The AI End Game: How Work is Changing with Ethan Mollick

**Ethan Mollick** (0:00)
There's a lot of people who really just think AI is going to go away. There's something here that this isn't real, the systems aren't as good as you say they are, they make mistakes. This is real. I talk to CEOs all the time, they are getting value out of it. It's funny because they'll say things like 10 million, 20 million here, nothing significant yet, but they're getting value out of these systems. There has not been major layoffs because of AI yet. I don't think that continues infinitely.

**Chris Hayes** (0:21)
No.

**Ethan Mollick** (0:22)
Maybe people get better jobs, but we need the systems in place to cushion it, which means we believe this is real.

**Chris Hayes** (0:33)
Hello and welcome, Why Is This Happening with me, your host Chris Hayes.
Well, we're here for another special edition of our AI series WITHpod, The AI End Game. And today, I want to sort of focus on neither the best case scenario nor the worst case scenario, but a trajectory in which these things really are incredibly powerful and transformational, in which the kind of more maximalist claims of its backers basically come true, short of the end all human life on the planet, which we can sort of put in another category. But what does it look like if the people saying, this technology is completely revolutionary on a scale, maybe even more revolutionary in the Internet, maybe the most revolutionary form of automation that's ever happened? What exactly does that mean if that's true? My guest today is a professor at Wharton, Ethan Mollick. He's been studying AI and its implications for education, entrepreneurship, work. He's author of numerous books including a 2024 New York Times bestseller called Co-Intelligence, Living and Working with AI.
He has a new book coming out in the fall called Coexistence about working with AIs that are as he says, sometimes smarter than you. He also writes a sub stack called One Useful Thing. Professor, it's great to have you in the program.

**Ethan Mollick** (1:48)
Great to be here. Thank you.

**Chris Hayes** (1:56)
So, how long have you been working with and working on AI?

**Ethan Mollick** (2:00)
So, I mean, that's always a hard question because AI is many different things. When I was in graduate school at MIT, I did work at the MIT Media Lab with the AI group at that point, some of the fathers of AI. They're from the original days of the 1950s. And I was the non-technical person, so I was like the business person translating stuff. And then I've used AI a lot for teaching and educational purposes. And certainly since the large language models came out, I've been talking a lot about them and how they impact work and education and everything else.

**Chris Hayes** (2:25)
So where are you on the kind of scale of 1 to 10, of 1 being it's a complete con or a bubble that's going to completely fail, and 10 being it will change the world unlike any other technology we've ever had?

**Ethan Mollick** (2:41)
So, I mean, one thing I'll just try and be careful about without being boring is that there is a little bit of like changing the world is absolutely definite in a huge way. So maybe eight or nine in the longer term. But that this is not an instantaneous process, right? There is a process of adapting to technology and that change takes place over time, not instantly.

**Chris Hayes** (3:01)
You know, one of the examples I think we've had is, even if you just talk about the internet or you talk about other forms of digital revolutions, there used to be a joke about the paperless office. I remember being made in the 1990s where you were still printing out a ton of stuff and people were like talking about like joking about the paperless office as you like went to the printer and printed out 90 pages.
And it was because there was a huge gap between what the frontier prediction was for what wired networking computing would do to say a workplace and what actually happened in real time. Now in the year 2026, there's really not a lot of printing happening. Like every time you have to use a printer is really a bummer in your life. It turned out that prediction was true. It just took like two decades longer than some people thought. Do you think that's something similar happening here?

**Ethan Mollick** (3:54)
So I think it is, right? I mean, there's sort of this weird needle to thread because a lot of, especially online discussion is either zero or one. Like either this is all fake, which it just clearly is not, or the machine god is coming next week, right? And I mean, can't 100% rule that out, but that's the most likely scenario is some aspects of it look like other technologies. And if you work at any organization, you've probably seen this, right? No company transformed radically as a result of AI in 2025, because to do that, let's say your programmers are 100 times more productive. So how are they getting instructions about what to build? Who's testing this? Who's shipping that product? How are you evaluating their work? What are they supposed to do with their time? Even if they're using the product, there's a whole bunch of other systems that have to be connected together to make AI work. So we call this diffusion of technology in the academic world. And it's just a constant. All technologies take some effort, some time to diffuse, so nothing happens instantly. That said, diffusions happen very quickly here, but nothing is instantaneous.