758 citations · 1.8k across the 31 of their papers we have counts for
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Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support
Michael Madaio, Lisa Egede, Hariharan Subramonyam +2
Various tools and practices have been developed to support practitioners in identifying, assessing, and mitigating fairness-related harms caused by AI systems. However, prior resea…
Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data
Aaron Schein, Anjali Nagulpally, Hanna Wallach +1
We present a new non-negative matrix factorization model for bounded-support data based on the doubly non-central beta (DNCB) distribution, a generalization of the beta dis…
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé +2
We take inspiration from the study of human explanation to inform the design and evaluation of interpretability methods in machine learning. First, we survey the literature on huma…
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs
Solon Barocas, Anhong Guo, Ece Kamar +5
Disaggregated evaluations of AI systems, in which system performance is assessed and reported separately for different groups of people, are conceptually simple. However, their des…