Bayesian Truth Serum and Prediction Markets

Speaker 1
Can
Speaker 3
you quickly maybe give a very short definition in the uniquely crypto blockchain context of a Bayesian truth serum here? Because isn't this where Bayesian truth serums apply?
Speaker 1
Sure. I mean, the Bayesian truth serum is actually an example of those pure prediction mechanisms we described, and there are many different versions of it. But loosely, the idea is if I ask you your opinion on something, did you like this movie? And then I ask you, what's the likelihood that, you know, another person I ask will say that they liked the movie. You might have a reason to lie to me about whether you liked the movie or not. You might say, oh, I really liked it because, you know, you produced it. What am I going to do? But you actually hated it. Your estimates of everybody else's beliefs will be sort of tilted in the direction of them mostly disliking it. So long as I'm going to reward you to proportional to your accuracy, like, you know that you disliked it, and so everyone else probably will too, because you're a Bayesian. And so I can detect, looking at everybody else's responses, I can detect whether you sort of like told me a distribution of other people's beliefs that's consistent with what you said your belief is. Great.
Speaker 3
One of my quick applications, and kind of an obvious one, but I want to just call it out, because I find it very boring when people say the same thing like, oh, media, whatever. What I find very interesting is and people often talk a lot about having mechanisms for, quote, finding truth. But sometimes I find it to be very pedantic and moralistic and equally as grating as a way that the very people they're trying to bring down. And so it's a pet peeve of mine when I'm on the Twitter discourse, like, oh God, I'm so bored by this. But I do find it very interesting that some of the commentary surface at prediction markets for basically resolving more accurately and faster than mainstream media, but not having some of the same filtering of partisan interests. I mean, although this might be different with certain communities of DAOs, if you do predictions limited to certain DAOs.
Speaker 1
Yeah, again, it depends who's in your market.
Speaker 3
Yeah, exactly. This goes back to your point about thick and thin. But it's also interesting because it's a way to put a little bit more skin in the game, which is one of the biggest drawbacks in current media. It's like the people writing don't have skin in the game, which is why I've always been a believer and not having third-party voices, but the experts write their own posts and then editing them is more interesting to me. So I do think it's very interesting to think about this use case of reinventing news media using prediction markets. And Vitalik's post actually had a great headline, which is that think of a prediction market as a betting site for participants and a news site for everyone else. That'd be my application. So
Speaker 2
I think more generally, it is odd how we do quite a bit of journalism. So for example, it's totally standard practice for a financial journalist, right? For it to be against company policy, for them to invest in the companies which they're recommending, right? And as an economist, I kind of think, wait a second, don't want the exact opposite, right? Yeah,
Speaker 3
you want more skin in the game. Exactly.
Speaker 2
Yeah, more skin in the game, right? So, you know, I say that a bet is a tax on bullshit, right?
Speaker 3
I like that line. That's a great line. I love it. So,
Speaker 2
you know, how about you have to be upfront about it. You have to be honest about it, transparent about it. But maybe journalists should say, this is what I think will happen. And these are the bets which I've made. And you can see my bets on chain, right? And let's see what their past track record is, right? Like, it's kind of amazing that we do not have any track record of opinion editorialists whatsoever. Only Tetlock, you know, started to create that and found that they were terrible, right? But how about let's create a series of bets and on chain. And this would, you know, change the types of people who become, you know, editorialists, who get these jobs in the first place, right? So let's start making sure you bet your beliefs. And then let's promote people whose bets turn out to be accurate. And that's going to change journalism entirely if we were to change the metrics by which journalists are evaluated. I
Speaker 3
agree. Annie Duke talks a lot about this too. It's not just bets like in a binary, true, false way, but bets that are weighted in terms of likelihood, probability of accurate, like you don't have to make a binary, like it will be this or that. I believe 80% that X will happen. And that is also another way to kind of assess in a more nuanced way. And that gives a lot of room for the nuances that are often true when it comes to guessing the truth.
Speaker 2
Absolutely. Exactly. There's a big incentive to say, this is never going to happen. This is impossible, right? But then if you ask them, well, if it's never going to happen, are you willing to bet $10 that it might happen? Exactly. They should all be willing to, of course, they're never willing to make those bets.
Speaker 3
That's right. Even people who hate Elon Musk as journalists will then start saying, well, actually, I'm going to bet on that guy for building X to happen because I saw that, you know, shuttle launch. And now I'm thinking, okay, maybe I'll increase that from
Speaker 2
10 to 20% or whatever. Yeah, exactly. So betting could reduce the hyperbole. Yeah, that's exactly
Speaker 1
right. Yeah, totally. By the way, this ordered on some other really critical information elicitation mechanism that uses a different version of this sort of cross-examining some people's beliefs against others. If you think about community notes on Twitter, that's an information aggregation mechanism, right? It's like getting a lot of people's opinions and then only deciding that they're correct if you have agreement from people who usually disagree. Yes,
Speaker 3
exactly. Because that's where Wikipedia failed when they had the cabal of expert reviewers. They didn't have that kind of check and balance mechanism. Yeah, totally.
Speaker 2
Yeah, community notes is a great one. I
Speaker 3
have one last question for you guys, because we don't have enough time to go into policy. You know, in general, like some of these became popular because they're offering contracts that were banned from the market. So a big question is whether the offshore crypto markets will follow the rules or not. So how do you sort of create like innovation, obviously, in that environment? To me, the core question here is what's the difference between gambling and speculation? Is there a difference? I'm curious if you guys have a thought on as a parting note on this. I
Speaker 1
mean, so one very important thing to remember is that depending on the context, like you may be in a different point on a continuum, right? Like part of what makes sporting events like exciting and suspenseful is that there's a lot of stochasticity and like, you know, sort of the amount of information that any individual has is reasonably small, even if they put a lot of effort into figuring it out. But there might be some amount of like, you know, sort of informed betting in sporting events. And then as you move towards things where there's a lot of information to be had and a lot of like value also to knowing the answer, right? A lot of market value to actually figuring it out, right? Like how do we allocate goods in markets, right? Going back to the very beginning when we were talking about like the role of markets and, you know, determining the value of something and clearing supply and demand, there is value generated through the process of people engaging. Now, there's one really important caveat about speculation. We talk about this a lot in Cryptoland. There is speculation of the form, I have beliefs and I'm investing to support a product that I think will exist and that I want to exist and that I think other people will want. And then there's also speculation on speculation where you're actually not so much betting based on your own beliefs, you're betting on, you know, what you think other people will choose to bet on. Like we talked earlier about hurting, you know, you might place bets because you think other people are going to place bets in a given direction, not because you actually have any information about what's going to happen just because you have information about how the market might move.
Speaker 3
That's right. That's speculating on speculation.
Speaker 1
Exactly. That's speculating on speculation. So there's this sort of like valuable type of speculation, which is people moving resources around in a way that reflects their beliefs and sort of like can help us make markets work better and achieve better outcomes. Like that's sort of in this mid space between the randomness where moving the money around has no impact on outcomes, right? You're just betting on coin flips, like, you know, your money does nothing. And this other edge where moving the money around becomes sort of its own project that is independent of outcomes. And so again, like sort of doesn't provide information, right? Like these prediction markets are particularly well architected, again, at least in the cases where they're very large and thick and all the things we talked about that you need to make them work. They're particularly well architected to try and be in that midspace where the information provided is valuable and comes out of like real knowledge and activity in a that actually sort of means the market does something valuable.
Speaker 3
Yeah.

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