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Explore discrimination testing methodologies for generative AI systems in this 12-minute conference talk from the Association for Computing Machinery. Learn from researchers at Columbia University and New York University as they present frameworks for evaluating bias and discrimination in AI-generated content. Examine current evaluation practices and policy implications for auditing generative AI systems, with particular focus on developing effective testing approaches that can identify discriminatory outputs. Discover how legal and technical perspectives intersect in the development of robust evaluation methodologies for ensuring fairness in generative AI applications.
