What Should the New Financial Infrastructure of the AI Era Look Like?
The article explores the limitations of current prediction markets, which, despite their success in aggregating information through risk-sharing (e.g., accurately predicting election outcomes), suffer from a flawed economic model: their most valuable output—information—becomes a free public good once generated. This restricts their viability to entertainment-driven domains like elections and sports, while critical areas (geopolitical risk, regulatory outcomes, etc.) remain unaddressed.
The author proposes "Cognitive Finance," a new infrastructure designed from first principles for the AI and crypto era. Key components include:
- **Private Markets**: Using trusted execution environments (TEEs) to keep prices confidential, enabling entities (e.g., hedge funds, corporations) to pay for exclusive signals without leakage to competitors.
- **Combinatorial Markets**: Moving beyond isolated events to maintain a joint probability distribution, where trades update correlated outcomes simultaneously, akin to a neural network.
- **Agent Ecosystems**: AI-native markets where specialized agents (trading, evaluation, information acquisition) operate with strict isolation between price access and information sourcing to prevent self-cannibalization.
- **Human Intelligence**: Interfaces allowing humans to contribute knowledge via natural language without seeing prices, compensated based on predictive accuracy.
The vision is a decentralized, composable infrastructure where AI systems and humans collaboratively build a continuously updated, probabilistic world model. This transcends today’s prediction markets, aiming to transform decision-making in finance, supply chains, geopolitics, and beyond by making uncertainty tradable and knowledge liquid.
marsbit12/26 11:06
