Data for Equality
The discussion highlights the importance of using data to address historical disparities in various fields, particularly in healthcare. Orly emphasizes the need to move beyond traditional comparisons of AI and human performance, advocating for broader access to technology to enhance inclusion. She also addresses the challenges of historical biases in data, proposing innovative alternatives to ensure fairness in automated systems, such as hiring and judicial processes.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
636: The Equality Machine — with Orly Lobel
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