Feb. 13, 2018
All people are created equal, but in the eyes of the algorithm, not all faces are just yet.A new study from MIT and Microsoft r...
Buolamwini, J., Gebru, T. "Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification." Proceedings of Machine Learning Research 81:1–15, 2018 Conference on Fairness, Accountability, and Transparency
Joy Buolamwini showed facial-recognition systems consistently giving the wrong gender for famous women of color.
Examination of facial-analysis software shows error rate of 0.8 percent for light-skinned men, 34.7 percent for dark-skinned women.