Ethan Mollick

Things Ethan Says on Podcasts

I am a professor at the Wharton School of the University of Pennsylvania. I study entrepreneurship & innovation and AI. I am trying to understand what our new AI-haunted era means for work and education.

Where to Find Them

Ethan Mollick writes One Useful Thing (Ethan Mollick) , writes Beyond The Prompt - How to use AI in your company , writes Coaching for Leaders , writes Your Undivided Attention , writes Think Like A Game Designer , writes Tự Học Cùng AI and writes Why Is This Happening? The Chris Hayes Podcast . They have also been a guest on HBR IdeaCast (3 times) , Plain English with Derek Thompson (2 times) , Motley Fool Hidden Gems Investing (2 times) , Harvard Business Review (2 times) , The Lawfare Podcast , The Prof G Pod with Scott Galloway , This Week in Business , Pioneers of AI , The Lawfare Podcast: Patreon Edition , Economist Podcasts , Into the Impossible With Brian Keating , The Ezra Klein Show , Night Science , Hidden Brain , Hard Fork (NYT) , Worklife with Molly Graham , Boss Class from The Economist , Future of HR , WorkLab , Scaling Laws , Possible , The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch , FranklinCovey On Leadership , Hello Monday with Jessi Hempel , Big Technology , The Education Equation with Jeremy Singer , Super Data Science: ML & AI Podcast with Jon Krohn and A Bit of Optimism .

Recently: “Wharton AI Researcher: If AI Froze Today, It Would Still Rewrite Work” on Into the Impossible With Brian Keating (October 2026); “AI Is Smarter Than Ever. So Where’s the Revolution?” on Plain English with Derek Thompson (October 2026); “How AI Is Changing Strategy—and 4 Skills Leaders Need Next” on Harvard Business Review (October 2026); “How AI Is Changing Strategy: Rethinking What Your Business Is Designed to Do” on HBR IdeaCast (October 2026); “The Dot and the Swarm” on One Useful Thing (Ethan Mollick) (October 2026); “The Overhang” on One Useful Thing (Ethan Mollick) (September 2026).

What They Said

“I will always do AI as a second pass, never as a first pass. It's actually interesting. I study innovation and brainstorming was invented in 1955. And by 1957, we knew it was a terrible idea because the problem is as soon as you do any group process, your ideas fit the group. So you always want to start working on your own before anything else. … If the AI writes, it will write a seductive, wonderful section that I will not be able to get out of my head and will influence my writing.” — Ethan Mollick, Into the Impossible With Brian Keating

Mollick, a Wharton professor who studies AI and work, explains why he writes first drafts and peer reviews himself before consulting AI. He does use the models afterward, for example to fact-check his books, which turned up errors in his own work and in work he cited.

Into the Impossible With Brian Keating · 2026-10-20 Permalink → Listen →
Into the Impossible With Brian Keating Around 38:05 into the episode
Ethan Mollick

And I remove phrases. The things I say every time my kids say to me, you sound like, you know, I think Claude was based on you because we have a similar kind of speak. Like, so like, that's a problem for me. But like, yes, that's part of my reaction is to show you. I view that.

Brian Keating

Sorry. Again, it's sorry to interrupt. I view that like saying to me, you know, Keating, you dye your hair, you know, stop dyeing your hair. But I view that as a compliment. Oh, you sound like Claude. Well, I wrote it myself. So Claude sounds like me or sounds like Ethan.

Ethan Mollick

…second pass, never as a first pass. It's actually interesting. I study innovation and brainstorming was invented in 1955. And by 1957, we knew it was a terrible idea because the problem is as soon as you do any group process, your ideas fit the group, right? So you always want to start working on your own before anything else. Adam's written about this as well. I feel the same way about writing. If the AI writes, it will write a seductive, wonderful section that I will not be able to get out of my head and will influence my writing. So I have to write my own replies first to things, right? And for reviews, I have to do my own review. Then the question becomes in the bigger question of science, okay, the AI's going to follow. I mean, one of the, so it was funny. I fact-checked coexistence with AI and it was great. There was no errors, but it also not only found errors in my work, but it found an error in the work I was…

Brian Keating

I mean, the dirty secret of publishing is that, you know, 90% of the time, at least, you know, previously, we're emailing docx files across the country to our agents and our

Speaker 3

editors. And I don't know, you know, I'm writing my fifth book now and I don't even talk to my editor half the time. I just put into Claude Fable to turn it up and say, well, I say it has guardrails. It can't write anything for me. It can tell me what I need to dictate or to type out or write.…

Brian Keating

you used a typewriter probably when you were a kid. I certainly did. I'm a little older than you, I think. And the keys were set on the QWERTY keyboard such that they wouldn't interfere with each other because the word frequency was set such that it was less efficient to type with than Dvorak…

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“The AIs are trained to use English in this kind of case because it lets us have some observability into what they're thinking rather than non-English. It's not a lucky thing. It is an actual design decision that the AI labs are under pressure to relax, because the AIs will be much more efficient if they didn't use English.” — Ethan Mollick, Into the Impossible With Brian Keating

Brian Keating suggested we are simply lucky that AI models happen to think in English. Mollick replies that when agents talk to each other they drift toward a compressed machine language, and that keeping them in readable English is a deliberate trade-off between being able to watch them and making them efficient.

Into the Impossible With Brian Keating · 2026-10-20 Permalink → Listen →
Into the Impossible With Brian Keating Around 20:01 into the episode
Ethan Mollick

…we created a model of the world because human language models the world. Otherwise, how could we describe quantum physics unless we could describe it with like? Language. And I find that a somewhat satisfying answer, but it's still hard to answer the questions about consciousness or anything else.

Brian Keating

…Hawaiian, which has 13 letters, and there's Cyrillic, which has 32 letters, and there's English. Not all languages are the same. There's binary code. And there may be languages that these entities can communicate in that we don't understand. And we are just lucky for now that they use English.

Ethan Mollick

That's actually a big worry of AI Researcher: because if you've ever used, especially Claude Fable 5 has gotten better at this. If you've ever watched it talk to other AI agents, it talks in a language called Claudish, which is a variation of what's called Neuralese, which is, yes, of course, the AIs will come with a better language for talking to other AI agents. And a huge amount of effort in fighting inside the labs is that's more efficient, but we lose observability. We can't see what the AI is doing. So the AIs are trained to use English in this kind of case because it lets us have some observability into what they're thinking rather than non-English. It's not a lucky thing. It is an actual design decision that the labs are under pressure. The AI labs are under pressure to relax because the AIs will be much more efficient if they didn't use English.

Speaker 3

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Brian Keating

With the scaling laws that you mentioned, the only pushback I have is that they're just empirical. You know, they're phenomenological. They're not immutable laws of nature like F equals MA. So again, what observation would convince you that scaling is going to hit some fundamental limit? I mean…

Ethan Mollick

It's so great because you always give two questions in each question. So I'll try and pull those apart. Question one is about scaling, saturated. Scaling's already saturated multiple times. There's multiple scaling laws. I talk about a couple of them in the book, but the truth is we keep hitting…

Speaker names from our own diarization · position estimated from where the line sits in the episode

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