Discrimination-Aware Process Mining: A Discussion

Lecture notes in business information processing, pp. 101–113

Abstract

Abstract Organizations increasingly use process mining techniques to gain insight into their processes. Process mining techniques can be used to monitor and/or enhance processes. However, the impact of processes on the people involved, in terms of unfair discrimination, has not been studied. Another neglected area is the impact of applying process mining techniques on the fairness of processes. In this paper, we overview and categorize the existing fairness concepts in machine learning. Moreover, we summarize the areas where fairness is relevant to process mining and provide an approach to applying existing fairness definitions in process mining. Finally, we present some of the fairness-related challenges in processes.

Authors 3

1. Timo Pohl Aachen Process and Data Science Chair

   RWTH Aachen University

   Affiliation as printed

   Process and Data Science Chair (PADS), RWTH Aachen University, Aachen, Germany

2. Mahnaz Sadat Qafari corresponding Aachen Process and Data Science Chair

   RWTH Aachen University

   Affiliation as printed

   Process and Data Science Chair (PADS), RWTH Aachen University, Aachen, Germany

3. Wil M. P. van der Aalst Aachen Process and Data Science Chair

   RWTH Aachen University

   Affiliation as printed

   Process and Data Science Chair (PADS), RWTH Aachen University, Aachen, Germany