Equity-sensitive machine learning

Equity-sensitive machine learning refers to developing algorithms that prioritize fair treatment and outcomes for different groups, especially those historically marginalized or disadvantaged. It incorporates awareness of social inequities into model training to prevent perpetuating biases, ensuring decisions (like lending, hiring, or resource allocation) benefit all groups more equitably. Essentially, it balances predictive accuracy with fairness considerations to promote social justice, recognizing that optimizing for one group shouldn't come at the unfair expense of others.