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Explore a 20-minute conference talk from the FAccT 2021 virtual event that introduces a statistical test for probabilistic fairness. Delve into the research presented by B. Taskesen, J. Blanchet, D. Kuhn, and V. Nguyen, which addresses the critical issue of fairness in machine learning algorithms. Learn about their innovative approach to detecting and quantifying bias in probabilistic classifiers, and gain insights into how this test can be applied to improve fairness in various AI applications. Understand the implications of this research for developing more equitable and just machine learning systems across different domains.
