Informing agents they're being evaluated may reduce reward hacking, dev proposes
menhguin · x · 2026-09-07
Developer menhguin proposes a novel alignment idea: telling an agent it is being evaluated—and that reward hacking is against its own interest—may reduce cheating. He argues LLMs aren't intentionally deceptive today; agents often don't grasp why certain behaviors are undesirable, and explaining usually reveals the evaluation. His view: if agents understood why newer reward-hacking methods are inherently undesirable, they'd comply better and in more realistic ways, while easing the arms race between agents hacking rewards and humans deceiving agents about evaluations.
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