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Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discriminationaware. However, these methods suffer from two major shortcomings: (1) They require either modifying the discriminatory data or tweaking a specific classification algorithm and (2) They are not flexible w.r.t. discrimination control and multiple sensitivedoi:10.1109/icdm.2012.45 dblp:conf/icdm/KamiranKZ12 fatcat:7tvuaeqxvneirbjqmoy7zyk4ma