Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification

Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. This paper, presents an approach to evaluate bias present in automated facial analysis algorithms and datasets with respect to phenotypic subgroups.