We ask whether an artificial intelligence (AI)-enabled process monitor’s alarms remain informative beyond its commissioned operating range. Conformal alarm rules rely on exchangeability, which deployment shifts can break. Conditioning calibration on the operating point restores validity, not necessarily informativeness: the certificate constrains only the fault-free calibration law, so a diagnostic relying only on that law cannot identify the loss without an additional assumption. Across ten one-class detectors in a seed-controlled Tennessee Eastman campaign with counterfactual twins, validity holds at every evaluated level while informativeness decays. Resolved at ×0.001, the loss is a ramp, not a step, crossing a declared 0.70 floor at ×0.825. There the plant is bistable: fault-free episodes settle into a steady mode or an unsteady one with the purge valve on its stop, the detectors cannot rank the fault inside the unsteady mode, and informativeness above chance scales with the square of the steady share. Disabling that protective override removes the unsteady mode and lifts far-edge receiver operating characteristic (ROC) area from 0.47 to 0.76. Supervised classifiers recover the ranking only when trained on labelled faults in that settled state. Fault-free commissioning measurements, mapped by a curve fitted on labelled faults, predict the loss to a mean absolute ROC-area error of 0.041.
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Saydirasulovic et al. (2026) studied this question.
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