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Benchmarking Intersectional Biases in NLP

50 citations0/0 files storedConference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)

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Ethics and Social Impacts of AI Natural Language Processing Techniques Hate Speech and Cyberbullying Detection

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John Lalor, Yi Yang, Kendall Smith, Nicole Forsgren, Ahmed Abbasi. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2022.

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2019HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case 2021A Survey on Bias and Fairness in Machine Learning 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification 2014Big Data's Disparate Impact 2017Semantics derived automatically from language corpora contain human-like biases 2018Word embeddings quantify 100 years of gender and ethnic stereotypes 2020Language (Technology) is Power: A Critical Survey of “Bias” in NLP 2019A comparative study of fairness-enhancing interventions in machine learning

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2023Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness 2023A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges 2023Fairness in Language Models Beyond English: Gaps and Challenges 2024Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines 2023Causal-Debias: Unifying Debiasing in Pretrained Language Models and Fine-tuning via Causal Invariant Learning

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