Battlecard: Accuracy Is Not Fairness
Handle the common objection that strong overall accuracy is enough to justify launch.
The model is accurate overall, so bias is not the real issue. Overall accuracy matters, but it is only one view. We still need to check who is underrepresented in the data, whether the label reflects unequal history, and whether error rates or harms differ across groups before we call this launch-ready. This response does not reject the metric. It places the metric in a broader fairness standard and moves the conversation toward evidence the team can actually inspect. Overall metrics can hide subgroup harm. A clean score can still come from a biased label. Thresholds and deployment policy can…
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