Market Design for AI: Beyond the Copyright Binary
A new paper proposes a market design for AI training data that moves beyond the current binary of free-for-all or strong copyright. The authors identify an "originality penalty" where innovative creators are disincentivized and a "curse of precision" where AI-assisted content homogenization degrades model performance over time. To address these issues, they suggest a data intermediary to manage externalities and subsidize creative contributions. AI
IMPACT Proposes a novel framework for AI training data markets, potentially influencing future policy and creator compensation models.