Predictive markets are not only experiments in collective intelligence but also power struggles over “who has the authority to define reality.”
(Background: Polymarket manipulated by a oracle! Over $7 million bet on “truth turned upside down” with winners and losers)
(Additional context: US lawmakers propose legislation to ban civil servants from using prediction markets for “insider trading”! Polymarket suspected of leaks and plans to arrest Maduro)

Table of Contents

• 1. The frequent “semantic traps” in prediction markets
• 2. The failure boundary of “code is law”
• 3. The “last mile” of truth is hard to decentralize

Whether the US has “invaded” Venezuela is a semantic judgment that directly determines a bet worth millions of dollars.

You might find it counterintuitive, since in the real world, the US has indeed taken a series of actions against Venezuela, including military deployments and direct interventions. In everyday language and media narratives, such actions are easily understood as “invasion.”

However, the final settlement did not align with some users’ expectations—Polymarket did not recognize US military actions as an “invasion” under its rules at the time of judgment, thus negating the “Yes” option and sparking protests from bettors.

This is a familiar yet highly representative controversy, exposing a long-standing but often overlooked structural issue in prediction markets: When dealing with complex real-world events, what justifies and who defines “facts” in decentralized prediction markets?

1. The frequent “semantic traps” in prediction markets

It’s “not new” because similar semantic disputes have occurred multiple times in prediction markets.

Indeed, such situations are common on Polymarket, especially around political figures and international affairs. The platform has repeatedly seen rulings that users find “counterintuitive.” Some predictions, almost undisputed in reality, end up in repeated appeals and reversals on-chain; others deviate significantly from most users’ judgments.

An even more extreme case is during dispute resolution, where oracle mechanisms allow token holders to vote, enabling some high-stakes topics to be “twisted” by top players through voting power…

These disputes share a common point: they are often not technical issues but social consensus problems. For example, a widely discussed case involved whether Ukrainian President Zelensky wore a suit at a specific time:

In reality, last June, Zelensky appeared in formal attire at a public event, and multiple sources like BBC and designers confirmed it was a suit. By normal logic, the matter should have been settled. But on Polymarket, this seemingly clear fact turned into a tug-of-war involving hundreds of millions of dollars.

During this period, the probabilities for “Yes” and “No” fluctuated wildly, with some engaging in high-risk arbitrage, achieving huge short-term gains, yet the final settlement remained delayed.

The core issue is that Polymarket relies on the decentralized oracle UMA for result adjudication, which allows token holders to participate in dispute voting. This makes it easy for top players to manipulate the outcome of certain topics.

More controversially, the platform has not denied that this mechanism could be exploited but insists on “rules are rules,” refusing to adjust the judgment logic afterward, ultimately allowing large capital to overturn results through the rules themselves.

Cases like these provide a highly illustrative entry point for understanding the boundaries of prediction market systems.

2. The failure boundary of “code is law”

Objectively, prediction markets are now regarded as one of the most imaginative applications of blockchain, evolving from simple tools for “betting” or “predicting the future” to frontlines for institutions, analysts, and even central banks to observe market sentiment.

But all of this relies on a premise: Prediction questions must be answerable with clarity.

Blockchain systems are naturally good at handling deterministic issues—such as whether assets have arrived, whether states have changed, or whether conditions are met. Once these results are written on-chain, they are almost impossible to tamper with.

However, prediction markets often face a different kind of question: Has a war broken out? Has an election ended? Does a certain political or military action constitute a specific judgment? These questions are not inherently codifiable; they heavily depend on context, interpretation, and social consensus rather than a single, verifiable objective signal.

Therefore, regardless of the oracle or adjudication mechanism used, subjective judgment is almost unavoidable when translating real-world events into settled results.

This is why, in many disputes on Polymarket, the disagreement between users and the platform is not about whether the fact exists but about which interpretation of reality can be settled as the truth.

Ultimately, when this interpretive authority cannot be fully formalized into code, the grand vision of “code is law” encounters its fundamental limits in the face of complex social semantics.

3. The “last mile” of truth is hard to decentralize

In many decentralization narratives, “centralization” is often seen as a flaw. But I believe, in the specific context of prediction markets, the opposite is true.

Because prediction markets do not eliminate the authority to adjudicate; they transfer it from one position to another:

• Trading and settlement phases: Highly decentralized, automated;
• Definition and interpretation phases: Highly centralized, dependent on rules and adjudicators;

In other words, decentralization addresses the trustworthiness of execution but cannot avoid the reality of concentrated interpretive authority. This is why the appealing concept of “code is law” in the blockchain world often falls short in prediction markets—because code cannot generate social consensus; it can only faithfully execute predefined rules.

When the rules themselves cannot encompass all the complexities of reality, the authority to adjudicate inevitably returns to “humans.” The difference is, this authority no longer appears as an explicit arbiter but is embedded in problem definitions, rule interpretations, and adjudication processes.

Returning to the dispute over Polymarket, it does not mean prediction markets have failed, nor does it mean that decentralization is an illusion. On the contrary, such disputes remind us to reconsider the boundaries of prediction markets: They are very suitable for outcomes that are clear and well-defined but are inherently ill-suited for highly politicized, semantically ambiguous, and value-laden real-world issues.

From this perspective, prediction markets have never been about “who is right or wrong,” but about how, under given rules, markets can efficiently aggregate expectations. When the rules themselves become a source of dispute, the system exposes its institutional boundaries.

The recent controversy over whether Venezuela was “invaded” illustrates that, in dealing with complex real-world events, decentralization does not mean the absence of adjudicators but that the authority to decide is more covertly embedded.

For ordinary users, what truly matters may not be whether prediction markets are “decentralized,” but who has the power to define the problem when disputes arise—who decides which version of reality can be settled? Are the rules clear and predictable enough?

In this sense, prediction markets are not only experiments in collective intelligence but also power struggles over “who has the right to define reality.”

Understanding this allows us to find a closer approximation to certainty amid uncertainty.