Prediction platforms, like Polymarket, recently attracted significant attention during the US elections for their distinct role in forecasting outcomes. However, Ethereum co-founder Vitalik Buterin believes these platforms hold even greater potential, envisioning their evolution to reshape social media, science, news, governance, and other sectors.

In his recent blog post titled “From Prediction Markets to Info Finance,” Buterin outlined a concept called “info finance,” which extends beyond traditional prediction markets by merging information with finance on a blockchain scale.

Buterin Highlights Prediction Markets’ Power Beyond Elections

Buterin sees prediction markets serving dual purposes: enabling bets and acting as alternative news sources. He highlights how platforms like Polymarket have become trusted for information, often outperforming traditional media in accuracy.

“To many people, prediction markets are about betting on elections, and betting on elections is gambling – nice if it helps people enjoy themselves, but fundamentally not more interesting than buying random coins on pump.fun,” Buterin wrote.

He noted that Polymarket accurately indicated a stronger chance for Trump to win certain elections, while mainstream sources suggested otherwise. It also effectively forecasted outcomes for Venezuela’s July election, combining real-time data with market predictions.

According to Buterin, these platforms offer valuable insights to both bettors and non-bettors. Bettors can place wagers, while other users can view market data as a unique news source. This structure, he argues, bridges the gap between information and finance, creating a type of “info finance” that could address issues of trust and accuracy on a blockchain scale.

Buterin noted that info finance allows users to extract valuable insights by identifying a key fact and designing a market to gather this information from participants. He envisions this concept as a “three-sided” market, where bettors make predictions, readers consume these forecasts, and the system generates public predictions.

This structure aligns financial incentives with the distribution of reliable information, creating a unique, value-driven ecosystem.

“One technology that I expect will turbocharge info finance in the next decade is AI (whether LLMs or some future technology). This is because many of the most interesting applications of info finance are on ‘micro’ questions: millions of mini-markets for decisions that individually have relatively low consequence,” Buterin added.

Looking forward, Buterin believes that info finance could expand beyond prediction markets to influence decentralized autonomous organizations (DAOs), personal tokens, and even advertising. In DAOs, for instance, prediction markets could complement or even replace traditional voting by leveraging both human and AI predictions to streamline decision-making.