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David Autor
Professor of Economics, MIT
Sharut Gupta
PhD Student, MIT CSAIL

MIT Economics Professor David Autor says that AI is “not like a calculator where you just punch in the numbers and get the right answer. It's much harder to figure out how to be effective with it.” Offering unique insights into the future of work in an AI-powered world, Professor Autor explains his biggest worries, the greatest upside scenarios, and how he believes we should be approaching AI as a tool.

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Professor, MIT CSAIL

Have we achieved Artificial General Intelligence? MIT CSAIL Professor Manolis Kellis argues yes. Computers can do nearly every intellectual task that humans are capable of and are rapidly tackling the physical tasks. What does this mean for the future of AI integration, regulation, and development? Hear Professor Kellis’ ideas about how businesses can incorporate LLMs (large language models) to minimize silos, why we shouldn’t put up too many guardrails on AI technology, and how human-AI collaboration can lead to broader societal benefit, including healthcare.

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Marzyeh Ghassemi
Associate Professor, MIT EECS/IMES

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. 

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Andreea Bobu
Assistant Professor, MIT CSAIL
Karandeep Singh
Jacobs Chancellor’s Endowed Chair and Chief Health AI Officer at UC San Diego Health, Associate Professor, UC San Diego

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.

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Daniel Weitzner
Faculty Co-Director, MIT Future of Data, Trust, and Privacy, Director, MIT Internet Policy Research Initiative (IPRI), Senior Research Scientist, MIT CSAIL

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.