Vitalik Buterin thinks prediction markets are being dramatically underused-and that, if designed differently, they could one day play a role so central to finance that they effectively “replace fiat currency.”
The Ethereum co-founder recently outlined his concerns about how today’s prediction markets are evolving, and why he believes their current trajectory is leading toward what he bluntly calls “corposlop”: shallow, profit-driven systems mostly optimized for degenerate short‑term crypto bets rather than serious information discovery or risk management.
At the same time, he sketched out a radically different future. In that vision, prediction markets become a kind of financial infrastructure: tools that let individuals and businesses hedge against real‑world uncertainty to such an extent that traditional currencies and even some stablecoins might become far less necessary.
From speculative casino to information infrastructure
Buterin’s core criticism is that most existing prediction platforms are stuck in a narrow niche. Volumes are high enough that some traders can treat them as full‑time jobs, and the odds they generate can be surprisingly accurate. Yet the majority of activity clusters around short‑term, crypto‑centric questions: token prices by the end of the week, the outcome of a forthcoming protocol upgrade, or the latest meme coin drama.
That’s not what he considers their highest calling. In his view, prediction markets should be a public good-an “information infrastructure” that aggregates dispersed knowledge about the future and translates it into tradable probabilities. Instead of only answering, “Where will ETH be on Friday?”, they should address questions like:
– How likely is a specific regulation to pass within two years?
– What is the probability a given country will enter recession next year?
– How likely is a certain pharmaceutical trial to succeed?
If markets consistently price these probabilities, they allow everyone-from individuals to corporations-to build financial strategies around the future, not just around price charts.
Hedging as a replacement for fiat stability
The most provocative part of Buterin’s argument is his suggestion that hedging via prediction markets could replicate one of the main reasons people rely on fiat currencies: short‑term stability.
Today, if someone wants predictable purchasing power, they typically hold dollars, euros, yen, or a stablecoin pegged to them. Those assets serve as anchors in a volatile world. Buterin suggests a different approach: use crypto as the base asset and layer prediction‑market hedges on top to cancel out specific risks.
Imagine a user holds a volatile cryptocurrency as their main store of value. Instead of exchanging it into dollars whenever they want stability, they could open positions in markets that pay off if that crypto falls in value or if other macro shocks occur. By carefully designing those hedges, the user could create a synthetic position whose real‑world purchasing power is fairly steady-without ever touching fiat.
In other words, prediction markets don’t just forecast; they can be building blocks for financial engineering. If they are deep and liquid enough, they become a universal hedge layer, able to smooth out income, expenses, and savings in a way that reduces the need for government‑issued money.
Why stablecoins aren’t the whole answer
Buterin explicitly compares this future to the role stablecoins play today. Stablecoins have already shown that people want crypto‑native instruments with predictable value. However, most stablecoins are still tightly tethered to fiat currencies, both conceptually and operationally. Their “stability” is defined by their ability to track dollars or other state money.
Prediction‑based hedging could move beyond that. Instead of defining stability as “whatever the U.S. dollar does,” users could define stability in terms of their own needs and risks:
– A farmer might hedge against poor weather or falling crop prices.
– A software startup might hedge against a broad tech downturn.
– A household in an emerging market might hedge against local inflation or political shocks.
In each case, what counts as “stable” is different, and a one‑size‑fits‑all peg to a single national currency is a blunt tool. Prediction markets, in theory, can offer custom‑tailored stability profiles that fit specific lives and businesses rather than just tracking a central bank’s policies.
The problem with “corposlop”
The term “corposlop” in Buterin’s critique captures his worry that prediction markets are drifting into the same rut as many other financial platforms: optimized for engagement, fees, and short‑term entertainment at the expense of depth and utility.
He sees signs of this in:
– Overemphasis on short‑term price speculation and meme narratives.
– Market questions that are vague, poorly designed, or borderline meaningless.
– Payout structures that cater to gambling behavior rather than serious hedging or research.
In such an environment, prediction markets risk becoming just another form of leveraged betting, no more useful, in aggregate, than sports gambling. Buterin warns that if this trajectory continues, the sector might achieve high volume but low social value: impressive numbers, negligible real‑world impact.
What a “serious” prediction market might look like
To avoid that outcome, Buterin argues that prediction platforms must be re‑oriented around questions that matter and mechanisms that reward genuine information.
That implies several design priorities:
1. Clear, verifiable outcomes
Markets should be framed around events that can be unambiguously resolved-e.g., official statistics, electoral results, or documented corporate actions. This aligns incentives toward truth rather than endless disputes over interpretation.
2. Longer‑term horizons
Not every useful prediction resolves next week. Markets on multi‑year outcomes-economic growth, technological adoption, regulatory shifts-are more aligned with the kind of hedging and planning individuals and companies actually need.
3. Balanced incentives for liquidity and insight
Structures that reward early accurate information, not just raw capital, can prevent markets from being dominated solely by whales chasing volatility.
4. Composability with other financial tools
If prediction markets can be seamlessly integrated into wallets, DeFi protocols, and accounting systems, they move from being curiosities to core infrastructure.
How hedging might work in practice
To see how this could reduce reliance on fiat, consider a simple example.
Suppose a freelancer is paid in a volatile crypto asset. Their rent, groceries, and other expenses, however, are relatively fixed in local currency terms. Today, they would typically convert a portion of their income into fiat or a fiat‑pegged stablecoin to lock in their ability to pay bills.
With mature prediction markets, they could instead:
– Hold the bulk of their wealth in crypto.
– Enter into markets whose outcomes correlate with their main risks-such as crypto price drops, local inflation spikes, or economic downturns.
– Adjust their hedge size based on time horizons (one month, six months, a year).
If those markets are liquid and well‑priced, the combined position (crypto plus hedges) can closely track the purchasing power they need, even though they never directly hold fiat. For many users, that could be “stable enough” to meet everyday needs.
Corporate and institutional use cases
Buterin’s vision also has implications far beyond individual traders.
For businesses and institutions, prediction‑based hedging could become an alternative or complement to traditional derivatives and insurance. A company exposed to:
– Commodity price swings,
– Regulatory risk in a specific jurisdiction,
– Or technological disruption in its industry,
could use prediction markets to offload part of that risk to willing counterparties worldwide. Unlike bespoke contracts, these positions would be standardized, on‑chain, and globally accessible.
If such tools became mainstream, the need to constantly rebalance between multiple fiat currencies could diminish. Balance sheets might be denominated in crypto or baskets of assets, with prediction‑market hedges providing the fine‑tuning that fiat currencies currently approximate through macroeconomic management.
Obstacles: regulation, liquidity, and user experience
The path from today’s speculative markets to Buterin’s imagined infrastructure is far from straightforward.
– Regulation: Many jurisdictions treat prediction markets as gambling or heavily regulate them as derivatives. Expanding them to cover politically sensitive topics or macroeconomic outcomes invites intense scrutiny.
– Liquidity fragmentation: For hedging to be credible, markets need deep, reliable liquidity. Yet high‑quality, long‑dated questions about real‑world events have historically struggled to attract the same participation as simple price bets.
– Complexity for end users: Translating sophisticated hedge strategies into simple, understandable interfaces is a major design challenge. If users can’t see, at a glance, how a given position protects them, adoption will lag.
– Oracle and resolution risk: High‑stakes markets on real‑world events require extremely robust mechanisms to determine outcomes. Any perception of bias in oracles or ambiguity in resolution can quickly erode trust.
Buterin’s intervention implicitly challenges builders to tackle these problems head‑on rather than chasing short‑term volume.
Cultural shift: from degen bets to serious signals
Beyond technical hurdles, there is a cultural issue. Crypto culture has often celebrated “degen” behavior: high‑risk, high‑leverage bets, memes, and a casino‑like thrill. That mindset does produce liquidity, but not the kind of signals Buterin wants prediction markets to generate.
To become a true “information infrastructure,” these systems need a different ethos:
– Valuing accuracy over entertainment.
– Rewarding long‑term forecasting skill, not just momentum trading.
– Attracting domain experts-economists, scientists, policy analysts-who care about getting the future right, not just extracting yield.
If that cultural pivot occurs, prediction markets could become a bridge between specialized knowledge and everyday financial decisions.
What it would mean to “replace fiat”
When Buterin quips, “we’re gonna replace fiat currency,” he is not necessarily predicting that dollars and euros will disappear overnight. Rather, he is pointing to a world where the *functions* of fiat-stability, unit of account, medium of exchange-can be replicated and even improved upon inside a crypto‑native, market‑based system.
In such a world:
– People and institutions could denominate value in crypto or baskets of assets.
– Stability would be engineered through dynamic hedging rather than issued by central banks.
– Information about the future-embedded in prediction market prices-would directly shape how people allocate resources today.
Whether that world ever fully arrives is uncertain. But Buterin’s critique makes one thing clear: if prediction markets continue to serve primarily as speculative side‑shows, they will fall far short of their potential. If they evolve into robust tools for hedging real‑world risk, they might not just complement fiat money-they could fundamentally redefine what “money” and “stability” mean in a world of programmable finance.