Distribution-Free Inference for AI-in-Use: Addressing Multiplicity, Selectivity, and Adaptivity
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This project develops mathematical tools for assessing when artificial intelligence systems can be trusted after their predictions are used to make decisions. Modern AI tools help rank drug candidates, support medical decisions, screen large data sets, and suggest scientific hypotheses. In these settings, predictions are often used selectively and…
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