Zelensky's "200 million dollar suit controversy": When the Oracle Machine becomes a money-making tool, how can AI solve the "truth dilemma"?

Author: Omer Goldberg

Compiled by: Tim, PANews

The controversy surrounding the Zelensky suit incident on Polymarket is not a system failure. It is a $200 million case that reveals a fundamental flaw in human manipulation of oracles: when the cost of corruption is lower than the returns, the truth becomes a commodity purchased by the highest bidder.

Zelensky's $200 million fashion show

Imagine this: Zelensky walks into the NATO summit venue wearing an outfit that all major media refer to as a suit. The prediction market's trading volume reaches $200 million, and the outcome seems obvious.

However, the UMA oracle gave a "no" prediction for the question of whether Zelensky would wear a suit in July.

It's not because he wasn't wearing a suit, nor is it because the evidence is insufficient.

It is because those who control the oracle have placed tens of millions in bets on the "no" option, and they can rewrite reality simply by exercising their voting rights, with almost no real risk.

Oracle control

One unsettling truth about human-controlled oracles is that humans are biased.

• Some major UMA token holders are betting heavily on "no".
• When "yes" seems to be the correct result, they do not accept the loss, but instead start manipulating the votes.
• More than 23 million UMA tokens (worth about 25 million USD) were voted to counter this outcome.

This is not decentralization; it is completely the whales protecting their positions.

As long as there are enough UMA tokens and operations, the facts no longer matter; the result is what is key.

The broader oracle crisis

The impact of this issue extends far beyond Polymarket and UMA themselves. Human-controlled oracle systems are susceptible to various manipulation methods and face various traps and flaws in incentive mechanism design.

Although we use the Zelensky suit incident as a case study, it should be noted that we have previously observed this issue in the case of Ukrainian mineral trading in March 2025.

All major prediction markets face the same fundamental challenges.

When humans control the definition of truth, truth becomes a tool for profit.

The Evolution of Oracles: From Human Control to Intelligent Decision-Making

The only true solution to the oracle problem controlled by humans is to completely eliminate subjective human interference.

AI-driven oracles will change this situation:

• No financial incentives: The model neither holds positions nor cares about the final outcome.
• Anti-bias decision rule: Same training weights, prompts, and temperature parameters = The model will score evidence based on the same underlying criteria. AI has no emotional fluctuations, no off-field interest associations, and certainly no behind-the-scenes trading.
• Inference Pipeline: Each intermediate process can be recorded, reviewed, and replayed.
• Machine-level throughput capacity: Capable of processing thousands of data sources in parallel, without rest and without relying on any human intervention.

Residual errors still exist, but they belong to random statistical noise. This type of error is extremely difficult for traders to exploit. Supported by clear resolution standards and certified data sources, the most advanced models currently have production-level accuracy, and the accuracy curve is showing a steep upward trend.

residual noise surpasses carefully calculated lies

The future of prediction markets must completely exclude humanity from the determination of truth.

The specific form of this architecture is as follows:

• Predefined source hierarchy: Reuters > BBC > Local news > Blog
• Cryptographic proof of data source: ensuring that the information has not been tampered with.
• Multi-Agent Consensus: Multiple AI systems reach independent conclusions.
• Traceable Inference: Each decision has a complete audit trail.
• Immutable evidence: Proof stored on the blockchain that cannot be modified or deleted.

Truth Determination in the Post-Truth Era

Prediction markets are a microcosm of larger challenges. When Wikipedia can be edited, news can be manipulated, and "facts" become negotiable, we need to establish systems that can determine objective truth.

The impact of this issue extends far beyond the prediction market itself:

• Election Integrity and Verification
• Scientific Consensus and Research Verification
• Verification of News Authenticity in the Era of Deep Fakes
• History Record Preservation and Tamper Resistance
• Corporate Transparency and Accountability Mechanisms

Final Thoughts

The choices facing the prediction market are exceptionally severe: either continue to believe that humans driven by economic interests can become neutral arbiters of truth, or build a truth determination system that completely eliminates human bias.

This question already has an answer - it is hidden within the operation of the market itself. When 200 million dollars flows into a market with an obvious outcome, the "obvious answer" unexpectedly fails, revealing the true nature of the system.

The technology to solve this problem already exists.

The determination of truth is crucial and cannot be decided by the highest bidder.