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Explore the intersection of artificial intelligence, racial justice, and financial inclusion in this 39-minute conference talk from the Toronto Machine Learning Series. Delve into the challenges of combating discrimination in lending practices through machine learning algorithms. Learn about the limitations of current group fairness approaches and discover innovative solutions like Distributionally Robust Fairness (DRF) and the SenSR training algorithm. Gain insights into how these cutting-edge methods aim to address subgroup discrimination and promote fair lending practices for African Americans and other marginalized communities. Understand the potential impact of these AI fairness techniques on reducing financial exclusion and predatory lending, while considering their real-world applications and validation.
