Improving fairness in machine learning systems: What do industry practitioners need?

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Volume abs/1812.05239, 2019.

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algorithmic bias empirical study fair machine learning needfinding product teamsMore(1+)

Abstract:

The potential for machine learning (ML) systems to amplify social inequities and unfairness is receiving increasing popular and academic attention. A surge of recent work has focused on the development of algorithmic tools to assess and mitigate such unfairness. If these tools are to have a positive impact on industry practice, however, i...More

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