AI Is Not Improving Productivity: Nobel Laureate Daron Acemoglu

AI Is Not Improving Productivity: Nobel Laureate Daron Acemoglu

Author: MIT Sloan Management Review February 24, 2026 Duration: 32:59
In this bonus episode, Nobel Prize-winning economist Daron Acemoglu joins Sam to challenge some of the most common assumptions about artificial intelligence’s future. Drawing on his book Power and Progress, Daron argues that technology doesn’t have a fixed destiny — and that today’s choices will determine whether AI boosts workers or simply accelerates automation and inequality. He makes a case for focusing on new tasks that complement human skills, rather than replacing them, and warns that current incentives push AI toward centralization and automation by default. The conversation tackles productivity myths, reliability risks, and why regulation should proactively steer AI toward social good. Read the episode transcript here. Guest bio: Daron Acemoglu is an institute professor at MIT, faculty codirector of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work, and a research affiliate at MIT’s newly established Blueprint Labs. He is an elected fellow of the National Academy of Sciences, American Philosophical Society, the British Academy of Sciences, the Turkish Academy of Sciences, the American Academy of Arts and Sciences, the Econometric Society, the European Economic Association, and the Society of Labor Economists. He is also a member of the Group of Thirty. He has authored six books, including Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity with Simon Johnson. His work in economics has been recognized around the world, notably with the Nobel Prize in economic sciences, along with co-laureates Johnson and James A. Robinson, in 2024. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

Ever wondered how some organizations manage to turn artificial intelligence from a buzzword into a genuine engine for growth, while others struggle to move beyond the pilot phase? Me, Myself, and AI, a production from MIT Sloan Management Review, goes straight to the source to find out. Instead of theoretical discussions, this podcast features candid conversations with the people who are actually building and implementing AI systems at scale. You'll hear directly from leaders at prominent companies like YouTube, Cisco, and Hugging Face as they recount their journeys-not just the polished successes, but the real-world challenges, strategic decisions, and sometimes surprising lessons learned along the way. Each episode digs into the practicalities of creating measurable business value, cutting through the noise to reveal what effective AI leadership and integration truly look like. It’s a focused exploration for anyone in technology, business, or education who wants to understand the human and operational stories behind the algorithms. Tune in for an unvarnished look at the future being built, one practical application at a time.
Author: Language: English Episodes: 100

Me, Myself, and AI
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