8 citations · 12 across the 2 of their papers we have counts for
2 papers
stat.ML2019★ 8 cited
Limitations of Pinned AUC for Measuring Unintended Bias
Daniel Borkan, Lucas Dixon, John Li +3
This report examines the Pinned AUC metric introduced and highlights some of its limitations. Pinned AUC provides a threshold-agnostic measure of unintended bias in a classificatio…
cs.LG2019★ 4 cited
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
Daniel Borkan, Lucas Dixon, Jeffrey Sorensen +2
Unintended bias in Machine Learning can manifest as systemic differences in performance for different demographic groups, potentially compounding existing challenges to fairness in…