The a16z Show
Robin Hanson on Prediction Markets, Gambling, and the Future of Forecasting
26 May 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: What are prediction markets and how do they function?
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, in politicians' speeches, in policy wonk, you know, reports.
And that's what you're seeing initially here with Pelshi and Parley 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,
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.
Chapter 2: Why has Minnesota criminalized prediction markets?
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 Calshi 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 Sofia Puccini speak with Robin Hanson about prediction markets, futurism, games, and the future of forecasting.
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?
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 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, um,
know there's economic interests in that would like state regulation instead of national regulation and then there's just you know people looking for a political hot ball 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
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 wasteful gambling nonsense or immorally making money off of tragedy. Those are the two attack angles I see.
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Chapter 3: What backlash is occurring around platforms like Kalshi and Polymarket?
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 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 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 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.
Right. So you wrote an article a few months ago called Prediction Markets Now. What do I think of calci and poly markets 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 Kalshi?
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.
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Chapter 4: How can prediction markets advise individual and organizational decisions?
That is, speculative markets are shown to be an 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 politicians' speeches, in policy wonk, you know, reports. And that's what you're seeing initially here with Kalshi and Parley 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...
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.
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.
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 the 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 – there aren't any decisions companies make much bigger 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.
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Chapter 5: What is Robin Hanson's vision for decision markets?
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 the CEO? So these markets are remarkably, 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 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 or whatever?
Yeah.
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 established, and most importantly, people familiar and comfortable with using this.
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Chapter 6: How do prediction markets differ from traditional gambling?
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. Yes, indeed. 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 they're possible. And most innovation is 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.
But that doesn't mean something like that won't work later. You know, 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. What you should have more confidence in is the exploration of a large space of possibilities 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 Kalshi, sports, which accounts for like 80%.
So the weather... In fact, in this Minnesota case that we were 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.
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 weather? a sports market?
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Chapter 7: What role does sports betting play in the popularity of prediction markets?
But as I said, you know, centuries ago, the typical response to the possibility of gambling was just a ban at all. And that sort of banned pretty much all financial markets. And over time, we allowed more financial markets for that rationale. 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 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?
Yeah, so you can imagine like drone betting.
Sure.
As a way to accelerate military technology.
Right, you might imagine we create more sports related to new military technology so that people could, and 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.
Right.
And they're fun, but they also have this other purpose.
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