Podcasts

Associate Professor Marzyeh Ghassemi discusses why, despite its tremendous potential for good, AI must be approached with caution, especially in high risk areas like healthcare. Biases in training data can perpetuate real-world inequalities, providers might rely too much on potentially faulty AI, and tools created for one demographic might not necessarily translate to a different population. However, considering the incredible potential of AI to tackle challenges in transformative ways, it’s worth approaching these considerations with rigorous academic insight. 

This month’s podcast is a double feature. First up, Associate Professor and Chief Health AI Officer at the University of California San Diego Karandeep Singh explains the reality of using artificial intelligence for medicine. Professor Singh extrapolates on what works, what doesn’t, and how some challenges are social rather than technical.

Founding Director of the MIT Internet Policy Research Initiative CSAIL Senior Research Scientist Daniel Weitzner says a lack of visibility about how personal data is being used is leading to an erosion of customer trust. However, companies increasingly need to leverage data for analytic advantage, generative AI applications, and more. His research focuses on solutions which would empower consumers with visibility and control of their data, facilitating a future of accountability and trust.

Professor of Finance at the MIT Sloan School of Management and CSAIL Andrew Lo believes AI can help everyday consumers make important financial decisions by democratizing access to quality finance advice. His research aims to address the challenges of deploying AI in finance by, for example, answering questions around responsibility and engaging with financial advisors to make sure such tools are useful in the field.

Princeton Professor Arvind Narayanan, author of "AI Snake Oil," sheds light on the stark contrast between the public perception and actual capabilities of AI. In this podcast, he explores the significant gap between the excitement surrounding AI and its current limitations. Find a full transcript of this podcast here.