On the ethics of utilizing prediction markets for forecasting hydrological catastrophe

As peer-to-peer prediction markets increasingly allow real-money wagering on environmental events, public scientific agencies are being drawn into the role of financial “settlement oracles,” the designated sources of truth against which contracts resolve. The purpose of the present paper is to examine the ethical and operational risks that follow when AI-accelerated hydrologic forecasting becomes the settlement basis for such markets, with attention to flood and drought management. We develop a taxonomy of settlement oracles that distinguishes physical observations, certified records, model forecasts, official warnings, and administrative classifications, and we reframe the parallel between forecasting and market workflows as a comparison of partially analogous information systems whose prices are not calibrated probabilities. Three cases selected for maximum variation ground the analysis: a real-money contract settling on the observed crest of a fatal river flood, a federal prosecution alleging trading on classified government information, and a contract settling on a federal drought classification. Additionally, a stylized incentive model shows that the expected profit from manipulating a settlement value grows with market liquidity, and thus that thin markets deter manipulation only by accident. Applying consequentialist, deontological, and noxious-market frameworks across five modes of professional engagement, we conclude that trading by forecasters on products they produce or can influence is unethical without qualification, that agency use of market signals is at most conditionally permissible, and that the audit benefits claimed for these markets can be captured through sanctioned adversarial testing. We close with recommendations for agencies, professional societies, regulators, platforms, and affected communities.