a16z Crypto: AI-based judgment mechanisms may solve the scalability bottleneck of prediction markets

The a16z Crypto article "How AI 'Judges' Expand the Scale of Prediction Markets" points out that the biggest challenge facing prediction markets is not "pricing the future," but rather determining what actually happened. Similar issues frequently arise in some small-scale events, where erroneous or opaque 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, specific LLM models, timestamps, and judgment prompts could be encrypted and recorded on the blockchain at the time of contract creation, allowing traders to understand the complete decision-making mechanism in advance. The model weights would be fixed and not easily tampered with to reduce the risk of cheating, and the settlement mechanism would be publicly auditable with no arbitrary human rulings. The AI judgment mechanism could significantly improve the efficiency and scalability of prediction market settlements while ensuring transparency and fairness.