In this episode, Matt and Joseph sit down with Robin Hanson, Associate Professor of Economics at George Mason University, to discuss prediction markets.

A prediction market is a kind of betting market, wherein people place bets on whether or not some future event is going to happen by investing in market shares associated with that event. If the event happens, the people who predicted it correctly get paid. If not, they lose the money they invested. So far, so good: all that is pretty normal for a betting market. But in the case of a prediction market, there is a further twist. Before the future comes to pass and the people who guessed it correctly get paid, there’s a mathematical formula you can use, based on all the bets that have been placed so far, to determine what the probability of that event happening is. In other words, before the payout, the current prices of all shares in market give us the ability to subtly aggregate the wisdom of every individual speculator into a combined judgment about what is probably going to happen.

So what, you might think. Well, it turns out that this system for forecasting the future is unusually accurate, particularly when it comes to making the most difficult predictions about the behavior of large, complex systems. And so, for several decades now, our guest has been thinking hard about how can we leverage the information provided by various prediction markets to assist with a wide range of challenging forecasting tasks that might nonetheless be important to do.

Although prediction markets have mostly been set up, thus far, to determine the outcomes of things like elections or sporting events, Robin Hanson thinks they can be also be used for more ambitious purposes. One small-scale example is: the board of a public corporation could use a variation on a prediction market (called a decision market) to make decisions about whether to hire a new CEO. A bolder example would be a new system of government he calls futarchy, in which legislators abandon their role of drafting and passing legislation, and instead turn their attention to coming up with precise, measurable definitions of success. Each individual question about what policies to pass when can then be adjudicated by prediction and decision markets, which require measurable definitions of success to function.

Robin Hanson is always abrim with fresh ideas, and it was a pleasure talking to him. I hope you enjoy our conversation.

Matt Teichman

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