Approaches to Fairness in Machine Learning with Richard Zemel

Banner Image: Richard Zemel - Podcast Interview

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About this Episode

Today we continue our exploration of Trust in AI with this interview with Richard Zemel, Professor in the department of Computer Science at the University of Toronto and Research Director at Vector Institute.

In our conversation, Rich describes some of his work on fairness in machine learning algorithms, including how he defines both group and individual fairness and his group's recent NeurIPS poster, "Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer."

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Thanks to our sponsor Georgian Partners

Georgian Partners is a thesis-driven growth equity firm investing in business software companies leveraging applied artificial intelligence, trust and conversational AI. Based in North America and founded by successful entrepreneurs and technology executives, Georgian Partners leverages its global software expertise to be able to directly impact the success of companies.
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