The Truth Dilemma of Oracle Machines: Examining the Challenges of Decentralization through the Zelensky Suit Incident

Recently, a prediction market regarding Zelensky's attire has sparked widespread discussion. This is not just a simple system failure, but it reveals a fundamental flaw in the Oracle Machine system. When the profits brought by corruption exceed its costs, facts become commodities that can be purchased at a high price.

$200 million clothing controversy

At a NATO summit, Zelensky's attire became the focus of attention. Mainstream media widely reported that he attended in a suit, while the trading volume of related prediction markets reached as high as $200 million. However, an Oracle Machine system unexpectedly provided results that contradicted the general perception.

The emergence of this result is not due to any controversy surrounding the facts themselves, but rather because some people who control the Oracle Machine have placed huge bets on the "deny" option. They can change the outcome simply by leveraging their voting power while facing almost no substantial risk.

Insider Manipulation by Oracle Machines

There is an undeniable problem with human-led Oracle Machine systems: the biases of human nature. In this event:

• Some large holders have bet on the "no" option
• Faced with potential losses, they choose to manipulate the vote rather than accept the results.
• More than 23 million tokens (worth about $25 million) were used to reverse the outcome.

This behavior deviates from the original intention of Decentralization and is essentially large fund holders protecting their own interests. With sufficient funds and operations, the importance of facts is diminished, and the outcome becomes the ultimate deciding factor.

Broader Trust Crisis

The impact of this issue extends far beyond a single platform or institution. Human-led Oracle Machine systems commonly face various manipulation risks and incentive mechanism design flaws.

It is worth noting that similar issues had already emerged in the Ukrainian mining trading case back in March 2025. All major prediction markets face the same fundamental challenge: when humans hold the power to define truth, truth can become a tool for profit.

Oracle Machine's Evolution: From Human Decision-Making to Intelligent Judgment

The fundamental solution to the problem of human-dominated Oracle Machine is to completely eliminate human intervention. AI-driven Oracle Machine systems are expected to change the status quo:

• No financial motivation: The model does not hold positions and does not care about the outcome ownership.
• Fair decision-making rules: identical training parameters and inputs will produce consistent evaluation standards.
• Transparent reasoning process: Each decision step is traceable and reviewable.
• High processing capability: can analyze large amounts of data sources simultaneously without manual intervention.

Although there are still some errors, these errors are random statistical noise that is difficult to exploit intentionally. With clear standards and reliable data support, advanced AI models have demonstrated production-level accuracy, and their performance continues to improve.

Build a Trustworthy Oracle Machine System

The prediction market of the future must completely eliminate human factors from the determination of truth. An ideal framework should include:

• Preset information source levels: such as Reuters > BBC > local news > blogs
• Cryptographic proof of data source: ensuring that the information has not been tampered with
• Multi-AI system consensus: multiple independent AI systems reach a conclusion
• Traceable decision-making process: Each judgment has a complete audit trail.
• Immutable evidence: Stored on the blockchain, ensuring that the evidence cannot be altered or deleted.

Broader Impact

The challenges of prediction markets are merely a microcosm of larger issues. In an age where information can easily be manipulated, we need to establish systems that can ascertain objective facts. This need is not limited to prediction markets, but also involves:

• Verification of election fairness
• Validation of scientific research
• News Authenticity Verification in the Era of Deep Fakes
• Preservation and tamper-proofing of historical records
• Corporate transparency and accountability mechanisms

The prediction market faces a critical choice: whether to continue believing that humans driven by economic interests can make fair judgments, or to build a truth determination system that completely eliminates human biases. The actual operation of the market has provided the answer—when an obvious outcome is unexpectedly negated, the fundamental issues of the system are laid bare.

The technology to solve this problem already exists. In this era, determining the truth is crucial and should not be decided by the highest bidder.