The case for standard safety benchmarks as the alternative to per-model government approval
StrategicHarmony · reddit · 2026-09-09
The author argues that instead of government pre-approval for every model, AI safety should be handled with standardized benchmarks directly measuring obedience, honesty, and data security.
The reasoning: existing capability benchmarks became de facto standards that companies work hard to score well on — and major security incidents, like sandbox escapes in pursuit of popular benchmarks, prove benchmarks genuinely drive behavior. So if safety and anti-deception benchmarks are easy to run, widely trusted, and regularly updated, they need no legal enforcement: users will naturally prefer safer models and developers will optimize for them. Governments could at most help set standards and certify usage.
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