Sendhil Mullainathan: AI and Algorithmic Bias

As AI continues to permeate various aspects of society, its impact on decision-making, bias, and future technological developments is complex. How can we navigate the challenges posed by AI, particularly when it comes to fairness and bias in algorithms? What insights can be drawn from the intersection of economics, computer science, and behavioral studies to guide the responsible development and use of AI?In this episode, Sendhil Mullainathan, a prominent economist and professor, delves into these pressing issues. He shares his journey from computer science to behavioral economics and discusses the role of AI in shaping the future of decision-making and societal structures. Sendhil provides a nuanced view of algorithmic bias, its origins, and the challenges in mitigating it. He also explores the potential and pitfalls of AI in healthcare and policymaking, offering insights into how we can harness AI for the greater good while being mindful of its limitations.0:00 - Start1:51 - Introducing Sendhil14:20 - Algorithmic bias29:20 - Handling Bias41:57 - AI and Decision Making57:01 - AI in our Future1:02:29 - Conclusion and the last question

Om Podcasten

Artificial General Intelligence — the type of AI that reaches or even surpasses human capabilities — is an exciting topic. But what is not explored as much is an equally important question: what happens before AGI is here? That is, what should we be doing to prepare? In Before AGI, I hope to have honest conversations about what are the goals, what are the problems, and what lies ahead as we develop AI.