AI Fairness at Subgroup Level : A Structured Literature Review

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Lämmermann, Luis ; Richter, Patrick ; Zwickel, Amelie ; Markgraf, Moritz:
AI Fairness at Subgroup Level : A Structured Literature Review.
In: Proceedings of the 30th European Conference on Information Systems (ECIS). - Timișoara, Romania , 2022

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Abstract

AI applications in production environments often fail to gain required acceptance by stakeholders due to unfairness issues. Research mostly investigates fairness on individual or group levels. However, increasing research indicates shortcomings in this two-fold view. Particularly, the non-inclusion of the heterogeneity within different groups leads to increasing demand for specific fairness consideration at the subgroup level. Subgroups emerge from the conjunction of several protected attributes. An equal distribution of classified individuals between subgroups is the fundamental goal. In this paper, we analyze the fundamentals of subgroup fairness, its integration in group and individual fairness. Based on a literature review, we analyze the existing concepts of subgroup fairness in research. Our paper contributes to the understanding of AI fairness by providing a deeper understanding of the underlying concepts and their implications on AI development in practice