Brussels, Belgium Belgium
Dec. 10, 2012 to Dec. 10, 2012
Discrimination-aware data mining (DADM) aims at deriving patterns that do not discriminate on ``unjust grounds'' such as gender, ethnicity or nationality. DADM safeguards can be very helpful for decision-support applications in fields such as banking or employment. However, constraining data mining to exclude a fixed enumeration of potentially discriminatory features is too restrictive. It should be complemented by exploratory DADM. We discuss these two forms of DADM and their requirements for evaluation, and we discuss and refine our DCUBE-GUI tool as a system for exploratory DADM. In a user study administered via Mechanical Turk, we show that tools such as DCUBE-GUI can successfully assist novice users in exploring discrimination in data mining.
Data mining, Educational institutions, Training, Sociology, Statistics, Usability, Atmospheric measurements, Mechanical Turk, Discrimination-aware data mining, Discrimination discovery, Evaluation, User studies, Responsible data mining
Bettina Berendt, Soren Preibusch, "Exploring Discrimination: A User-centric Evaluation of Discrimination-Aware Data Mining", ICDMW, 2012, 2013 IEEE 13th International Conference on Data Mining Workshops, 2013 IEEE 13th International Conference on Data Mining Workshops 2012, pp. 344-351, doi:10.1109/ICDMW.2012.109