Wharton AI Researcher: If AI Froze Today, It Would Still Rewrite Work

Forecasters gave AI under 2% odds of helping solve a millennium-level math problem by September 2026. It happened. Ethan Mollick has been measuring what AI actually does to real work with field experiments, not forecasts, and his answer is not what most people expect. Subscribe if you want science with evidence, not speculation.

Mollick runs the Generative AI Lab at Wharton. He is the author of Co-Intelligence and Coexistence, his new book on navigating a world where AI tools are already good enough to change almost all intellectual work, even if progress stopped today.

The conversation covers the jagged frontier: why AI solved a math olympiad before it could count the Rs in strawberry, what it means that roles blur when everyone on a team starts using AI, and what four human advantages still hold an edge when a model can already write a publishable paper. It also covers what happens when your kids tell you that you sound like Claude.

What you’ll hear:

What centaur, cyborg, and conjurer work actually look like in a real academic lab

Why brainstorming was considered a bad idea shortly after it was invented and what that means for working with AI

Why Mollick reduced em dashes in his new book and what that tells you about living alongside these models

What co-evolution might look like if the escalator keeps moving

“If we just had the models we have right now, that’s enough to change almost all of human work in the next ten years. It’s good enough.” — Ethan Mollick

CHAPTERS

00:00  AI writes good papers now. Taste is the weak spot.

03:14  The jagged frontier: math olympiad gold, but not the Rs in strawberry