Position: Token Taxes Can Mitigate AI's Economic Risks

Economic risks of AI deserve equal research attention to safety risks: The paper argues that while AI safety research focuses heavily on capability risks, "comparatively little work has studied how to mitigate the economic risks of AI," including wage erosion and tax base depletion that could mirror the 40-year wage stagnation during the first industrial revolution.

Token taxes offer a practical enforcement mechanism for AI governance: Unlike previous robot tax proposals, token taxes (usage-based surcharges on AI model inference) are "enforceable through existing compute governance infrastructure" and capture value "where AI is used rather than where models are hosted," making them technically feasible to implement.

Implementation requires solving specific technical and economic challenges: The paper identifies a staged audit pipeline (black-box token verification, norm-based tax rates, and white-box audits) as necessary for enforcement, while also highlighting the need for economic modeling to understand "cost pass-through and deadweight loss"—how taxes would affect prices and market efficiency.

Policymakers must address concerns about innovation and geopolitical competition: The authors acknowledge that token taxes "could stifle innovation" and discuss the risk that "AI superpowers" might veto such measures, suggesting that responsible AI governance requires balancing economic redistribution with maintaining technological progress and preventing regulatory capture.