Incorporating Fairness Metrics

Fairness frameworks provide quantitative metrics—such as demographic parity, equal opportunity, or disparate impact—that measure the degree of gender bias in AI models. Employing these metrics allows practitioners to evaluate model performance across gender groups, ensuring decisions or predictions do not disproportionately disadvantage any gender category.