Methodological Blind Spots in Machine Learning Fairness: Lessons from the Philosophy of Science and Computer Science

31 Oct 2019Samuel DengAchille Varzi

In the ML fairness literature, there have been few investigations through the viewpoint of philosophy, a lens that encourages the critical evaluation of basic assumptions. The purpose of this paper is to use three ideas from the philosophy of science and computer science to tease out blind spots in the assumptions that underlie ML fairness: abstraction, induction, and measurement... (read more)

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