Human-in-the-loop is not oversight.
A note that real AI oversight starts before decision-time review, because machine-shaped orientation can make late human approval weak.
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A note that real AI oversight starts before decision-time review, because machine-shaped orientation can make late human approval weak.
A case that oracle-style AI trains dependency, while long-lived entities use time, scarcity, and continuity to damp addictive loops.
A case that AI belongs in memory and stabilization layers, while humans retain judgment and direction under uncertainty.
A clarification that cognition is layered and that lived-with AI depends on local persistence, limits, time, and consequence rather than superhuman scale.
A case that safe AI defaults to refusal, waiting, escalation, and bounded judgment rather than blind compliance.