By considering intersectionality, algorithm designers can move beyond single-axis fairness metrics and develop models that account for overlapping social identities. This promotes equitable outcomes across a wider range of demographic intersections rather than optimizing only for the majority.

By considering intersectionality, algorithm designers can move beyond single-axis fairness metrics and develop models that account for overlapping social identities. This promotes equitable outcomes across a wider range of demographic intersections rather than optimizing only for the majority.

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