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2012 IEEE 12th International Conference on Data Mining Workshops
Exploring Discrimination: A User-centric Evaluation of Discrimination-Aware Data Mining
Brussels, Belgium Belgium
December 10-December 10
ISBN: 978-1-4673-5164-5
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.
Index Terms:
Data mining,Educational institutions,Training,Sociology,Statistics,Usability,Atmospheric measurements,Mechanical Turk,Discrimination-aware data mining,Discrimination discovery,Evaluation,User studies,Responsible data mining
Citation:
Bettina Berendt, Soren Preibusch, "Exploring Discrimination: A User-centric Evaluation of Discrimination-Aware Data Mining," icdmw, pp.344-351, 2012 IEEE 12th International Conference on Data Mining Workshops, 2012
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