proper authorities are being undermined. And, you know, when journalism first showed up a few centuries ago, the usual authorities then had the same complaints about journalism, the church and the state and the aristocrats. They said, this is sensationalist. You can't trust it. These people have the wrong motives. They aren't the proper sort of prestigious people. That should be your sources on these things. And they heavily regulated journalism in many places and disparaged journalism because it was not the proper respectful authorities. Now journalism has achieved its high status. It's even displaced many of these, uh, like the church or aristocrats as prestigious sources of information in our society. And now they see these markets as threatening their proper prestige.

Speaker A: Interesting. So the wisdom of the crowds and this kind of information, you know, if I want to find out if, you know, the US Is going to bomb Iran, actually I should look into prediction, into prediction markets as a better sense of the information and the accuracy of that information.

Speaker B: And people are starting to do that. If there's a world event, you go to the prediction market first and say, what are the odds do they have before you go to the New York Times? And that makes the New York Times a little unhappy because they wanted to be your first place you went to to look for information about these things.

Speaker A: So you believe the backlash, A big driver of the backlash are some of these incumbents in the space of, let's call the business of information, basically.

Speaker B: Right. Well that's an alliance between them and puritans who just don't like people having fun.

Speaker A: Yeah, well, on the, uh, well, yeah, I mean it that we could not be argued against those. The puritan movement, what it call is also against sports betting and gambling and all the other stuff as well. Right. So are you surprised to see the fight like when from your perspective, looking at it more realistically, uh, there's a massive fight right now between the CFTC who believes this should be a federal jurisdiction in the states, who see it as sports betting. In my opinion, this is going to go to the Supreme Court. I don't see how this is going to, you know, how this could be actually, uh, decided otherwise. Ah. Are you surprised of this becoming such a big debate or you believe it's because there's dollars involved, uh, of tax revenues or ideological.

Speaker B: We know specifically that the main people pushing for the states are the regulated firms regulated by the states who are now losing their business to the national, you know, gambling. National sports betting basically used to have state regulated sports betting and now they're losing their business.

Speaker A: So you think it's pure business? That's the main reason.

Speaker B: I mean there's lots of reasons people get involved in these things. One of the deepest questions in politics and policy is about at what level should decisions be made. And there's no easy answer to that. Uh, sometimes people pick whichever side favors them. Right. I don't know. Half century ago people were really important that issues of civil rights be handled at the federal level. Right. Because if the states were doing that would all go wrong. Right. But that's because those people had more sway at the federal level than they did at the state level. So that's what they favor. But people just, for a very long time, people favor who should make the decision based on who they think will favor their side.

Speaker A: Let's talk about the individual level. So you mentioned we right now that the company level, uh, you know, I can make a decision whether you know, the uh, US will bomb Iran or whatever, you know, um, and so right now most of the big platforms, the contracts, the markets are set by the company. Right. Polymarket, we decide what is there. You wrote a lot in recent blog posts that you know, on the individual level.

Speaker B: Right.

Speaker A: So I can have an individual level, uh, on Henry, like should I do, uh, X number of podcasts?

Speaker B: Let's walk through this. So first thing, every new technology starts off with high prices, high costs, and as the costs fall, the range of applications can spread. So when you're looking at advising decisions, the first place to look is at the most valuable decisions, like, say, firing the CEO, because you can afford a pretty high price for this process and still get value there. But as you lower the cost, as you make this infrastructure cheaper and more accessible, then you can go to a wider range of applications. So that's what we're talking about here. We're not talking about doing this today, necessarily, but maybe not that far from today. So we might. So, for example, there was a website called Manifold that was a play money market, but it set up some markets on some, uh, individual people, and if they dated other people, how long those relationships would last. And that isn't that expensive to set up these markets because they did them for play money. You could do them for real money. So you could, in fact, ask the people around you, okay, I'm thinking of dating these people. Who do you think if I date them, it would last? That's quite feasible to do mechanically. Now you have to ask, do you really want to know? Because that's part of the problem here. They might tell you, no, these people don't like you, and they don't want to date you or something. Okay. But, uh, think of other big decisions you make in life. Like think of a high school kid deciding which college to go to, which major to take. You could have markets on your lifetime outcomes conditional on which college you go to, which major you go into, and which first job you take after college. Each of those is an important decision in your life. In addition, of course, on the other side, the college could say, if we admit you, what's the chance you'll graduate with what gpa? Uh, and they could use that in the admission process. So any big decisions we have, most companies that hire a new person, say you're a division with 20, 50 people every year. You typically hire a couple of people. And you could have markets for each set of new hire candidates. And if you hire them, what will their employee evaluation be a year or two after you've hired them? That's, again, individual decisions about individuals. So the company could say, do we want to hire you? How will that go? We could have a market for the person, okay, if you take this job, how will that go? That's all quite feasible. And, uh, another way to think about this is if you had markets on these individuals dating other people or going to particular schools, say you had Millions of those people. Well, you'd have professionals betting on those millions as aggregates. They would take all people of a certain characteristic with all other people and they would bet on that. They wouldn't have to go bet on each particular person and case, but each person would get their advice from the fact that people were betting on all these aggregate cases. So it could actually be quite cost effective for people to have these markets on. Who should I date? What school should I go to? What should I major in?

Speaker A: As long as it's liquid, as long as market is tick, as you mentioned

Speaker B: before, it doesn't actually have to be that liquid. So that's the whole point. So when we were first worried about prediction markets being allowed decades ago, again, the main complaint from regulators was all these things do is aggregate information. They don't hedge risk because they're too small. So then we just don't allow them. But small markets without much liquidity can still aggregate a lot of information. Actually, it's about the cost of people to get the information. So you want to think of it as a market for buying and selling information. When you put a low price of information, then people will supply the information up to the cost of the information that you set the price at. So when you have a small market with, with small amounts of rewards, you will get information. You will just get a limited amount of information. But that can be a lot if people actually already know a lot. Right? If people already know a lot about your topic as a result of doing other things, then you don't have to work that hard to give them big incentives because all you have to do is get them to bother to tell you what they already know. And that's a reason why many play money. Sports betting markets have done pretty well because there's a lot of people already thinking about sports out there. You don't have to do anything extra. You just have to get them to tell you what they know. But when there's a specialized topic and you really need some extra research into it, like should the CEO be fired? Then as you raise the liquidity here, you're raising the price you're paying for information. And now people ask themselves, okay, could I go find some more information? At what cost? And then how much are they paying for information? And then you'll get more information when you offer a higher price for information.

Speaker A: Absolutely. And I can see, um, on that perspective, I mean to use that to continue on your, on your analogy is if I'm nasdaq, I have an incentive actually to have such markets because it will actually bring liquidity. Will bring more liquidity in a way. Right. More people are trading those. Prediction markets will probably trade the stock as well. I mean, it just brings, uh. And the value. As the value is more important, it will be, uh, interesting as well.

Speaker B: So most markets up until now, their customer is the trader and they're making policies to get more trades. More traders coming in.

Speaker A: Yeah.

Speaker B: So we're thinking of switching to a world where the customer is the person who wants information. And now we ask what information do they want and what are they willing to pay for? Obviously the same markets can do both. But, uh, the fact is traders trade on the things they're most interested in when they have to pay. And there's a lot of important things in the world they're not that entertained with. And so if we're going to get them to trade on the important things that they're not so entertained with, we're just going to have to pay them,

Speaker A: increase the value to make it more. But let's use the low value one or the, you know, the wedding one is a good example. How many of us, we've been to weddings and you're like, oh, uh, this marriage is never going to last. Right. And if we could put money on it, maybe it would give color to the bride or groom.

Speaker B: That's not actually very valuable, uh, to tell them how long the marriage will last at the wedding.

Speaker A: Exactly. It should be before, when you're dating. Perfect.

Speaker B: When they're dating, what's the chance you'll get married? And if you get married, how long will that last? That's when you want to give the advice.

Speaker A: Yeah, that's a good point. Yeah. So let's. That's what I do. A dating example is better than actually what I. So let's use a dating one. I'm about to date a girl and, um, my buddies, even if it's only 20 people, will put odds on it. And that should give me that wisdom of my buddies, should give me actually an informed opinion, uh, in a way. And they will each profit depending of the outcome as well, in that perspective.

Speaker B: Indeed. Although, again, most people don't do this in part because they don't necessarily want to hear the answers.

Speaker A: Yeah, exactly.

Speaker B: So you need a world where people want to know the answer. This is true for prediction markets all over. So, I mean, this is the thing I learned about the world from thinking about prediction markets. I first came in and say, look, the world seems to want information. This will give them information. Great. Let's do that. And then when I started to offer prediction markets to people, I started to realize, oh, people actually don't want information about a lot of things. They want to give the appearance that they are interested in information, but they often want to manage narratives more than they want to learn more. And that's one of the main obstacles to introducing these in for profit firms. Interesting is that many managers see themselves as trying to manage information and perceptions and this is threatening, uh, to be an out of control force. So an example I like to give is imagine the C suite, the big table where all the C folks sitting around the table talking to each other. Imagine at this table we put an autist, we put a person who knows the company really well, but whenever a topic comes up, they just have no sense of what anybody wants to hear and what will bother anybody, what the agendas are. And they just blurt out the things they know about the company. Whenever a topic comes up, I predict this person won't be allowed to sit at the table very long. Okay, that's just a fact about corporate politics, right? If you're going to sit at the table, you can't just know things about the company. You have to be aware of what people want to hear and what the issues are. Okay, but that's what a prediction market is. Unless you do something clever with it, it just blathers and tells you what it thinks without any sense of who wants to hear that. And that's typically a problem.

Speaker A: Super interesting. I mean, is there any topic that you would not trust prediction markets? And I'm not saying that where there's no incentives or the cases where people don't want to hear it, but is there any situations in life, in the, in information gathering that we should not trust prediction markets?

Speaker B: Well, not trust is a different standard than not use.

Speaker A: Perfect.

Speaker B: So I would say if you just have a bunch of people who trust each other, they can just talk to each other and ask each other questions. And that's a lot cheaper than bothering to make a market. A market is an extra overhead that can be worth the extra overhead when the question's important enough or you have enough dysfunction or inability to talk honestly to each other. But when you start to perceive that people aren't being fully honest, uh, then you might be willing to pay the overhead of a market. So that's a reason why don't bother on small questions. When you trust you. And of course that creates a problem. As soon as you suggest let's have a prediction market, people say oh, you're suggesting we can't trust each other. Yeah, you are, kind of. And that's an obstacle there. Uh, if you could just believe each other, you wouldn't need this mechanism. And I guess another thing is, say, I don't know, say you want to get somebody to reveal their password. You could set up a betting market on their password. But. But why should they reveal their password in your betting market? And if they want to keep their password secret, they'll keep their password secret. If you have somebody who just really has a high value of keeping a secret and they're the only one who knows, offering the betting market is not really going to help there because they're just going to keep their secret, which is fine. The other big thing is actually we have a lot of big topics we talk about in the public, where it's a common pool. That is we all want to know more, but none of us really want to pay for it. We want other people to pay for it. And so this idea of the product where the customer is a person who wants the information, we say, hey, who wants to pay for this? And everybody goes, let everybody else pay for it. So when you've got a common question that lots of people are interested in, uh, unfortunately that makes it harder to entice anybody to pay for it. You might get decent estimates as a result of their just finding it fun to bet on. But, but, uh, that's why a lot of public policy questions are actually more of a problem here. That's why I want to go for the private policy questions, your personal life, your company. Because there, if you don't pay for it, nobody else is going to pay for it. So pony up or not.

Speaker A: It's interesting. It needs to be nascent for me to ask people, and I want to hear the answer as well. So very, very interesting. But I can see on the policy side, I mean, years ago, and you correct me on the year, but, uh, you work on something called the policy analysis market right future map, where, and my data may be a bit wrong, but it was on the Middle east back in the days ago, where it's ironic we're back at the same problems now, but it was basically making people making bets on what was going to happen in the Middle east. And it was shut down due, uh, to policy and, uh, Congress stuff. Do you believe the situation now is different or the same powers to be that block you 20, 25 years ago would do it as well today.

Speaker B: So we actually did that project 10 years later without people complaining about it because they didn't hear about it. So in fact there's this guy, uh, north who was in the boss chain above us and people wanted to get him and they got him through our project. Interesting. So there was this big press complaining about our project because they wanted to claim about him.

Speaker A: Interesting.

Speaker B: But that didn't happen 10 years later. So nobody was trying to get somebody fired above us. So that didn't happen. So we actually did that project ten years later. We developed a lot of technology called combinatorial betting markets. And there's a lot of technology out there that isn't being used yet that's potentially able. And we're happy to walk through that if you like. But we actually did that later. Now another example you should ask me about is maybe the Hollywood Stock Exchange.

Speaker A: Yep, of course, yeah.

Speaker B: Uh, in the aughts, the place called the Hollywood Stock Exchange. It was a play money market. It was doing very well predicting movies and Hollywood events. And the principals there went to the millions of dollars of trouble to go through the hoops to get the CFTC to approve them for trading real movie futures. And the movie industry executives learned about this, were upset, lobbied Congress to ban movie futures. And that's why we don't have movie futures today. So in the 50s, Congress banned onion futures for some reason and in the aughts they banned movie futures. And so that's another example of what could have been if they would allowed to continue. We would have had this sort of thing 20 years ago. And in the last few years, a lot of people are upset and complaining about prediction markets, but somewhat randomly, they're

Speaker A: somewhat defensive because the movie features are very interesting. Right. It allow people to actually make bets on what the outcome would be if there was a movie with, I don't know, Ben Affleck and George Clooney or whatever. And you could argue that would actually create more, uh, the price discovery, people lending for movies and stuff. It would make everything more efficient, basically.

Speaker B: You might. But the movie executives thought that it would limit their ability to control the narrative. So at the moment they market in order to give the impression that a movie might be popular on opening weekend. And these market prices would just undermine that. Right. If the market says nobody's gonna like this movie, then they won't even get people there on opening weekend and they'd rather be able to control the narrative. So that's just. Again, our world is full of people who are more interested in controlling the narrative than they are in finding out more information.

Speaker A: It's super Interesting. And I recommend any of the listeners to look into the Hollywood, uh, uh, the market you mentioned. I think it was super interesting how we got closed shut down as well, which I find is very, uh, I mean the policy angle there to shut it down. I think it's different, it's a different question, but it is what it is on the policy side as well. Um, I think many people in crypto don't know this, but there's been a lot of some of the major figures in the crypto industry, Vitalik Buterin from Ethereum being one. Um, in a lot of the conversations we've had around decentralized autonomous organizations daos, they refer actually to a lot to your work as well. Um, do you believe that in the context of, let's say decentralized organizations using prediction markers to dictate policy could work? And the counterargument, I'll make that and want to throw it to you is doesn't make a bit too communistic. Right. Where it's a wisdom of the crowds deciding, but then it's not going to go in the right direction. People will look to take short term decisions. Uh, what's your view on that? Or you believe we should be able to run communities using models?

Speaker B: First, I'll brag that I, uh, did work on automated market makers for prediction markets very early and then the early crypto market makers were based on my automated market makers for prediction markets. So of course they've gone another direction since then. But I'll brag that was influential for crypto. The crypto automated market makers defi up. Right. But that was just a variation on the ones I had done for predictions. Okay. So I think organizations can and should be governed more using betting markets. I gave you the example of firing the CEO or not, but you could more generally have a system where key decisions are just generally made by the market. And there's a crypto company at the moment called Metadao that has been experimenting with that for now four years. So they've done at least roughly 100 decisions that way. And I think that's going well. I know a number of other crypto organizations that have experimented with prediction markets. And of course as they become a bigger potential thing, people who are concerned about them are going to come up with complaints and we should walk through these complaints, like to say how plausible they are. Right. So you said short term. So there's this story that the market is short term. I just don't think that's true. Uh, there is an adjacent thing that's true. Which is um, actually if you look at say private equity, uh, private equity actually does better in many ways than public firms. Um, because when you have a really big important choice to make, private equity has concentrated ownership which will then look at those choices really carefully and then make them well. Whereas in a public firm, uh, if you're the manager of a public firm, you have to impress the stock speculators who don't know as much as you. And so often the speculators are going to be skeptical about your claiming that we should do some big investment because that's usually not a good idea. Public firms more have to pander to the market in the market ignorance relative to private equity. I uh, think futarky is my name for using these markets for governance. And I think Futarky has great promise against in comparison with a great many other common ways we do governance, but maybe not quite against private equity because private equity is pretty damn powerful. So we basically see in the world that when a company is uh, some big decisions to make, it's usually private or you take it private so that you can have private equity really focus on these key big decisions and get them right. When you finally reach a stable situation where they can milk the cow as they call it, then you take it public and you give it to public managers who can basically continue the process. We're going, they don't need to make any big decisions. And now the capital there, private equity capital can be reallocated to other more important private equity things. So I'm not going to claim necessarily that futarky will beat out private equity as a governance mechanism, but I think compared to other public companies, it'll help public companies do better. And for other organizations that are not for profit, it'll do substantially better because you can have these markets have other outcomes that you're trying to achieve other than profit. So that's a key advantage of decision. But again the Metadao has been experimenting with as a for profit, uh, but even there they have this key question so the managers of companies. So here's some stats. When a for profit company says, the CEO says I want to raise capital, I've got the board's approval and I don't need the shareholder's approval. Stock price goes down 2%. Market says that's not so good. When the CEO says I'm going to raise capital, I've got the board's approval, but I need shareholder approval too, the price goes up 2%. People say, yeah, good, we need shareholder to Take a look at this. When activist investors buy a bunch of share of the company, say, we're going to, uh, try to reform this company, price goes up 6%. People say, yeah, that sounds good. So for public companies, often the market is a little wary of giving the CEO too much discretion because that could go bad. So these few tarchy decision markets can be a good substitute for a shareholder vote. They're a lot cheaper, a lot faster, and a lot more flexible. And so they could sit in that role of being the check. Which means we don't quite trust the CEO to make all these big decisions. We'd like somebody to check on that, but the CEO doesn't quite like that. So as you may know, most firms have poison pills in effect, where they can prevent a hostile takeover, but that's bad for shareholders. So you might ask, why do shareholders allow firms to have poison pills? Because typically, early on in the firm's history, the founder didn't wanted a poison pill and said, hey, if you want me working on this, you have to have a poison pill. So founders often get their way even at the cost of investors in terms of corporate structure. And that's also an issue for prediction markets. So, for example, Metadao made the following switch and you can think about how good an idea it is. They said, okay, in order to pass a proposal, it has to have the price if the proposal passes be higher than the price if the proposal fails. But we're going to actually give a preference for CEO or founder proposals for them. It can be down to 3% worse and we'll still pass it. But for people who aren't the founder, there has to be at least 3% better to pass it. So they create this 6% differential where the threshold for the founder proposal versus the outsider proposals, they say, which I believe that that's making founders more interested in using this mechanism because they can tell everybody, see, we've got the disciplinary mechanism that's going to check us, but then they make sure to tilt the table a bit to make it easier for them to get their proposals through and harder for other people to, to get there for falses.

Speaker A: Interesting.

Speaker B: But you can see founders have typically had so much power to shape these things that you can see why you might compromise with them and give them a lot in order to just have any sort of oversight mechanism. Because typically they don't want, for example, they love poison pills because they don't want hostile takeovers, even though hostile takeovers would in fact on average be good for investors.

Speaker A: Well, this is a typical, I mean you could argue we're seeing this with Elon Musk and the control he has as a company. So you can also argue on a policy level as well. Many people would rather live in a benevolent dictatorship like in many countries, the Middle east, where there's a decision making, things move fast, rather than other countries where it's, let's say, less optimal. You know, uh, from, from that perspective. Uh, one last question as well, Robin. Actually two more M.1 of them you, you were really behind um, the lmsr, which is a logarithmic market scoring rule, which is from what I understand by the way. I was not aware that the work you did contributed to the amms. Right. Automated the market making tools that we have, uh, uh, in uh, defi protocols. And I knew there was a lot of actually work in the dao space that was uh, based on a lot of your research. I mean really, thank you for contribution to the crypto space. But you did a lot of work on the um, let's say pricing mechanisms with the lmsr. How do you see these evolving in the next couple of years? Assuming that prediction markets become more, that's called mainstream.

Speaker B: So you have to go back a ways. Remember long ago the regulators said only big markets are allowed small markets. There's no point because they can't hedge much risk. And in the big markets you could just have a person be the market maker. And there was plenty of money to pay that person to be a market maker. So you had smart persons being market makers. I said, okay, I want to have small markets, but I can't afford to have a smart market maker here. I want a market maker because that'll help people trade. How do I have a dumb market maker? And so I needed a dumb safe market maker. So safe means, okay, it's not going to make money, but it can't lose more than a certain amount. I designed a market maker such that uh, there's just a limited amount it could lose in the worst possible case, no matter what happens, it can't lose more than a certain amount. And I said, look, that's a nice safe little market maker to put on a small market because it can be dumb because it's got this nice safety. Now my safe market maker was actually just a reinvention of something in the prior literature I just translated to the prediction market context. So that wasn't really my idea, but that was the whole point there is just to have a simple dumb thing. Now in our world today, if you want to have a lot and a lot of markets, you don't want somebody smart there, then this is still an attractive idea. Just a simple dumb thing. But at the moment, for say, Calcium Polymarket, they have a smaller number of markets and they're willing to pay people to be market makers. And that's actually the typical way it's done. So what they do is they say, okay, who's willing to offer the following spread? And over the following period, your following spread hold an auction. Who will charge the least amount to be willing to offer the spread? And then whoever does that is the market maker. And that's how they do it. And that person can do whatever formula they want, which is fine. My LSMR was again designed to solve the simple problem of how can I have a stupid market maker that can only lose a limited amount now? But here's the thing interesting. I could prove about that stupid market maker. I told you about combinatorics. So let's imagine we have, I don't know, a thousand questions. And now I want to let people trade on all combinations of these questions, any logical combination of and if or not, whatever. And I want to trade on all those combinations at the same liquidity. I traded on each of the base questions. So say I have some liquidity. I'm willing to put Markovator on each of the base questions. A thousand questions. And now I want all combinations which is really, if These are binary 2 to the thousand state space, okay, it's really a lot. And I want that same liquidity and all of that. How much more does that cost? And the answer is nothing. That's a magic of combinatorial markets. You can have as much liquidity on all possible combinations of these variables with the same liquidity as each space variable has for no extra cost in terms of the cost of the market maker.

Speaker A: Interesting. It's going to be fascinating industry, really.

Speaker B: I find that someday that'll matter. When people actually do these combinatories, someday they will be combinatorial financial markets. That's what I, you know, you've heard it here first, perhaps, and maybe not a ways away. But at the moment you have these separate markets that are just separately run and you have to trade separately in the different markets. But there could be a single joint market where you could trade all combinations of any of them all together, all at once.

Speaker A: Interesting. Uh, you know, one thing, it's maybe a very random question, and I don't know if you know the answer, but I was researching for the show, um, I saw that there Was there's been a link between you and Hal Finney? Is that possible?

Speaker B: I knew Hal from a long time ago. Yeah.

Speaker A: So Hal Finney for the benefit is obviously many believe he could be Satoshi.

Speaker B: Indeed.

Speaker A: It was my guess.

Speaker B: It's my, my guess too.

Speaker A: Interesting. So you were dealing with Hal Finney back in the day.

Speaker B: Right. So I was in a world of tech futurist people in Silicon Valley. It was a science fiction club that he went to and various parties. And uh, he was into cryptography and crypto anarchy as they called it. And I thought that was cool, but I wasn't so into that. That wasn't my topic, so I didn't follow it that closely. But he and Nick Szabo and Tim May and other people were there talking about that. And when I look back at those people and I say who could have done this? How's the obvious person really? I don't want to insult Nick or Tim or the other people, but Hal had it together.

Speaker A: What sense? I mean, um, uh, you know, from all the research and even my last book I talk about actually that I also believe it was Hal Finney. Recently there was though, uh, there was Satoshi was writing emails while Hal was running the marathon.

Speaker B: Recent documentary that suggests it was a teamwork between Hal and somebody else, which not crazy, but I would guess that Hal's part of the team.

Speaker A: And what was it in him that you believe made him Satoshi?

Speaker B: So as you may know, there was this thing called PGP back in the day and it was an effective cryptographic thing and he was one of the main software persons behind that. And then he was just organized. That is, look, there's a lot of people you meet and they're interesting and provocative but uh, not always so organized or methodical. Hal was just well organized person. He was somewhat, you know, shy, not shy, but modest. But he was very clearly devoted and had a strong, you know, passionate thing. But he was also just organized and could do stuff interesting. He would definitely be able to keep a secret. He would able to organize his projects, do it, not tell people and keep the secret. That and of course the fact that he's dead means he wasn't tempted for the last few decades to reveal the secret. So.

Speaker A: But what I mean is I also believe, I think the odds are it's him. But there was this um, emails that he was running a marathon. While emails were being sent. The big question is could it be with somebody else like Adam back from blockstream recent documentary is saying.

Speaker B: But uh, yeah, the other Claim was that it was somebody else who died also.

Speaker A: Yeah, yeah, yeah. I just forgot his name now. Yeah, yeah.

Speaker B: So that's also more plausible. That is. It is pretty implausible that whoever did this is still alive.

Speaker A: Interesting.

Speaker B: It's a pretty big temptation at this point.

Speaker A: Yeah. Yeah, interesting. I mean, it's really random. I didn't expect to ask this, but I was doing research and I saw that he really.

Speaker B: So he did some guesses. Posts on my blog, for example.

Speaker A: Yeah, exactly. That's what I saw. Yeah. Wow.

Speaker B: Um. But, you know, so I'm honored to have been so. So again, I guess I was there with people near the founding of Bitcoin, but. And I was there with people. The founding of the World Wide Web.

Speaker A: Yeah, exactly.

Speaker B: When we were making the web happen long ago. And so I can see. But I've learned some things basically about people who did really big things, which is typically, they don't get that much reward.

Speaker A: Interesting.

Speaker B: So I learned with the World Wide Web is that the people who made the World Wide Open happened. They didn't get much. They foresaw something other people didn't think was going to happen. They could see it, but they couldn't actually get much personal payoff from it. The people made big payoff for, say, the people who made Netscape or whatever. They actually made a product that turned out to be something they could sell in the short term and get revenue. And if you were an investor or principal in one of those first firms, you could make profit. But if you just could see something coming and foresee it and maybe even make something and contribute it to them, you don't get paid for that. And so I learned that if I'm hoping to influence the future, I still have hopes, But I don't expect necessarily to get paid. I might expect some credit. That'll be okay. And Hal didn't get paid, and these people, again, who founded the World Wide Web didn't get paid. And I still have hopes. But you might ask me, how can you be so presumptuous? This thing, you could have this big impact. Because I'd say, look, lots of people could have a big impact and choose not to because they're not actually going to get paid much for it.

Speaker A: Interesting.

Speaker B: We're not actually paying people who do big things in our world that much. So, yeah, that's why you, as a more ordinary person might think you could do it.

Speaker A: Interesting.

Speaker B: Because mostly it's not about, ah, are you the best? It's about, does anybody even bother?

Speaker A: Interesting. Do you Believe that the prediction markets and everything you've been working on the last 40 years would have taken off without crypto. I mean, you think about the settlement layer in the back end and everything that provides.

Speaker B: Right. So I mean, you have to ask, say about the founding of Kalshi, obviously, Poly markets crypto. Yeah, but Kalsi's not. Maybe Kalshi wouldn't be there if not for the crypto. I guess you'd have to more look into the founding of Kalshi to ask that. But honestly, here's the best thing I will say about crypto is m. Most of the things, uh, people hope to get out of crypto were kind of there at the beginning with bitcoin. So most of the investment that's happened since then hasn't actually received that much traction in terms of getting big things to happen the world. But the big advantage that happens from crypto is when people make money from crypto for whatever reason, the story they have to tell themselves about why they deserve this money makes them do interesting things with the money.

Speaker A: Interesting what sense?

Speaker B: Like, uh, like interesting projects like life extension or, you know, all these sorts of other projects. A lot of interesting crypto projects happen because the people who made money in crypto, their concept of themselves is as an innovator trying to change the world through projects. And they fund interesting, interesting projects, which

Speaker A: a lot of founders have, even people interviewed over the years. Now they're into longevity or doing that. And it's actually encourages people who make

Speaker B: money in real estate or dentistry, they just don't do such interesting things with the money. Okay, I'm glad they're there. People should make money in real estate and dentistry, but the. What they do with the money later, isn't that impressive?

Speaker A: Super. Interesting. I have, uh, you know, a tradition, professor, when my bell is here. So basically I'm gonna ask you quick questions and.

Speaker B: All right.

Speaker A: One or two word answers.

Speaker B: I don't have to answer, you know.

Speaker A: Uh, yeah, well,

Speaker B: this doesn't force me to answer. I may answer. Let's see.

Speaker A: So here we go. Let's kick it off. So, um, if you had one message to give to the CEO of Calcium Polymarket, what would that message be?

Speaker B: Good job. That was fast.

Speaker A: There we go. Um, uh, if you could build today a new prediction market platform,

Speaker B: who will

Speaker A: be your ideal co founder of any of the big CEOs that we have today in the market?

Speaker B: Whoever's willing to do it. I'm happy to work with any big top people, but I want to do these Decision markets, the futarchy, the decision advice. And, uh, as you know, these projects just go much better when you have a really good person with a good track record. And I'm willing to defer. I'm willing to compromise a lot. You should be willing to compromise a lot to get a good founder. Absolutely.

Speaker A: If you're not an economist, what profession would you rather be?

Speaker B: I could have gone up through other channels to become the sort of scholar that I am. I could have been a sociologist. I could have been a physicist, computer, computer scientist. Lots of other paths. I could. Once you get tenure, you don't have to be whatever you were. You can just spread. You can just go in all the other directions.

Speaker A: Any, any student that is interested on prediction markets, what course you believe they should, they should take at university.

Speaker B: Yeah, there's not going to be a course.

Speaker A: Nothing there. Um, if, um, what do you do when you're not busy researching on this topic? What do you do on your weekend when you're not working on prediction markets?

Speaker B: I mean, I allow myself to just read a lot of different stuff. I'm intrigued by a lot of different topics, and that's where I allow my. I tell myself it's for breadth and maybe I'll discover something. Mostly I just like to read a lot of different stuff.

Speaker A: Uh, you've written about tremendous amount of topics. Actually, I discovered you first on the Lex Friedman podcast a couple of years ago. Talking about aliens.

Speaker B: Yes, exactly.

Speaker A: I mean, it's really interesting how, uh, you have so much horizontal depth. Depth on that side. What's exciting you the most right now outside of prediction markets?

Speaker B: Cultural drift. Um, briefly. Humanity's superpower is cultural evolution and we broke it.

Speaker A: Interesting.

Speaker B: And civilization's gonna fall unless we figure out how to fix it. And we probably won't fix it. And so we'll probably fall. And that's pretty scary.

Speaker A: I think we could have a whole podcast on that. We could indeed. Over beers. And to finish it off, um, Robin Hanson, uh, the associate professor at George Mason University. Uh, I have to say this was super exciting. My traditional question, whoever comes on my TV show, my podcast, if you could have lunch or dinner with one person, dead or alive, lunch or dinner with one person, dead or alive, who would he have lunch or dinner with?

Speaker B: Elon Musk.

Speaker A: Elon Musk. Why is that?

Speaker B: Has. He's done some spectacular stuff.

Speaker A: That's absolutely the case. Well, hopefully, uh, this was an interesting episode. I mean, I have to say, uh, I love that. This was definitely one of my favorite episodes. We've ever done, uh, in the last decade of the show. Thank you very much, everybody. Again, if you like the show, make sure to follow and subscribe. It helps us get more exciting guests like we had today with Professor Hanson. Professor thank you very much. And how can people find out more about you if they want to discover,

Speaker B: learn more about your Google my name.

Speaker A: There you go. Robert Hanson. Robert Hanson, professor at George Mason. Thank you very much. Thanks for being with us. Thank you very much, everybody, and hope this was interesting and useful. Thank you. This episode was brought to you by ACX Compliance. Looking to set up operations in the uae. ACX Compliance Licensing team can help you with all your needs for your VARA or ADGM application and ongoing support. Thinking about the UAE? Think about ACX compliance. Acxcompliance.com acxcompliance.com M.