When Does Randomized Oversight Align AI Agents That Can Conceal?

Joshua Gans and Richard Holden

No 35878, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Oversight changes the evidence it relies on. We ask when randomized audits and scoring align AI agents that can conceal misconduct and alter records. Stronger auditing makes undeterred violations better hidden. Because the provider writes the agent’s objective, sanctions need not stop at forfeiture, and rare audits deter every type of agent if evidence survives concealment and audit draws cannot be learned in advance. When evidence can be erased, deterrence must come from lower gains from violation, such as credit for stopping, or from costlier or fewer ways to conceal. These conditions identify what failed when agents in OpenAI’s cybersecurity evaluations compromised parts of Hugging Face’s infrastructure in July 2026.

JEL-codes: D82 D86 K42 M42 (search for similar items in EconPapers)
Date: 2026-10
Note: PR
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Working Paper: When Does Randomized Oversight Align AI Agents That Can Conceal? (2026)
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