Pod Insights a16z Podcast Robin Hanson on Prediction Markets, Gambling, and the Future of Forecasting About this episode Theo Jaffee and Sophia Puccini speak with economist Robin Hanson about prediction markets, gambling, and why he believes speculative markets are one of the most powerful tools humans have for aggregating information and forecasting outcomes.
The conversation begins with Minnesota’s recent law criminalizing prediction markets before expanding into the broader backlash surrounding platforms like Kalshi and Polymarket. Hanson explains his long-term vision for “decision markets,” where markets could help guide choices made by companies, governments, and even individuals.
Along the way, they discuss sports betting, games and human psychology, futurism, AI, and Hanson’s broader work on how societies misunderstand risk, incentives, and coordination
Transcript 0:00 Speaker 00 Well, so, start at the beginning. The basic vision is that speculative markets are shown to be a unmatched mechanism for aggregating information and telling us about stuff. And initially, most people who come to this area think about, let's have markets on the big topics in public conversation, in the news, in politician's speeches, in policy wonk, you know, reports. And that's what you're seeing initially here with Kalshi and Polymarket as well. But I think most of the value is actually advising decisions for individuals and organizations, not in the big public conversation topics. We could advise business ventures like that with conditional stock markets. So, for example, we could have a stock market in a company that says,
0:45 Speaker 00 what's the price of this company if the CEO stays in power past the end of the quarter? And another, what happens if the CEO leaves by the end of the quarter? Those would give you two different stock prices. The higher one would be the advice about what to do. There aren't any decisions companies make much bigger than that.
1:02 Speaker 01 For decades, Robin Hanson has argued that prediction markets are one of the most effective tools humans have for aggregating information and forecasting outcomes. Not just for elections or sports betting, but for helping companies, governments, and individuals make better decisions. That vision is becoming more relevant as platforms like Polymarket and Kalshi bring prediction markets into mainstream culture. But it's also triggering backlash, including new efforts to criminalize or restrict these systems. At the center of the debate is a deeper question. Are prediction markets just gambling? Or are they a new form of social coordination and knowledge discovery? Theo Jaffe and Sophia Puccini speak with Robin Hanson
1:46 Speaker 01 about prediction markets, futurism, games, and the future of forecasting.
1:54 Speaker 02 So today, we wanted to talk about the new law in Minnesota, which makes it a felony to operate a prediction market in the state. Specifically, it is a felony to create, operate, or advertise a prediction market, and violators are facing up to five years in prison for this. Minnesota is the first state to pass such a law. The CFTC, part of the federal government, recently sued to block the law's passage. But as far as I know, it remains in force now. So how could this have happened under our political system?
2:31 Speaker 00 Well, so as you may know, for a long time, many key political questions in our country and elsewhere have been about, at what level do we make decisions? People often want them to be at national level or local level, depending on where they have more support. And recently, we had a regulatory ruling at the national level that allowed a lot more of these things. And that was a problem for, say, many people who did sports betting, regulated by the states. This regulation was displaced, and now they allowed these national competitors, and they didn't like that. So there's economic interests that would like state regulation instead of national regulation. And then there's just people looking for a political hot ball,
3:16 Speaker 00 something to fight about. And many people didn't like this change at the national level, and they want to show their opposition to it by trying to push for state regulation to displace national regulation.
3:30 Speaker 02 How do you start to convince the public more broadly that this technology is actually useful? Because there seems to be this very persistent conception of prediction markets as something between like wasteful gambling nonsense or immorally making money off of tragedy. Those are sort of the two attacking angles I see.
3:51 Speaker 00 The history of all financial markets is that they were pretty much all once illegal. As gambling or usury or something. And then we carved out exceptions over the period. And the main reason people came to accept exceptions is just that, you know, the world seemed to keep going and somebody wanted them and saw them as valuable. So, you know, the usual proof is just somebody somewhere sees something as valuable. Other people accept legitimacy of that, saying, okay, you seem to find value in it. So I guess you should be able to continue. But that requires that somebody find value and that they are seen as legitimate. So, you know, most stocks, options, you know, commodities, insurance, all of these things exist in our world.
4:36 Speaker 00 There is a sense in which they are all gambling. And the question is, is that okay? And the reason it's okay is because, you know, we've seen long enough years of people doing it that other people seem to be okay. But some of these things, when people look at them, they just go, oh, well, that couldn't be serious. And some of these don't look very serious. They look more like they're being done for fun. And that's more vulnerable to people saying, oh, well, if you're just having fun, then I don't approve.
5:06 Speaker 02 Right, so you wrote an article a few months ago called Prediction Markets Now. What do I think of calcian polymarket specifically? And you said you're mostly interested in the potential of stuff today to enable and cause that future vision. And said, interestingly at the end, of course, if these systems induce a backlash that gets them outlawed or drastically shrunk, that may plausibly block or at least long delay my vision, which seems to be happening right now. I see many people complaining about these things. I fear a new prudish temperance movement may shut them down and as a side effect, shut down the more promising markets that I've envisioned. So how does your ultimate vision for this stuff differ from what we have today on polymarket and calc?
5:47 Speaker 00 Well, so start at the beginning. The basic vision is that we could have speculative markets on more topics and therefore know more about more topics. That is, speculative markets are shown to be a unmatched mechanism for aggregating information and telling us about stuff. And the promise then is we could just learn about more topics if only we would have markets on more topics. So that's the promise I'm hoping for. And initially, most people who come to this area think, yeah, that's great. And then they initially think about, let's have markets on the big topics in public conversation, in the news, in politician's speeches, in policy wonk, you know, reports. And that's what you're seeing initially here with Kalshi and Polly Market as well.
6:30 Speaker 00 They're just going for whatever topics people are talking a lot about and maybe wanting to trade. And so that it makes sense that they're doing that. But I think most of the value is actually advising decisions for individuals and organizations, not in the big public conversation topics. And so that's where my longer term hope is that we will get to those. But these markets today are helping us move in the direction, at least if they don't get too big of a backlash, because they're making, you know, lowering infrastructure costs, they're creating legal precedents, customer familiarity, all those things, if they can accumulate, will in fact, enable all the other things I want to do.
7:09 Speaker 02 So how would a market become large and liquid enough to be useful if its purpose is just to advise a single individual? Like, it seems like only a few individuals would be able to have that.
7:22 Speaker 00 Or an organization. So like, so for example, we have stock markets now, and those do tell you like which ventures are more promising when a stock price is higher, that says this venture could use some more money, and that it could, it should do more stuff. But we could advise business ventures like that with conditional stock markets. So for example, we could have a stock market in a company that says, what's the price of this company if the CEO stays in power past the end of the quarter? And another, what happens if the CEO leaves by the end of the quarter? Those would give you two different stock prices. The higher one would be the advice about what to do. That's giving advice to a company about keeping the CEO. That's actually a pretty, that there aren't any decisions companies make much bigger
8:07 Speaker 00 than that. And so that's a high value decision being advised by a market. And many other decisions that companies make, mergers, restructurings, raising more capital, all of those sorts of decisions could be advised by markets like this. So we're talking some pretty big decisions. Big government decisions could be advised this way. And yes, eventually, we could get down to personal decisions. But if we can lower these costs of these markets, then it'll make sense to apply them to more things. All technology starts out expensive. And initially, you apply it to the biggest value things you can find. And then as you get more practice, the costs come down and then you spread its range of application to lower value, but still higher value than cost applications.
8:49 Speaker 03 Could you tell us a little bit about decision markets? I read on your Substack the other day, but it's essentially the idea that like if you have markets that are tied to like personal outcomes that are attempted to mend the like the manager agent problem, like how would that work out?
9:12 Speaker 00 So I just mentioned one for fire the CEO. That is a decision market and that is giving advice to the company, to the board of directors in a way that's hard to mess with. That is, you know, it's a very political decision whether to keep the CEO. So obviously the CEO themselves are going to be trying to manipulate that context. They're trying to lobby other people. People on the board are going to get lobbied. You know, if you have a report written, that report is going to be biased by who hired them, et cetera. How do you get objective information about whether to keep a CEO? So these markets are remarkably neutral and hard to manipulate and they do give you well-informed objective information that overcomes these agency problems. But we could do it not just for companies eventually. So let's have more fun.
9:54 Speaker 00 Let's at the individual level, imagine you're not married and you have a set of people you might date and you wonder for each person I date, what's the chance that that will last a while? So we can make betting markets on for each person you date, if you date them, how long would that relationship last? How many dates in the next year, whatever would you have after that initial? And that would be market advice to you about who to date. We could also for young people have markets on, should you go to college? Which college you should go to? Which major should you get? And we could estimate life outcomes, conditional on those choices you make. The colleges themselves could say, should they admit you? If we admit you, what's the chance you'll graduate? GPA? Again, these are big, important decisions individuals make, and they're all open in principle to this sort of market advice.
10:39 Speaker 00 If we can get the costs down, get legal acceptance, get infrastructure, you know, established, and most importantly, people familiar and comfortable with using this.
10:50 Speaker 02 So I wanted to pause on that because there actually is a real-life empirical example of prediction markets applied to dating, which was manifold love.
11:00 Speaker 00 Yes, indeed.
11:01 Speaker 02 Manifold markets ran manifold love, and it didn't work. They had to shut it down because the amount of people for a given couple who had context on that couple and could reasonably infer how long their relationship might last was so small that it wasn't enough to make the markets liquid.
11:20 Speaker 00 Well, I think in all innovation, what you have to notice is you have some abstract ideas, and then you have lots of more specific instantiations if they're possible. And most innovations about searching in the space of the more specifics to make the abstract idea work. So what you saw is that a particular thing didn't work in a particular context at a particular time, but that doesn't mean something like that won't work later. You know, the history of almost all innovation is littered with precursors that didn't quite work out. And then eventually, something takes off and manages to find the right combination of stuff. And so that's where we are here. So this general idea has been around for quite a while, and no particular attempt should you have high confidence in.
12:02 Speaker 00 What you should have more confidence in is the exploration of a large space of possibilities, and let's figure out what works.
12:10 Speaker 03 So what do you think is the value, if any, of like very arbitrary markets that seem to be just based off of pure chance? So for example, weather markets on, you know, polymarket or calcie, sports, which accounts for like 80%.
12:26 Speaker 00 So the weather, in fact, in this Minnesota case that we're just talking about, the reason why we're talking is Minnesota said, oh, we don't want prediction markets. They passed a bill banning it, and then they passed an amendment right after saying, oh, we've got to allow weather markets because they got pushback from people in Minnesota who use weather markets, and they want those markets to hedge and get information. So that's actually substantially economically valuable.
12:49 Speaker 03 Right. I think, well, with weather markets, I'm not super familiar, but I assume it's similar to like, you know, it's basically like you have to invest a lot, a lot of time to become profitable in such a market. But with sports, it's something that's fairly arbitrary. Like, what do you think is the value, if any, of having a sports market? Like, do you think that this is like an inevitable emergence? Whenever you have free markets, there will always be some sort of like casino-ification.
13:21 Speaker 00 I'd say, you know, a technology can be used in many different ways, and then different people have different purposes. So like, you know, stickums, the little yellow stickums, that's bad glue. People who were trying to design glue and they came up with the kind of glue and they go, this doesn't work very well. And somebody else thought, well, yeah, but bad glue can make good stickums. So the world is full of things that can be used in many different ways. And the thing is to understand the different ways it can be used. So speculative markets are an abstract thing that can be used in multiple ways. Right? So obviously, we've been talking about, say, about the information function. They can help people learn and get information about things. Secondly, they can hedge risk.
14:01 Speaker 00 Much of financial markets, the standard regulatory rationale is that they help people hedge risks. But there's other things people get out of these things in history. For one thing, people have fun. What sort of fun? Well, they like action, they like the chance to prove themselves. And that's long been a reason why many people have had betting markets. And it's also been a reason why many people trade in financial markets.
14:25 Speaker 03 They're adrenaline markets, basically.
14:27 Speaker 00 Exactly. Many financial market professionals got in there because that was an adrenaline rush. They wanted to have the action and a sense that they were good and they wanted to prove themselves. And that's attractive. And, I mean, that's not only fun, but people like complimentary fun. That is, when you're watching a sporting event, it is more fun if you're betting.
14:48 Speaker 00 You are more involved in the sporting event when you're betting on it. That makes that event more interesting and more engaging to you. That's a value and that's what some of these people are achieving. So we have many kinds of fun in the world that we have disapproved of. So the world has often shut down fun and say fun should not be allowed. And maybe there's good reasons for that, right? But our world in the last century or so has been more pro fun than the world used to be. We've allowed more kinds of, you know, sexual practices and, you know, you know, sporting activities and all sorts of, you know. Look, we let people try to be actors and musicians and athletes. We, that's pretty low odds, but people seem to have fun trying to do that.
15:30 Speaker 00 And we're now kind of okay with people, you know, as in long ago, actors were not very well respected. It was not a, you know, respectable career and in part because the odds were low. And also, you know, the sort of people you're hanging with and, uh, but in our world, we tend to think fun is more okay, except I guess people are a bit prudish about gambling or betting. But again, the point is just to be honest here about the different values. And then maybe the different problems and how to mitigate the problems or reduce them. But as I said, you know, centuries ago, the typical response to the possibility of gambling was just to ban it all. And that sort of banned pretty much all financial markets. And over and over time, we allowed more financial markets for that rationale.
16:13 Speaker 00 Sometimes we allowed gambling just for the fun, but more limited. For example, horse racing. The idea was that for military capabilities, it was good if the public understood horses well. And especially which ones were strong and could race, you know, and could be strong in a, in a contest situation of having to do a lot fast. So it was believed that allowing betting on horse racing was good for the military capability of a society. And that's why there was a lot of horse racing where there wasn't a lot of other gambling allowed. That was a reason for horse racing, right?
16:49 Speaker 03 Yeah, so you can imagine like drone betting.
16:53 Speaker 00 Sure.
16:54 Speaker 03 As a way to accelerate military technology.
16:57 Speaker 00 Right, you might imagine we create more sports related to new military technology so that people could, sometimes people said video games, some video games are good for that. There are video games that the military has often thought is good for training people and selecting people for the military.
17:12 Speaker 03 Right.
17:12 Speaker 00 And they're fun, but they also have this other purpose.
17:15 Speaker 03 Right. Have you thought much about the societal origins of games? Like, games seem like to be pretty inherent to like the human race and the human experience.
17:28 Speaker 00 Well, you know, I've been a big board game fan for many years. So I've always pondered why I like them and what was different.
17:36 Speaker 00 But since then, I've learned a lot about the literature. So basically,
17:42 Speaker 00 humanity often just creates sub-worlds that have a set of rules and then we've managed things by having separate rules with sub-worlds. So for example, ordinary polite conversation around a Thanksgiving dinner table is a sub-world with a separate set of rules. And we learn those rules and we play that conversation according to those rules. And we manage that by saying, not all conversation moves are valid here. In this space, only these moves are valid. And we make a lot of worlds like that. Humans just do this a lot. We create many different sub-worlds with the different rules. And this is much of how we actually manage our social world. And then sometimes we make separate new worlds, kind of out of fun,
18:21 Speaker 00 where we, they're not actually achieving anything else other than the practice of just being in a new world and going through it. But, for example, many of us like to be a bit hostile and a little competitive, but most of the social worlds around us don't really let us do that with the people around us. Right? Most of the conversation worlds or polite worlds don't really let you like, want to take the other guy down and try to be overt by that, right? And show your competition and you think you're better. And games often do that. That's one of the charms of games is they put this boundary around a space. Okay, in this world, you can be more aggressive, you can be competitive, you can try to win. And as long as it's within this limited scope of the kind of means you use and the kind of outcome you get, go for it.
19:05 Speaker 00 We like that, because in fact, we like to be a bit hostile and aggressive. That's actually a deep need we have that we actually don't get to express a lot in a world that shuts down everything as a potential, you know, threat to as a crime or something. So yeah, that's part of the appeal of finance and betting markets is it's a place where you get to be aggressive, you get to risk, take a chance, prove yourself, maybe lose it all, but people like that chance to prove themselves.
19:37 Speaker 02 Why do you think sports gambling has just like dwarfed everything else combined on prediction markets like Polly Market and Caloshi in terms of trading volume? I think it's like 90% of Caloshi.
19:50 Speaker 00 Yeah.
19:51 Speaker 02 And everything else is 10%.
19:54 Speaker 00 So for a long time, you know, sports has been one of the biggest areas that we allowed aggression, that it was okay to sort of express your aggression and physically express your aggression. And then fandom near sports also really enjoyed that aggressive competitive element that I'm for my team, you're for your team, the hell with your team, my team's better. You know, people liked even being in fans of sports to join that sort of aggressive stance. And that meant that sort of making sports bets was a natural thing to do. People for a long time have wanted to prove themselves by betting on something and betting
20:35 Speaker 00 on something they're already taking an aggressive stance toward and feeling allegiance toward and like doing a fair bit of investment and thinking about that's that just all fits together. So I don't think it's at all puzzling, given the kinds of things people have been doing near sports for a long time that they would want to bet, and in fact, they have bet. So I don't know if I mentioned this last time, if you go back a century ago in the United States, there was more money bet in the US presidential betting markets at the time than there was in the stock market at the time.
21:04 Speaker 02 Wow.
21:05 Speaker 00 Stock market was really small. It's grown a lot over the last century. So, you know, betting goes way back and, you know, as you know, people a long time and like like to play cards, like to play dice. People have liked to play games where they risk money.
21:24 Speaker 00 As part of making those games fun. And the fun about, say, betting on sports or something is now, you know, a game is this whole hypothetical thing that's just made up, but at least the sports is like a bit more real. Right? That these horses racing in a horse race, if you're betting on that, you're you're showing something about your knowledge about something that actually matters more than throwing a dice in a game. Because it's, you might think, why is that so disconnected from the rest of the world? I'm gonna say, look, sports is actually more connected to the world than most gambling in terms of, you know, dice or cards or things like that.
21:59 Speaker 02 Totally. I'm curious, in your article, "My Best Idea Decision Markets," you said, "Decision markets are not my deepest, grandest, most beautiful or hardest one insight, just the one with the biggest expected impact." So if not decision markets, what insights do you think are your deepest, grandest, most beautiful or hardest one?
22:19 Speaker 00 Oh, you want me to brag? You know there's a norm against that.
22:23 Speaker 02 I encourage you.
22:24 Speaker 00 There's a strict norm against bragging. And so my usual move is to try to, as best as I can, avoid this opening so as that I show that I'm supporting of the usual norm against bragging. Right? That's, I'm pointing out, the usual social game has me supposed to make that move here, right? But I'm just, I guess I'll be ironic. So I have this book, "The Elephant in the Brain," that I'm pretty proud of here, where I tried to understand, I guess you could take away the screenshot you're showing of this other.
22:56 Speaker 02 Oh, we can see on stream.
22:57 Speaker 00 Okay, because I'm just seeing the other, okay, anyway. Basically, that we are just wrong about why we do lots of things. And this was a big insight to me. I was surprised that I was able to figure out something that basic that we didn't understand very well so far. That we're just wrong about why we do lots of things. Couple of years ago, I dug into the sacred, and I thought I had a good insight into what the sacred really is, in a way that previous theories hadn't explained. I did this work on grabby aliens, follow on to my previous great filter analysis, where I explained where aliens are in spacetime. I still think that's a best account. Last couple of years, I've been focused on culture and how we seem to have broken humanity's
23:41 Speaker 00 superpower, and that's gonna be hell to pay over the coming centuries for that. And that's what I've been focused on the last few decades. But...
23:51 Speaker 00 You know, when you're trying to understand the world, you're looking for ways, things that we misunderstand, deep questions, et cetera. And as an intellectual, those are more celebrated. Changing the world, however, doesn't necessarily require deep insights. It requires maybe clever or unseen insights. And that's what I think prediction markets here or decision markets are. They just have a potential to remake the world. And I can be proud of having that insight, but it's not that deep. It's not sort of uncovering stuff. It's just noticing something that people didn't notice.
24:27 Speaker 02 I noticed you didn't mention Age of M when talking about your greatest insights, which is my, my personal favorite Robin Hanson arc was Age of M. I think it was like incredibly prescient on the development of AI as we're seeing it now.
24:42 Speaker 00 Right, so the, the message there is that I've been a futurist for a long time. And many people say that it's just really impossible to see the future. That there's just too many complexities that you couldn't really ever figure anything out much about the future. Now, I learned otherwise a long time ago because I was part of the group that invented the World Wide Web before there was a web. And, you know, right after the web appeared, many people said, nobody could have seen that coming. And I said, but, but we did. We saw it coming and we were trying to make it. And people kept saying after that, see, here's an example of something no one could have seen coming. Because people just have this sense that, you know, there's just stuff no one could possibly see coming.
25:21 Speaker 00 But the Age of M is about showing that I could take a technological premise and I could just work out a lot of detailed consequences, a lot more than most people could just by sort of, you know, writing a science fiction novel or sketching a few things. And I actually crammed it full with more details than most people want. People say, gee, I would rather not see all those details, Robin. Couldn't you tell some stories or do something more fun? I was trying to like, show you, you could tell a lot of details. You could actually take a technological premise of the future and work out a lot of detail about what would happen. In order to tell the world, look, you can do a lot more futurism than you're doing. It's possible to do futurism. Maybe you don't want to, maybe you're not interested, but look, you can. That, that was my message of Age of M. I'm proud of that as a demonstration.
26:06 Speaker 00 I do think it still has a substantial chance of actually happening. But even if it doesn't, I think I showed that you can just analyze a future scenario in a lot more detail than you usually do. But again, the usual social norms insist that I be uncertain about what my best contribution is because I'm supposed to be humble. I'm supposed to let the rest of the world sing my praises or make such judgments. And I'm happy to both accept these usual norms, but also poke at them by pointing them out.
26:37 Speaker 02 Right. Well, we love Age of M. We love prediction markets. We're so grateful to have you back on MTS. Thanks so much for coming on, Robin Hanson.
26:43 Speaker 00 Thank you for missing me.
26:45 Speaker 02 Absolutely.
26:46 Speaker 03 For sure. We will miss you again.
26:48 Speaker 00 Okay.
26:51 Speaker 01 Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.substack.com. Thanks again for listening, and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies, and individuals are not endorsed by A H Capital Management
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