a16z Podcast - Robin Hanson on Prediction Markets, Gambling, and the Future of Forecasting

Episode Date: May 26, 2026

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 aggregat...ing 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 Resources: Follow Robin Hanson on X: https://x.com/robinhanson Follow Theo Jaffee on X: https://x.com/theojaffee Follow Sophia Puccini on X: https://x.com/schisofrenia Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Transcript
Discussion (0)
Starting point is 00:00:00 Well, so start at the beginning. The basic vision is that speculative markets are shown to be an 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 and politician speeches and policy won't, you know, reports. And that's what you're seeing initially here with Kalshi and Pali Market 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 the company that says,
Starting point is 00:00:44 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. For decades, Robin Hansen 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,
Starting point is 00:01:14 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 Hansen about prediction markets, futurism, games, and the future of forecasting. So today we wanted to talk about the new law in Minnesota, which,
Starting point is 00:01:59 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?
Starting point is 00:02:29 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 a 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 state. states, this regulation was displaced and now they allowed these national competitors and they didn't like that. So, you know, there's economic interests that would like state regulation instead of national regulation. And then there's just, you know, people looking for a political hotball, something to fight about. And many people didn't like this change at the national level and they
Starting point is 00:03:22 want to show their opposition to it by trying to push for state regulation to displace national population. How do you start to convince the public more broadly that this technology is actually useful? Because there seems to you 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 attack angles I see. 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
Starting point is 00:04:13 just somebody somewhere, see something as valuable. Other people accept the 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. There's 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 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,
Starting point is 00:04:58 and that's more vulnerable to people saying, oh, well, if you're just having fun, then I don't approve. Right. So you wrote an article a few months ago called Prediction Markets Now. What do I think of Calcian Polymarkets specifically? And you said you're mostly interested in the potential of stuff today to enable and cause that future vision and said, interesting 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, and 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
Starting point is 00:05:42 differ from what we have today on Polymarket and Kalshi? Well, so start at the beginning. The basic vision is that we could have speculative markets and 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 speeches, and policy wonk reports. And that's what you're
Starting point is 00:06:27 seeing initially here with Kalshi and Pauley Market as well. They're just going for whatever topics people are talking a lot about and maybe wanting to trade. And so 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 precedence, customer familiarity, all those things if they can accumulate will, in fact, enable all the other things I want to do. 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 pull.
Starting point is 00:07:22 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?
Starting point is 00:07:49 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 than that. And so that's a high value decision being advised by a market.
Starting point is 00:08:12 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 thing. All technology starts out expensive. And initially, you apply it to the biggest value of things you can find. And then as you get more practice, the cost come down and then you spread its range of application to lower
Starting point is 00:08:44 value, but still higher value than cost applications. 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?
Starting point is 00:09:12 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,
Starting point is 00:09:33 that report is going to be biased by who hired them, et cetera, how do you get objective information about whether to keep the 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. 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 while?
Starting point is 00:10:03 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 or 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, or 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. 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. So I wanted to pause on that because there actually is a real-life empirical example of prediction market supplied to dating, which was manifold love. Yes, indeed.
Starting point is 00:11:01 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. 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 you'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 at a particular context at a particular time,
Starting point is 00:11:40 but that doesn't mean something like that won't work later. You know, history of almost all innovation is littered with precursor. 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. What you should have more confidence in is the exploration of a large space of possibilities.
Starting point is 00:12:06 And let's figure out what works. 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 calci, sports, which accounts for like 80. 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,
Starting point is 00:12:37 oh, well, we've got to allow weather markets because they got pushed back 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. 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.
Starting point is 00:13:03 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 casinoification. I'd say, you know, a technology can be used in many different ways and then different people have different purposes.
Starting point is 00:13:28 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 got 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?
Starting point is 00:13:52 So obviously, we've been talking about saying about the information function. They can help people learn and get information about things. Secondly, they can hedge risk that much of financial markets, the standard, you know, 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 a 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, basically. 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 on it. You are more involved in the sporting event when
Starting point is 00:14:50 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 is 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, sporting activities and all sorts of, you know, look, we let people try to be actors, musicians, and athletes.
Starting point is 00:15:26 That's pretty low odds, but people seem to have fun trying to do that, and we're now kind of okay with people, you know, as 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, sort of people you're hanging with 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
Starting point is 00:16:04 was just a ban at all. And that sort of banned pretty much all financial markets. and over and over time we allowed more financial markets for that rationale. Sometimes we allowed gambling just for the fun but more unlimited. 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 contest situation of having to do a lot fast.
Starting point is 00:16:33 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? Yeah, so you can imagine like drone betting. Sure. As a way to accelerate military technology.
Starting point is 00:16:57 Right, you might imagine we create more sports related to new military technology so that people could, and sometimes people have said video games. Some video games are good for that. There are video games that the military is often thought is good for training people and selecting people for the military. Right. And they're fun, but they also have this other purpose. Right.
Starting point is 00:17:16 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. 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. but since then I've learned a lot about the literature. So basically, humanity often just creates sub-worlds that have set of rules, and then we manage things by having separate rules with sub-world. 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,
Starting point is 00:17:57 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 their 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,
Starting point is 00:18:21 where they don't 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.
Starting point is 00:18:49 And games often do that. That's one of the charms of games is they put this boundary around in 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. we like that, because in fact, we like to be a bit hostile and aggressive.
Starting point is 00:19:09 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, and 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. Why do you think sports gambling has just like dwarfed everything else combined on prediction markets like Polly Market and Calci in terms of trading volume? I think it's like 90% of Calci. Yeah.
Starting point is 00:19:52 And everything else is 10%. 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 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
Starting point is 00:20:35 and betting on something they're already taking an aggressive stance toward and feeling an allegiance toward and doing a fair bit of investment and thinking about that just all fits together. So I don't think it's 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 bed. So I don't know if I mentioned this last time. If you go back a century ago in the United States,
Starting point is 00:20:58 there was more money bet in the U.S. presidential betting markets at the time than there wasn't the stock market at the time. 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, as you know, people a long time like to play cards, like to play dice. People have liked to play games where they risk money 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 a sports is like a bit more real. Right? These horses racing in a horse race, if you're betting on that, 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?
Starting point is 00:21:50 I'm going to say, look, sports is actually more connected to the world than most gambling in terms or dice or cards or things like that. Totally. I'm curious, in your article, my best idea of decision markets, you said, decision markets are not my deepest, grandest,
Starting point is 00:22:08 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? Oh, you want me to brag?
Starting point is 00:22:22 You know there's a norm against that. I encourage you. Real for it. And so, So my usual move is going 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? 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.
Starting point is 00:22:53 I guess you could take away the screenshot you're showing of this other. Oh, we can see you on stream. Okay, because I'm just seeing the other, okay, anyway, anyway, that, 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. We're just wrong about why we do lots of things. A couple 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 Gravy aliens, follow on to my previous Great Filter analysis,
Starting point is 00:23:32 where I explained where aliens are in space time. 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 superpower, and that's going to be hell to pay over the coming centuries for that, and that's what I've been focused on the last few decades. But, 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.
Starting point is 00:24:02 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. People didn't notice. I noticed you didn't mention age of M when talking about your greatest insights,
Starting point is 00:24:32 which is my personal favorite Robin Hanson Ark was age of M. I think it was like incredibly prescient on the development of AI as we're seeing it now. Right. So 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 we did. We saw it
Starting point is 00:25:12 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. People just have this sense that, you know, there's just stuff no one could possibly see coming. But the age of M is about showing that I could, I can take a technological premise and I could just work out a lot of detail of 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. Peace 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.
Starting point is 00:25:47 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 was my message of HM. I'm proud of that as a demonstration. 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 usually
Starting point is 00:26:17 not. 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 phrases or make such judgments. And I'm happy to both accept these usual norms, but also poke at them by pointing them out. 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. Thank you for missing me. Absolutely. For sure. We will miss you again.
Starting point is 00:26:48 Okay. Thanks for listening to this episode of the A16D podcast. If you like 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.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.
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