Benjamin F. Jones | AI in Research & Development

Summary

Benjamin F. Jones, the Gordon and Llura Gund Family professor of entrepreneurship at Kellogg School of Management, Northwestern University delivered a live presentation on AI in research and development (R&D) on April 15, 2026.

Professor Jones shared a framework for analyzing the impact of AI on R&D. He discussed how AI accelerates the “ideas production function” and how advances in machine intelligence can transform the productivity gain per unit of R&D investment.

Following his presentation, Professor Jones answered live and pre-submitted questions with our host moderator, Huiyu Li, co-head of EERN and research advisor at the Federal Reserve Bank of San Francisco.

This was a virtual event hosted by the EmergingTech Economic Research Network (EERN). You can view the full recording on this page.

Key Takeaways

How does creativity work and what are its limits?

“I find this metaphor of a hallway with doors on it very useful because you can think of what’s going on in a research process in R&D and innovation and coming up with new ideas. … You can look in a door with some effort and some cost and try to see if there’s something really important and new in that door. … Another way of thinking about creativity (is that it’s) fundamentally combinatoric. … What people are doing creatively is they’re making combinations. … The space that you can search combinatorically is basically infinite.”

Skip to 6:28 in the video for the full response.

How does AI enhance the creative process?

“While humans are experts, … searching locally around their own expertise and their creative insights, … (AI models) read everything. … They have a much broader set of ingredients, which they can combine. So, in that sense, an AI can seem especially creative. … If you think about the hallway, it’s like taking every door on that hallway, and putting a label on (them) … saying, there’s a material in here with interesting properties. That’s very exciting. It’s directing humans out of their narrow search and it’s doing it at very low cost.”

Skip to 14:09 in the video for the full response.

Will AI radically transform R&D?

“What I want to point out is that bottlenecks are a very, very strong phenomenon. …Let’s say that we had a productivity of one across all the research tasks … and then I took half of the research tasks and I made us infinitely productive at those. … When you take a harmonic average of one and infinity, the number you get is two. It’s a lot closer to one than infinity. … A way to think about this in R&D is maybe AI will be very good at conceptualization, it’ll give us lots of creative ideas to try, but still we have to do a lot of experimentation, and experimentation is going to be the bottleneck.”

Skip to 30:28 in the video for the full response.

Speaker’s Related Research