[Interpreting this Prediction Market White Paper on GitHub from an Information Economics Perspective] A colleague forwarded me a white paper from GitHub: The author, Dr. Elias, cites Hayek's classic 1945 paper, "The Use of Knowledge in Society." This made me revisit Hayek's core argument from an economic perspective: market prices are a mechanism for aggregating dispersed knowledge. Prediction markets are a direct application of this theory—through trading, transforming each person's private information about the future into public probabilistic judgments. However, the reality is that information providers (informed traders) and liquidity providers (liquidity providers) are often not the same group of people. The former have information but limited funds, while the latter have funds but insufficient information. Traditional prediction markets cannot solve this "principal-agent" problem. OracleX's "behavioral proof" mechanism attempts to unify these two roles through incentive design: staking provides liquidity, prediction contributes information, and rewards are linked to information quality. This theoretically reduces information asymmetry and moral hazard. Of course, "incentive compatibility" is difficult to perfectly achieve in practice. This line of thinking deserves the attention of the academic community. We look forward to seeing empirical research. #InformationEconomics #PredictionMarkets #MechanismDesign #OracleX