AI Is Not Improving Productivity: Nobel Laureate Daron Acemoglu

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Hi, everyone. We're back with a bonus episode, profiling another thought leader in the technology research space. MIT Institute Professor Daron Acemoglu is a Nobel Prize winning economist and the author of Power of Progress. He joined Sam today for a conversation spanning technological advancements, limitations, and regulation. We're back on March 10th with more new episodes. For now, we hope you enjoy this conversation.

**Daron Acemoglu** (1:07)
I am Daron Acemoglu, Institute Professor at MIT, and you are listening to Me, Myself, and AI.

**Sam Ransbotham** (1:14)
Welcome to Me, Myself, and AI, a podcast from MIT Sloan Management Review, exploring the future of artificial intelligence. I'm Sam Ransbotham, Professor of Analytics at Boston College. I've been researching data, analytics, and AI at MIT SMR since 2014 with research articles, annual industry reports, case studies, and now 12 seasons of podcast episodes. On each episode, corporate leaders, cutting-edge researchers, and AI policymakers join us to break down what separates AI hype from AI success. Hi, listeners. Thanks again to everyone for joining us. I'm excited to be talking with Daron Acemoglu, Professor of Economics at MIT. Daron works extensively on economic development, labor economics, and the economics of technology. In 2024, he was awarded the Nobel Prize in Economics for this work. His insights on the interplay between institutions, technology change, and inequality are particularly relevant for today's businesses. Of course, our listeners will be most interested in Daron's thoughts on AI. Daron, great to have you on the podcast.

**Daron Acemoglu** (2:26)
My pleasure. Thanks, Sam.

**Sam Ransbotham** (2:28)
Okay. So your work spans institutions, technology, and inequality. Can you share some of the themes in general from your past research?

**Daron Acemoglu** (2:36)
I got into economics because I was fascinated by what I saw around me in my very young teen years about very divergent economic, political, and social outcomes across countries, huge disparities in terms of wealth, in terms of poverty.
Those interests have framed my research and my focus on institutional factors, which determine the effects of history, the effects of how society is organized, the rules, the laws, the norms, and technology as the prime channel via which human ingenuity and human decisions impact economic productivity and economic well-being. Throughout, I have been fascinated by the interplay between institutions and technology and by how institutional factors and technological factors have evolved over time. A lot of my research has focused on, for example, why there has been a huge divergence in economic fortunes of different parts of the world since the 16th century or thereabouts. It is very much related to, for example, the fact that European powers colonized the rest of the world and shaped the institutional trajectories of very different nations around the world in very diverse ways. And I've also been fascinated by the industrial revolution and how we started this process of using knowledge, science, and various skills in improving the way that we can actually start producing goods and services.

**Sam Ransbotham** (4:21)
That's all really salient for what's going on right now. You have a recent book, Power and Progress, and I think I was reading the preface of a revised edition, perhaps, where you noted that things sort of changed on you underfoot. How has the recent changes changed some of your thinking?

**Daron Acemoglu** (4:37)
Well, I think two things are worth noting there. The main thesis of Power and Progress is that technology does, to some extent, what we want it to do. It does not have a preordained destiny that will take us in one direction or another. We have a lot of agency, a lot of choice in shaping the future of technology. And different futures correspond to different winners and losers, different benefits, different costs, different productivities.
We try to make that point by going into history, showing how critical periods during our recent history, like the last 1,000 years, have led to sometimes big technological breakthroughs, but with huge losers. And sometimes those forces have been reversed and gains from technological betterment have been shared more equitably. So that message, I think, is more relevant today than ever. AI is a particularly versatile technology. It provides so many different futures for us. And the narrative that there is a determined natural future of AI, and we are all going there whether we want it or not. And ultimately, we're all going to become incredibly more prosperous out of that is just simplistic. And fighting against that narrative, I think, is very important today because that narrative lulls us into a sense of helplessness and sense of complacence that could be quite costly. On the other hand, of course, in 2021, 2022, when we were writing, it was impossible to foresee how rapid some of the advances in generative AI would be. But those advances haven't really changed the basic trade-offs and the basic messages that we wanted to convey in the book. I talked at the high level about different directions of AI. What are they? I think simplifying it, you have a couple of poles that are pulling in different directions. I would single out in the production process automation, which is the dream of most AI models today, especially under the banner of artificial general intelligence, AGI, which aims for large language models or other generative AI tools to reach levels of capabilities comparable to the best workers across a very wide range of domains. The reason why that is viewed as attractive is that just like previous rounds of software that improved cognition in different domains that can then be used for automating tasks. So AGI is very tightly interwoven with the automation agenda. Automation is great. It gets rid of some routine tasks. It can do some boring tasks when it's applied in the physical domain such as with cranes or robots. It could remove the most dangerous tasks from the human work schedule. But automation also doesn't benefit workers by itself. It takes away tasks from workers. It is beneficial to capital and capital owners and not so much for workers in general. So at the other pole, we have things that are complementary to humans, meaning that technology enables humans to do more things or better things or completely new things. So then these new things is what I refer to as new tasks. So if you look at people around you, many of the occupations you'll see involve things that could not even be imagined 50 or 60 years ago. As a journalist, you're going to be making videocasts and podcasts and use technologies for research that require completely different skills than somebody 60 years ago going to the library and sifting through books. So those are some aspects of new tasks. So are many of the physical occupations in manufacturing that involve much more technical work. Those have generally been very good for productivity and for worker wages and employment. So that's one dimension in which the future of technology could have very different effects depending on whether we go on the automation or the new task direction.