When Did “Recommendation” Quietly Become “Decision”?

Many AI systems are framed as decision support, but in practice they operate as decision replacement. This shift rarely happens by design. It happens through convenience, speed, and repetition. Humans stop challenging outputs not because they trust the model, but because questioning it slows the system down.

This is where most AI Audits quietly fail. They confirm that a human is “in the loop” but never examine whether that human still has real cognitive leverage. A person who only clicks “approve” is not oversight. They are latency.

AI Audit must trace how recommendations harden into defaults, how defaults turn into policy, and how policy becomes invisible authority. If you don’t audit that transition, you’re not managing AI risk. You’re institutionalizing it.

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