Ethan Mollick | The Wharton School

**Jeremy Singer** (0:14)
I'm Jeremy Singer, President of the College Board, and this is The Education Equation. I spend my career grappling with what truly drives student success.
On this podcast, I'll talk with people who are researching, building and scaling solutions that matter. Every episode will go beyond the hype and focus on data and evidence to see what's actually working. Let's stop guessing and let's figure out what works. My guest today is Ethan Mollick, one of the leading voices helping us understand what AI actually means for how we learn and how we work. He's a professor at the University of Pennsylvania's Wharton School, where he studies how AI is reshaping everything from classrooms to careers. His book, Co-Intelligence, has quickly become a defining guide to engaging with AI, and his work has earned him recognition as one of Time's most influential people in artificial intelligence.
Ethan is not just observing this shift, he's actually testing it. Through his work with leading Generative AI Labs at Wharton, he's exploring how these tools actually perform in real classrooms and real work settings. He also writes One Useful Thing, one of the most widely read newsletters on AI today. And if you don't subscribe, you should. Ethan Mollick, welcome to The Education Equation.

**Ethan Mollick** (1:29)
Thanks for having me.

**Jeremy Singer** (1:30)
So first things first, how do I confirm you are actually Ethan Mollick and not just an AI bot that he has created?

**Ethan Mollick** (1:38)
So the good thing is I'm answering quickly enough and speaking quickly enough that I think we're okay. But it's getting harder to tell. I don't think that that is a thing you can promise that you can easily detect in the long term.

**Jeremy Singer** (1:49)
Okay, good. Because I planned a whole like biometric screening, but I will save our listeners time. It doesn't make great podcast content.
So I want us to warm up talking broadly about AI, not specific to education, but then we'll spend the majority of our conversation focused on education. You've been studying AI as I've noted very closely for a number of years. I've heard a lot of people try to analogize AI to past innovations whether it's the microchip or the Internet. But it feels at least to me that the pace of AI development, at least in the past couple of years, is just so much faster. So how has your thinking evolved as the technology has improved so rapidly?

**Ethan Mollick** (2:27)
So I think that a lot of us who follow the technology closely have had some sense of where this is going, or maybe not where it's going, but where it's going to go next, right? I don't think anyone knows where all of this is heading. I warned about the homework apocalypse back right after ChatGPT came out and it has unfortunately come to pass. What I actually find really interesting is that other people's thinking have finally evolved. I think this isn't a one-person problem, it's a many-person problem.
But I think as the capabilities of these systems keep growing, and we don't see sign of that slowdown that was always possible, we have to start preparing for a world where like, if it's good at math, it's going to be very good at math. If it's good at coding, it's going to be very good at coding in a pretty rapid order. And I think that the capacity to change quickly, to change perspectives, to react quickly, is becoming more important than ever.

**Jeremy Singer** (3:09)
Yeah, and I even saw, I think yesterday, I read your latest One Useful Thing newsletter, you sort of said, hey, the news releases, the pace is keep moving very quickly, which in some ways is a relief. But is there any belief that you had a couple years ago that has dramatically changed, or has it been pretty consistent? You deserve some credit, because I think you were onto this very early, and generally right, which is a big reason we have you here today. But is there anything that has shifted, that you've been surprised by?

**Ethan Mollick** (3:33)
This is going to sound very Pollyannaish, but I think a lot of the big negative effects that people were, I thought deep fakes would have a bigger impact than they did right now. I don't know if that's just our information environment so bad already. Also, I think I had a little bit of a too positive feeling that education would adjust more quickly, not systemically, but at the individual level around the idea that, okay, we've lost the category of assignments that are useful. There's a new form of work that is useful, that wasn't useful before. I think the level of delay and the level of denial that the tools are as good as they are also has been surprising to me. On the positive side, I think that the negative effects in some areas have been less than I thought. In the others, I thought some of the people would be reacting. I'm surprised. In the education section, very diverse responses, but there's still a debate over whether AI is real or not, which is a frustrating one, I think.