Aylin Caliskan

Aylin Caliskan, a Princeton researcher and co-author of a groundbreaking paper on AI bias, discusses the alarming ways AI can inherit societal prejudices. She unpacks how AI language models reflect racism and sexism, highlighting findings from the Implicit Association Test. Caliskan explains the consequences of biased AI in recruitment processes, leading to unfair treatment of candidates. She advocates for increased human oversight to mitigate these biases, emphasizing both the challenges and the potential for AI to help reveal and address unconscious prejudices.

Algorithms now determine how much things cost. It’s called dynamic pricing and it adjusts according to current market conditions in order to increase profits. The rise of ecommerce has propelled pricing algorithms into an everyday occurrence—whether you’re shopping on Amazon, booking a flight, hotel or ordering an Uber. We Meet:  Lisa Wilkins, UX designer  Gabe Smith, chief evangelist, Pricefx Aylin Caliskan, assistant professor, University of Washington Joseph Harrington, professor of business, economics and public policy, University of Pennsylvania Maxime Cohen, Scale AI Chair professor, McGill University  Credits: This episode was reported by Anthony Green and produced by Jennifer Strong and Emma Cillekens. We’re edited by Mat Honan and our mix engineer is Garret Lang, with sound design and music by Jacob Gorski.