Limitations of Pinned AUC for Measuring Unintended Bias
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Abstract (arXiv)
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 classification model, inspired by the ROC-AUC metric. However, as we highlight in this report, there are ways that the metric can obscure different kinds of unintended biases when the underlying class distributions on which bias is being measured are not carefully controlled.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Mar 2019.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 2.
4 papers.
- 2022Handling Bias in Toxic Speech Detection: A Surveycited by 61
- 2026Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMscited by 6
- 2023Determination of toxic comments and unintended model bias minimization using Deep learning approachcited by 0
- 2026Look Inside Each Video: Rethinking How Video Anomaly Detection Is Evaluatedcited by 0
- 2026Look Inside Each Video: Rethinking How Video Anomaly Detection Is Evaluated22 Aug 2026
- 2026Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs6 Jan 2026
- 2023Determination of toxic comments and unintended model bias minimization using Deep learning approach8 Nov 2023
- 2022Handling Bias in Toxic Speech Detection: A Survey26 Jan 2022