What Can Firms Do in the Face of Model Distillation?

The paper examines how model distillation—where smaller firms train models using data distilled from conversations with powerful proprietary models—affects market dynamics and user welfare. It analyzes a two-player economic model of an incumbent and a distilling competitor, exploring how the incumbent’s model traits influence distillation incentives and market outcomes. The study proposes regulatory interventions, showing that penalty-based rules can deter distillation but may harm competition, while self-distillation by incumbents can mitigate attacks and help preserve user surplus if deployed cost‑efficiently.

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