Fairness Through Awareness

This paper addresses the problem of discrimination in algorithmic decision-making. It introduces the concept of 'awareness' where the algorithm explicitly accounts for sensitive attributes (like race or gender) but only when these attributes are causally related to the outcome. The goal is to achieve fairness by mitigating discriminatory effects arising from statistical disparities in the data, while respecting individual autonomy and preventing reverse discrimination.