based on data that contains biased human decisions. This has led to a call for fairness-aware machine learning. However …, fairness is a complex concept which is also reflected in the attempts to formalize fairness for algorithmic decision making …. Statistical formalizations of fairness lead to a long list of criteria that are each flawed (or harmful even) in different …

bias and fairness in machine learning, and discusses how such debates could profit from VSD-derived insights and …

Most definitions of algorithmic bias and fairness encode decisionmaker interests, such as profits, rather than the … within groups. The literature emphasizes some apparent contradictions between different notions of fairness, and between … fairness and profits. These contradictions vanish, however, when profits are maximized. Existing work involves conceptual …