# A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classification

@inproceedings{Rava2021ABS, title={A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classification}, author={Bradley Rava and Wenguang Sun and Gareth M. James and Xin Tong}, year={2021} }

We study fairness in classification, where one wishes to make automated decisions for people from different protected groups. When individuals are classified, the decision errors can be unfairly concentrated in certain protected groups. We develop a fairness-adjusted selective inference (FASI) framework and data-driven algorithms that achieve statistical parity in the sense that the false selection rate (FSR) is controlled and equalized among protected groups. The FASI algorithm operates by…

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