a16z Crypto: AI adjudication mechanisms may solve the scalability bottleneck of prediction markets

Jinse Finance reported that a16z Crypto published an article titled "How AI 'Judges' Can Scale Prediction Markets," which pointed out that the biggest challenge prediction markets face is not "pricing the future," but determining what actually happened. Similar issues frequently arise in some small-scale events, where incorrect or non-transparent settlement mechanisms can undermine market trust, liquidity, and the accuracy of price signals. Industry experts suggest introducing large language models (LLMs) as arbiters in prediction markets, including on-chain rule commitments, resistance to manipulation, enhanced transparency, and increased neutrality. For example, when creating a contract, the specific LLM model, timestamp, and judgment prompt can be encrypted and recorded on the blockchain, allowing traders to understand the complete decision-making mechanism in advance. The model's weights are fixed and cannot be easily tampered with, reducing the risk of cheating. The settlement mechanism is open and auditable, with no arbitrary human rulings. The AI judgment mechanism can significantly improve the efficiency and scalability of prediction market settlements while ensuring transparency and fairness.