Position: AI Safety Requires Effective Controllability

AI safety is still largely framed as alignment: training models to follow human preferences, safety policies, and normative constraints. That framing has improved the behavior of modern language models, but aligned behavior does not by itself guarantee that a deployed agent can be stopped, overridden, or constrained once it operates in open-ended, interactive, and tool-using environments. A system may be safe in expectation and still fail to yield to explicit runtime authority under conflicting

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ethics.ai (26 May 2026), “Position: AI Safety Requires Effective Controllability,” evidence record 3670, https://ethics.ai/record/3670 (originally published by arXiv).

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