CONCEPT
Normalization Error
The gradual erosion of evaluative standards that occurs when users accept AI outputs at a pace that precludes thorough evaluation — each individual acceptance rational, the accumulated effect a progressive lowering of the bar.
The fourth category in the Norman volume's expanded error taxonomy names a failure mode that emerges over time rather than in any single interaction. Each individual acceptance of AI output is rational: the output looks correct, immediate tests pass, the deadline presses. But the accumulated effect is a progressive lowering of the bar — a normalization of superficial evaluation that becomes the default rather than the exception. The user who evaluated carefully on Monday is evaluating hastily by Friday, not because she has become lazy but because the pace of production has trained her nervous system to treat evaluation as a bottleneck rather than a safeguard.
In The You On AI Field Guide
Norman observed a structurally identical phenomenon in studies of automation in aviation and nuclear power. Operators who worked with reliable automated systems gradually reduced their monitoring, because the systems almost never failed. When the systems did fail, the operators were slower to notice, slower to diagnose, and slower