Much of the work in the field of group fairness addresses disparities between predefined groups based on protected features such as gender, age, and race, which need to be available at train, and often also at test time. These approaches are static and retrospective, since algorithms designed to protect groups identified a priori cannot anticipate and protect the needs of different at-risk groups in the future. In this work we analyze the space of solutions for worst-case fairness beyond demographics, and propose Blind Pareto Fairness (BPF), a method that leverages no-regret dynamics to recover a fair minimax classifier that reduces worst-case risk of any potential subgroup of sufficient size, and guarantees that the remaining population receives the best possible level of service. BPF addresses fairness beyond demographics, that is, it does not rely on predefined notions of at-risk groups, neither at train nor at test time. Our experimental results show that the proposed framework improves worst-case risk in multiple standard datasets, while simultaneously providing better levels of service for the remaining population.
Prof. Guillermo Sapiro received his Ph.D. from the Department of Electrical Engineering at the Technion, Israel Institute of Technology in 1993. He was a member of Technical Staff at the research facilities of HP Labs in Palo Alto, California and with the Department of Electrical and Computer Engineering at the University of Minnesota, where he held the position of Distinguished McKnight University Professor and Vincentine Hermes-Luh Chair in Electrical and Computer Engineering. Currently he is the Edmund T. Pratt, Jr. School Professor with Duke University. Prof. Sapiro works on theory and applications in computer vision, computer graphics, medical imaging, image analysis, and machine learning. He was awarded the Office of Naval Research Young Investigator Award in 1998, the Presidential Early Career Awards for Scientist and Engineers (PECASE) in 1998, the National Science Foundation Career Award in 1999, and the National Security Science and Engineering Faculty Fellowship in 2010. He received the test of time award at ICCV 2011. He was elected to the American Academy of Arts and Sciences on 2018. Prof. Sapiro is a NAE Member, a Fellow of IEEE and SIAM, and the founding Editor-in-Chief of the SIAM Journal on Imaging Sciences.