Grossman‑Stiglitz Paradox for AI

Applying Grossman and Stiglitz’s insight — that people only produce costly information if they can capture returns — to artificial intelligence: if producing high‑quality knowledge or labels is costly and rewards are misaligned, AI models will systematically reflect informational gaps and under‑invested knowledge, not because of algorithmic failure but because economics disincentivizes creation of that knowledge. — This reframes AI safety and governance as an incentives problem (who funds and is rewarded for producing reliable knowledge), with implications for research subsidies, open data policy, and procurement rules.