The Future of Prediction Markets
My talk at Manifest 2024
Watch the video here, or proceed to read the lightly edited transcript.
The talk
Welcome! I'm so glad you're all here. Like all of you, you've come from far away places. Welcome to Manifest! I guess this is the first talk. Manifest this year is twice as big as last year. It's going to be crazy. I hope you guys have a great time. I hope you have twice as much fun. I think my talk is not going to be twice as good as last year, but yeah, welcome.
My name is James. I'm one of the co-founders of Manifold. It's nice to meet you if we haven't met already. I'm going to dive right into my talk, which is on the future of prediction markets. I hope that you find it interesting.
I'm most interested in the potential use cases for prediction markets. I'm going to outline four of them in my talk. Basically, prediction markets are sort of going places these days. They're getting more popular. We even have people writing articles about prediction markets. Some of them are saying things like, "Oh, they're not going to grow very much more" or "They're actually not as good as polls." But when you have these kinds of articles coming out that are criticizing them, I think that's actually a good sign. That means we're on to something. So I'm happy about that.
The original idea of Manifold was to take prediction markets and have them be run by a creator where one person would ask the question, they would set the resolution criteria, they would allow people to trade, and they would earn trading fees. So they would sort of run this whole thing. They provide a lot of value by doing that, and then they would earn from the trading fees. So it turns it into almost like a mini business. That was the original idea that we proposed to Scott Alexander.
But we decided to move into play money. So it was never quite the case that you could create any question and if it got popular enough, actually earn income from it. However, Manifold has recently announced that we are going to introduce these cash prizes using the sweepstakes model. I'm happy to say that in about a month - it's not launched yet - you will be able to earn cash prizes and perhaps run markets and run them like a business and possibly earn a profit by being a creator of markets. So I'm really excited for that.
Also at this Manifest, you will be able to learn more about sweepstakes, including there will be a live theatrical performance and musical that will go over the details. I hope you will attend that. I think it'll be in the park in like a couple of hours. So look forward to that.
And then without further ado, I'll continue to enlighten you on the four use cases that I think are really valuable for prediction markets.
I. Running a market profitably
The first one I've sort of outlined already, which is to run a market in a way that's net profitable. On Manifold so far, with the play money world, we actually were not running these zero-sum markets. In fact, we were printing a bunch of Mana. We were giving out lots of bonuses because that made it a lot easier for someone who creates a market to earn Mana from doing it. So we would give you a bonus for every unique trader that trades on your market.
It was common for people to make a profit by creating markets on all these topics. Post pivot, we have eliminated all those bonuses, and it's very sad. All the markets are zero-sum actually, and we're charging trading fees. So when users trade, a little bit of their bet actually goes to the creator of the market now. We are trying to bring back the original vision of Manifold, which is that the creator can make a profit on their market.
Let me tell you an anecdote. Just yesterday, you know that Starship succeeded at taking off and re-entering, and it didn't explode. That's amazing. It's really significant, but it's significant for another reason, which is that one of our users, Chris J Billington, created a market on whether the Starship would not explode. He subsidized it with 50,000 of his own Mana, and in this zero-sum environment, he was able to earn a profit for the first time as a creator because lots of people bet on it. He managed to close the market before the spaceship launched, so that meant he was able to get back his liquidity.
The way liquidity works is a little complicated, but if the probability gets bet to an extreme, then it actually ends up eating it up, and that money goes to the traders that bet on it. But if you close the market early, which is kind of a novel thing because in Manifold with the play money version, people are just not that concerned about play money. But in this world, to justify adding a large amount of subsidy - and I hope that this was basically $50, 50,000 Mana, but I hope that we can scale that. So this is like a proof of concept that something with a little bit of subsidy, $50, is something that we can magnify, and we can eventually have $50,000 as a subsidy.
If you can manage liquidity right, then you can sort of turn the market into a profitable endeavor. So I think that that was something very significant that just happened yesterday.
Imagine if you have these engines for prediction markets where each one can actually become profitable. Then that will inspire a lot of people in a decentralized way to create markets on their niche, on what they're knowledgeable about. I think that is a great thing, and that's the first thing that I'm very jazzed about.
II. Buying information
Okay, the second thing I'm jazzed about for prediction markets: not every topic can support enough traders or enough betting volume in order to earn enough fees. So essentially, it's like what if you have a question that's not very popular? What if it's a niche question? What if it's some obscure scientific fact that you want a forecast on, but maybe it's not quite profitable?
In that case, prediction markets are actually still useful. Here's how: basically, you flip the script and you say instead of trying to earn a profit, I am going to purchase information. I am going to subsidize this market. So you put in however much money you think it's worth to answer this question, and then you just create the market. Then in a crowdsourced way, lots of people from around the world see that, and then they bet on it if they think it's profitable. Through this magic, the prediction market will create a forecast to answer your question.
So the second case is basically buying information. I think that that's really cool.
I've done this, for example. I wanted to know what the daily active users for Manifold would be in July, so in the future. I set it up. I asked this question using our experimental numeric distribution format, which I think is also novel. Essentially, it allows people to bet on this complex continuous distribution. It's actually not continuous; we break it into little buckets, but it's approximately continuous. Users can choose a range and then bet an amount within that range, and it will adjust the distribution to be higher where they bet it.
I paid 10,000 Mana, and I got as a result this nice distribution which said, "Here's the expected daily active users for Manifold in July." That's an amazing service. I think that's useful. I think that's worth $10, and I think it might be worth more. If you put in more, the more Mana you put, the more subsidy, the more traders will put in an effort to fix all the cases in that distribution.
Maybe they think that the chance is basically centered around where our current users are, and then there's this long tail where maybe we're going to grow a lot. I'm happy about that case, but it basically said there was like a 5% chance that we would grow by 50% or more. If I were interested in those tails and I wanted it to be more precise, it would actually just work to add more subsidy to the market so that people have more incentive to bet it to be accurate.
There are tons of examples within Manifold because we use markets all the time for everything. We're buying information or we're doing a brainstorming session where we're getting users to propose features to us, we're getting users to find bugs for us. There are many formats where you can ask either an open-ended question and get free response answers.
The T-shirt design for Manifest that you have is created through a market, which was basically a contest that says, "Who will design the best T-shirt?" Another example that's pretty cool is that every month, the Manifold team does a retrospective of what went well and what didn't go so well in the last month. I create two markets for that. These are free response markets that mostly the Manifold team uses where we submit answers of what we thought went especially well and what we thought maybe didn't. This helps us improve.
Basically, I will just look at those answers and then subjectively be like, "I think this is pretty important" and "This one's not that important," and I come up with weights for them. Then I just resolve the market according to that. So it provides an incentive for people to submit and bet on answers where I think it will be judged as relatively important. It's just one more use case for how we use markets internally. I think that the ability to earn cash prizes and subsidize stuff is going to be a major deal, which might unlock a lot of use cases for other companies to use these as well.
III. Economic hedging
Okay, the third use case for prediction markets that I think is valuable and will be interesting going forward is economic hedging. Usually, when you make a bet, you're betting it because you think you're going to make money in expectation, like you're going to get more out of it than you put in. Sometimes you don't even need that in order for it to be profitable for you.
The way that works is because people have utility functions that are basically risk-averse. They might want to hedge the downside so that maybe they're losing money in expectation, but they're also making sure that the worst case is not so bad. This is kind of like an insurance market.
I created a market for myself because I ride an electric unicycle, and it's very dangerous. So I created a market like, "Will I have an accident or will I have an injury?" The market itself can first find the right price, so it discovers what is the right price for my insurance, essentially. It'll be like, "Okay, I broke my collarbone last year right after last Manifest riding an electric skateboard, so I switched to unicycle because I thought it was safer." So you have a base rate.
I created that market, and I started. I was like, "I'll buy yes at 4% that I will have an accident in the rest of 2024." Then people started betting it up, and now it's like a 10% chance that I'll have an accident. So I ended up just posting a limit order to buy yes at 10%. People will fill that. I've gotten some of it filled already. Then I have insurance. Whenever I actually make a profit, if I do end up breaking another bone.
Economic hedging is probably less useful personally. I think the main use cases are usually for businesses. There are tons of use cases for this. There's like, "Will the weather be bad on this day that makes the event not work?" or "Will Trump be elected, and then somehow that changes something for you in your business?" or "Taiwan is invaded, and that's not good for your business for some reason." So you can hedge all of those outcomes.
What I will say is that the user-created model is basically an amazing combination with this economic hedging use case because you can figure out what you want to hedge, and then you create exactly that question and hedge it. Like I could create exactly the question I wanted on my electric unicycle. But if you're a business, I think that that's like a superpower. If you're going through traditional finance and stuff, it's not that easy. So economic hedging is pretty cool.
IV. Matchmaking
Okay, the fourth use case that I think is really valuable is matchmaking. I would put this in a generalized way. There's basically hiring, where you're matching a job seeker to a company. There's networking, like who should I meet, who should I talk to. There are friendships, like who would I really vibe with. And there's dating, of course. I mean, obviously.
After last Manifest, Robin Hansen gave a speech, and he said, "You guys are doing cool stuff, but you're kind of not getting to the really valuable use cases. You need to think long and hard about where prediction markets are going to be the most valuable. Is it really about predicting whether the ball pit is going to materialize at Manifest?" He suggested that hiring markets, helping companies hire employees, is obviously really valuable.
I heard that, and then I was like, "I know exactly what to build," and that was Manifold Love. I don't know if you guys know, but basically, the way I'll explain very briefly, the idea is that you create a public profile, a dating profile. You upload photos, you answer questions, and then you bet on who among these profiles is going to date who.
Secondly, I'd say that there were definitely some issues where people were not that interested in browsing on behalf of someone else. People are definitely more interested in themselves and browsing for themselves and betting on their own prospects. But I think that with the addition of sweepstakes and cash prizes, that could help incentivize people to go out and find matches for other people. So I think it's possible that Manifold Love could be rebooted at some point. I know if Stephen were here, my brother, he would be like, "No, no, no, we're not doing that at all. Just forget about Manifold Love." But yeah, I think it's really cool.
Also, we are planning to actually do the hiring use case. Manifold is not really hiring at the moment, but we might soon. When we are, I will create a market on who we will hire. I will subsidize it with lots of money so that you'll make at least $10,000, maybe more, by betting on who we're going to hire. I actually think that this is a promising use case. I think that crowdsourcing who we would hire, like people have good ideas, they know people, and the mechanism is correct. It's like they're going to bet if they think we're going to hire them, that it's profitable in expectation for them to bet on it. That will surface to us the most promising candidates. We will just look at them and see which one has the highest probability of being hired, then we'll interview those people. I think it's going to work. So we will dog food that, and if it's sufficiently successful, then we can just try to make that work for everyone, try to run that as a product for other companies. I think that's really exciting.
V. AI
Okay, so those are four use cases. This is a talk about the future of prediction markets, so I have to mention AI at some point. Basically, my take on AI is that it will take all of those use cases and it will supercharge them because AI is actually going to make all of those way better.
Let me run through them again. So we have running a profitable market. Imagine that it's an AI that creates the market. It's the AI that has to judge whether it happened. I actually think AIs are going to be great judges, like an impartial source. Instead of relying on a human that's emotional and maybe they didn't read the evidence correctly, or they woke up and were sick that day, you don't know. But if it's an AI, you're like, "Okay, that's objective." I think they're going to be great market makers and resolvers. They can do it for cheap, which is really like another superpower.
So it means that we can have markets on everything because it's going to be so cheap for AIs to create and resolve markets. You can ask the AI questions about the resolution criteria, and it will always be there to respond and give you clarifications. So I think it's going to be a better service, and it'll be cheaper. That's amazing because we actually can just support markets on everything. Then you can just type into Manifold any question, and we already have a lot of questions - we have like 100,000 - but then we'll just have like 100 million or something. There'll just be so many questions.
That's just the first use case - running markets as a business. It's going to be profitable for those AIs in particular because they just don't need to be paid much.
Then there's another use case, which is doing research or subsidizing markets. Why would an AI pay to create a market and subsidize it? I think we're going to enter this world of AI agents that are trying to understand the world. They're trying to make progress on their own. The world is complex, and the AI might not know everything. I think there could be domain expert AI agents that know about certain things.
Basically, what I think will happen is that prediction markets will be like a native technology of AIs. When there's something they don't know, they will ask a question using APIs, and they will subsidize it. Then other AIs will answer, will bet on it, and so it can, in a matter of seconds, sort of figure something out about the world. This is all just information technology. It's just whatever it wants to learn, it can do. There will be these AI agents that perform this role because it's profitable to bet on these markets.
They will be running businesses, and then they will be hedging their business economically using prediction markets because it just makes sense. It just produces value. So I think that prediction markets are actually a really good match with AI. I think humans are actually not a good match for prediction markets when you think about it. It doesn't come naturally, like thinking in probabilities, figuring out exactly how much to bet. That's like only weird humans do that. It's not something that all of us just natively think in this way economically and in probabilities. But computers are so good at this, and they're already trading on markets. Like most of the volume in stock markets is all algorithms and stuff. So basically, I want to submit that prediction markets, and in particular user-created prediction markets, will be a useful tool for AIs to do a bunch of things using all the use cases I outlined.
One ending anecdote might be if, in the future, you have your personal AI and it knows everything about you. But people are protective of their data, so actually only your AI has that data. It's kind of like it sees your whole life and it knows everything you say. So it has a really good grasp on you personally. That AI could go out and bet in prediction markets on who you will marry, on which jobs you will take. You will benefit from this because you will get all these nice forecasts of what you should be doing. It will make your life a lot better. I think that that would be a truly amazing world.