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Found 3 papers, 1 papers with code
Capturing Covertly Toxic Speech via Crowdsourcing
We study the task of labeling covert or veiled toxicity in online conversations.
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
Unintended bias in Machine Learning can manifest as systemic differences in performance for different demographic groups, potentially compounding existing challenges to fairness in society at large.
Limitations of Pinned AUC for Measuring Unintended Bias
This report examines the Pinned AUC metric introduced and highlights some of its limitations.
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