Zollo et al: Towards Effective Discrimination Testing for Generative AI
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Wang et al: Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Ways
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Panigutti et al: How to investigate algorithmic-driven risks in online platforms and search engines? A narrative review through the lens of the EU Digital Services Act
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Sandoval and Jing: Historical Methods for AI Evaluations, Assessments, and Audits
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Gerchick et al: Auditing the Audits: Lessons for Algorithmic Accountability from Local Law 144's Bias Audits
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Harvey et al: A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms
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De et al: Who Gets Heard? Calling Out the "Hard-to-Reach" Myth for Non-WEIRD Populations' Recruitment and Involvement in Research
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Urman et al: WEIRD Audits? Research Trends, Linguistic and Geographical Disparities in the Algorithm Audits of Online Platforms - A Systematic Literature Review
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Safir et al: Distributive Epistemic Injustice in AI Ethics: A Co-productionist Account of Global North-South Politics in Knowledge Production
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Schroeder et al: Disclosure without Engagement: An Empirical Review of Positionality Statements at FAccT
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Lepp and Smith: "You Cannot Sound Like GPT": Signs of language discrimination and resistance in computer science publishing
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