2025
Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness
Stephen R Pfohl, Natalie Harris, Chirag Nagpal, David Madras, Vishwali Mhasawade, Olawale Elijah Salaudeen +9
NeurIPS 2025poster
Disaggregated evaluation across subgroups is critical for assessing the fairness of machine learning models, but its uncritical use can mislead practitioners. We show that equal performance across subgroups is an unreliable measure of fairness when data are representative of the relevant populations…