Dr. Ravi Shroff won an Outstanding Paper Award at the 2022 International Conference on Machine Learning (ICML) for the paper "Causal Conceptions of Fairness and their Consequences." Less than 1% of accepted papers received an award.
As the authors explain: "Recent work highlights the role of causality in designing equitable decision-making algorithms. It is not immediately clear, however, how existing causal conceptions of fairness relate to one another, or what the consequences are of using these definitions as design principles...Our results highlight formal limitations and potential adverse consequences of common mathematical notions of causal fairness." For example, in high stakes decisions such as college admissions, "adhering to any of the common conceptions of causal fairness would simultaneously result in a lower number of degrees attained and lower student-body diversity, relative to what one could achieve by explicitly tailoring admissions policies to achieve desired outcomes."