3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.LG2021
Model Selection's Disparate Impact in Real-World Deep Learning Applications
Jessica Zosa Forde, A. Feder Cooper, Kweku Kwegyir-Aggrey +2
Algorithmic fairness has emphasized the role of biased data in automated decision outcomes. Recently, there has been a shift in attention to sources of bias that implicate fairness…
cs.CY2021
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…