So in this conversation, we tease apart the hype from the reality of prediction markets, from the recent election to market foundations... going more deeply into the how, why, and where these markets work. We also discuss the design challenges and opportunities (including implications for builders throughout). And we also cover other information aggregation mechanisms -- from peer prediction to others -- given that prediction markets are part of a broader category of information-elicitation and information-aggregation mechanisms.

Where do domain experts, superforecasters, pollsters, and journalists come in (and out)? Where do (and don't) blockchain and crypto technologies come in -- and what specific features (decentralization, transparency, real-time, open source, etc.) matter most, and in what contexts?  Finally, we discuss applications for prediction and decision markets -- things we could do right away to in the near-future to sci-fi -- touching on trends like futarchy, AI entering the market, DeSci, and more.

Our special expert guests are Alex Taborrok, professor of economics at George Mason University and Chair in Economics at the Mercatus Center; and Scott Duke Kominers, research partner at a16z crypto, and professor at Harvard Business School  -- both in conversation with Sonal Chokshi.

As a reminder: None of the following should be taken as business, investment, legal, or tax advice; please see a16z.com/disclosures for more important information.

Resources: (from links to research mentioned to more on the topics discussed)

The Use of Knowledge in Society by Friedrich Hayek (American Economic Review, 1945)

Everything is priced in by rsd99 (r/wallstreetbets, 2019)

Idea Futures (aka prediction markets, information markets) by Robin Hanson (1996)

Auctions: The Social Construction of Value  by Charles Smith