41 citations · 90 across the 8 of their papers we have counts for
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cs.CY2021★ 41 cited
Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off Research
A. Feder Cooper, Ellen Abrams
Across machine learning (ML) sub-disciplines, researchers make explicit mathematical assumptions in order to facilitate proof-writing. We note that, specifically in the area of fai…
cs.CY2020★ 3 cited
Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research
A. Feder Cooper
Across machine learning (ML) sub-disciplines researchers make mathematical assumptions to facilitate proof-writing. While such assumptions are necessary for providing mathematical…
cs.CY2020★ 19 cited
Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems
A. Feder Cooper, Karen Levy, Christopher De Sa
Trade-offs between accuracy and efficiency pervade law, public health, and other non-computing domains, which have developed policies to guide how to balance the two in conditions…