交叉歧視

Risk Description

Biases in individual protected characteristics (gender, race, age) produce amplified effects at intersections. For example, AI system discrimination against "older women" or "Black disabled persons" may be more severe than against single-characteristic groups. Traditional fairness testing typically only detects single-dimension bias, failing to discover intersectional discrimination. Groups affected by intersectional discrimination are often society most vulnerable.