Prediction Market: The Frontier of Information Finance

The prediction market is one of the most exciting applications in the Ethereum ecosystem. As early as 2014, I wrote about the prediction-based governance model known as futarchy proposed by Robin Hanson. Since 2015, I have actively supported and used the prediction market Augur, and made a profit of $58,000 through betting in the 2020 elections. Recently, I have been closely following the development of Polymarket.

Many people may think that prediction markets are just another form of gambling, such as betting on election outcomes. But on a deeper level, prediction markets represent an emerging "information finance" model, with the potential to be applied in various fields such as social media, scientific research, journalism, and governance.

The current prediction market has become a powerful tool for obtaining information. Taking the U.S. elections as an example, Polymarket not only accurately predicted the results but also timely reflected the latest developments, providing users with real-time insights. For ordinary users, Polymarket can serve both as a betting platform and as a news data source.

The core of information finance lies in designing reasonable market mechanisms to efficiently extract valuable information from participants. In addition to prediction markets, decision markets are also a typical application. By setting up conditional markets, the expected effects of different decision-making schemes can be assessed.

In the future, artificial intelligence is likely to play an important role in the field of information finance. AI can lower the barriers to market participation, allowing even small-scale, low-volume markets to obtain high-quality information.

Information finance can also be used to "refine" expensive human judgment mechanisms. By establishing prediction markets to simulate the outcomes of high-cost mechanisms, a credible, neutral, fast, and inexpensive alternative can be obtained. This approach is expected to be applicable in scenarios such as social media content moderation and DAO governance.

In addition, information finance has many potential applications: improving personal token projects, optimizing advertising placements, enhancing the quality of scientific peer reviews, and perfecting the funding mechanism for public goods.

Overall, information finance is facing unprecedented development opportunities. It can not only solve real-world trust issues but also achieve scalable applications through scalable blockchain and artificial intelligence technologies. In the future, we can expect to see information finance in a broader field beyond election predictions.