Data governance and property rights under privacy constraints

Identify property rights and governance mechanisms for training data that enable efficient pooling and allocation while safeguarding privacy and preventing monopolization, and evaluate institutional designs (e.g., data trusts and cooperatives) and technical infrastructure (e.g., privacy-preserving computation and provenance tracking) to support market formation.

Background

The paper highlights tensions between individual data ownership (as in GDPR), platform-controlled aggregation, and open commons. Nonrivalry allows simultaneous use, but excludability is needed for markets. Section 6 calls for legal frameworks, institutional designs, and technical infrastructure to balance privacy, efficiency, and competition.

Historical precedents (e.g., oil, spectrum) show property-right choices shape market structure and long-run outcomes, motivating rigorous governance designs for data.