Ethereum co-founder Vitalik Buterin says prediction markets are drifting away from their most useful purpose. In his view, too much activity now centers on short-term wagers such as crypto prices and sports outcomes, while the broader value of these markets as information tools is being weakened. He describes that direction as a “corposlop” problem, where product decisions start serving clicks, participation, and revenue more than accurate forecasting.
Short-term betting is crowding out long-horizon value
Buterin notes that trading volume in prediction markets has grown enough to support full-time participants. That shows real scale. But he argues the same growth has pushed markets toward what he calls an unhealthy product-market fit. Instead of pulling in users who help prices reflect informed views, platforms are increasingly shaped by demand for fast bets and quick stimulation.
He breaks prediction markets into two basic roles: smart traders, who contribute useful information to prices, and the counterparties who lose money. One side has to lose. According to Buterin, many markets now depend too heavily on naive bettors making poorly informed trades, and that creates a damaging incentive for platforms to recruit exactly those users.
Reliance on uninformed bettors can distort the whole ecosystem
For Buterin, the issue does not stop at market mechanics. If a platform needs less informed participants to sustain activity, brands, communities, and market operators may all be pushed to encourage unrealistic or “dumb” opinions simply to boost engagement. Prices may keep moving, but the informational quality behind those prices does not necessarily improve, and the broader social benefit stays limited.
His criticism is blunt: if market growth depends on attracting people with weak information, the system stops optimizing for truth and starts optimizing for participation. At that point, a prediction market begins to resemble an engagement product rather than an information product.
Buterin wants prediction markets to function more like hedging tools
Instead of treating prediction markets mainly as speculative venues, Buterin proposes a wider hedging use case. In that model, users would enter markets not to gamble on outcomes, but to reduce exposure to risks already present in their lives or portfolios. He gives the example of holding shares in a biotech company, where a political outcome could affect financial exposure tied to that investment.
Taking a position on the underdog, he argues, can in some cases stabilize returns by reducing volatility in the broader portfolio. Using a logarithmic utility model, he says that kind of risk reduction could be worth $0.58. Framed this way, prediction markets start to look less like pure betting platforms and more like insurance-style instruments against uncertainty.
From stablecoins to personalized expense index markets
Buterin extends the idea to money itself. Stablecoins aim to hold a steady price, but they still rely on fiat systems. He instead describes prediction markets based on price indices covering major goods and services, where each person could hold a basket of market shares tailored to their expected future expenses. The goal would be stability linked to real spending needs rather than to a single fiat reference point.
Under that framework, people could separate assets for growth from instruments designed to stabilize day-to-day costs. Buterin puts the point sharply: “We do not need fiat currency at all!” His proposal is not a minor tweak to existing prediction markets. It is a shift in purpose, from short-cycle betting toward tools that hedge future living costs and financial risk.