Prediction Markets

So, where are prediction markets headed? 

N=1 here, but they appear to be diversifying beyond forecasting the results of political elections and sports events.

How they work and some of their new applications are captured in this useful explainer article in the journal Nature by Adam Mann. 

What are they? 

Prediction markets are a method for pulling forecasts from the aggregated guesses of individuals. 

But rather than just asking participants to vote on what they think will happen in any given situation, they work like a market where contracts contingent on the occurrence of the event can be traded. They incentivize correct predictions.

They can be astonishingly accurate, so long as the pool of participants is large enough and the participants' knowledge/priors are sufficiently diversified. 

Why?

One answer was theorized by economist Friedrich Hayek in the mid-20th century. He thought that markets generally could be viewed as mechanisms for collecting vast amounts of information held by individuals and synthesizing it into a useful data point — in his theory, the price that people are willing to pay for goods or services.

The recent expansion in use cases can be chalked up to lower barriers to creating and participating in markets, courtesy of the internet, and successful examples, like PredictIt and the IEM, being popularized in academic literature and popular media. 

Like AI, prediction markets seem to be emerging as a valuable decision-support mechanism for people who need to make big, good choices.