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Although AI systems archive a great success in various societal fields, there still exists a challengeable issue of outputting discriminatory results with respect to protected attributes (e.g., gender and age). The popular approach to solving the issue is to remove protected attribute information in the decision process. However, this approach has a limitation that beneficial information for target tasks may also be eliminated. To overcome the limitation, we propose Fairness-aware Disentanglingdblp:conf/aaai/ParkH0B21 fatcat:qh3nagka75hivn7gs6cazahkeq