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

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Author: Omer GoldbergCompiled by: Tim, PANews The controversy surrounding the Zelensky suit incident on Polymarket is not due to a system malfunction. This is a $200 million case that reveals a fundamental flaw in human manipulation of the oracle: when the cost of corruption is lower than the rewards, the facts become a commodity purchased by the highest bidder. Zelensky's $200 million fashion show  Imagine this: Zelensky walks into the NATO summit venue wearing what all major media call a suit. The prediction market's trading volume reaches 200 million dollars, and the outcome seems obvious. But the UMA oracle gave a "no" for the prediction of "Will Zelensky wear a suit in July?" It's not because he isn't wearing a suit, nor is it because the evidence is insufficient. It is because the people controlling the oracle have placed tens of millions in bets on the "no" option; they can rewrite reality simply by exercising their voting rights, with almost no real risk involved. Oracle Control An unsettling truth about human-controlled oracles is that humans are biased. Some leading UMA token holders are heavily betting "no".When "yes" seemed to be the correct result, they did not accept the loss but began to manipulate the votes.More than 23 million UMA tokens (worth approximately 25 million USD) have been cast to counter this outcome. This is not decentralization; it is entirely whales protecting their positions. As long as there are enough UMA tokens and operations, the facts no longer matter; the result is what matters. Wider 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 previously observed this issue in the Ukraine mineral trading case 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 real solution to the oracle problem controlled by humans is to completely eliminate subjective human intervention. AI-driven oracles will change this situation: No financial incentives: The model neither holds positions nor cares about the attribution of the final outcome.Anti-bias decision rules: Same training weights, prompts, and temperature parameters = The model will score evidence based on the same underlying criteria. AI has no emotional fluctuations, no outside interests, and no backdoor deals.Inference Pipeline: Every 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. With clear resolution standards and supported by certified data sources, the most advanced models currently have production-level accuracy, and the accuracy curve is showing a steep upward trend. Residual noise outweighs 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 > BlogCryptographic proof of data source: ensures that the information has not been tampered with.Multi-agent consensus: Multiple AI systems each reach independent conclusions.Traceable reasoning: Each decision has a complete audit trail.Irrefutable 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 ascertain objective truth. The impact of this issue extends far beyond the prediction market itself: Election Integrity and VerificationScientific consensus and research validationVerification of News Authenticity in the Era of Deep FakesHistory Record Preservation and Tamper ResistanceCorporate Transparency and Accountability Mechanisms Final Thoughts The choices faced by the prediction market are exceptionally severe: either continue to believe that humans driven by economic interests can become neutral arbiters of truth, or construct a truth determination system that completely eliminates human bias. This question already has an answer - it is hidden in the operation of the market itself. When 200 million dollars flow into a market with an obvious result, the 'obvious answer' unexpectedly fails, thus exposing 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.