A data ethics officer is reviewing fairness metrics for a recidivism prediction model used in bail decisions. The model achieves equal accuracy across racial groups but has different false positive rates. Which fairness criterion is violated?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — c is correct because equalized odds requires both equal true positive rates AND equal false positive rates across groups — if false positive rates differ (meaning some groups are more often incorrectly labeled high-risk), equalized odds is violated even when overall accuracy is equal. A requires equal positive prediction rates across groups.
Full explanation below image
Full Explanation
C is correct because equalized odds requires both equal true positive rates AND equal false positive rates across groups — if false positive rates differ (meaning some groups are more often incorrectly labeled high-risk), equalized odds is violated even when overall accuracy is equal. A requires equal positive prediction rates across groups. B requires only equal true positive rates. D requires equal precision across groups.