Subvolts take AI's productivity claims are myths; focus on human augmentation, not just automation. Feb 23, 2026 - Developers
- Learn how to build AI that complements human skills, not just replaces them.
- Business
- Understand the economic arguments against AI-driven automation and for human augmentation.
Features a Nobel Prize-winning economist offering a critical, research-backed perspective on AI's societal and economic implications.
AI Is Not Improving Productivity: Nobel Laureate Daron Acemoglu
Audio streams from MIT Sloan Management Review. Your place is remembered on this device.
From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Nobel laureate Daron Acemoglu challenges AI's productivity claims on Me, Myself, and AI. He argues technology's path is not fixed and current incentives favor automation over worker augmentation. Acemoglu advocates for AI development that complements human skills, warning against increased inequality and automation. The discussion covers productivity myths, reliability, and steering AI for social good.
This episode questions if AI truly makes us more productive. Economist Daron Acemoglu explains that we choose how AI develops, and current trends might increase inequality by automating jobs instead of helping workers.
This episode offers a critical perspective on AI's impact, challenging common assumptions about productivity gains. It is for business leaders, policymakers, and anyone concerned about AI's societal effects. Acemoglu's arguments about steering AI toward social good and complementing human skills are highly relevant to current debates surrounding AI regulation and development strategies at frontier labs.
- HostSam Ransbotham
- HostShervin Khodabandeh
- GuestDaron AcemogluGuest, MIT
- Guest: Daron Acemoglu
- Title: AI Is Not Improving Productivity: Nobel Laureate Daron Acemoglu
- Show: Me, Myself, and AI
- Length: 33 minutes
- Guest Affiliation: MIT
- Book Mentioned: Power and Progress
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.
- automation
- Daron Acemoglu
- using machines or computers to do jobs previously done by people
22 minConnecting Data at Scale With AI: Dropbox's Ali Dasdan
WithAli Dasdan
28 minAI for Process, People for Heart: GoFundMe’s Tim Cadogan
WithTim Cadogan
27 minAI Goes Grocery Shopping: Instacart’s David McIntosh
WithDavid McIntosh
40 minCreating Shared Prosperity With AI: Stanford Digital Economy Lab’s Erik Brynjolfsson
WithErik Brynjolfsson
Questions people ask
- What is Daron Acemoglu's main argument about AI?
- Acemoglu argues that technology, including AI, does not have a fixed destiny. Current choices determine whether AI boosts workers or accelerates automation and inequality.
- How should AI be developed according to Acemoglu?
- He advocates for focusing on new tasks that complement human skills rather than replacing them, warning that current incentives push AI toward automation by default.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to MIT Sloan Management Review.