Bonus Episode: Lessons From Jobs in the Age of AI

**Sam Ransbotham** (0:02)
Hi, listeners. I'm here with Tim DeStefano, Associate Professor of Research at the Georgetown University, McDonough School of Business. We're here at the World Bank Georgetown event, Jobs in the Age of AI, which is part of a series on AI in Action that Tim, along with John Timmis, had put together. Tim, can you give our listeners a brief overview of the event and how it came to be?

**Timothy DeStefano** (0:26)
Absolutely, Sam.
John and I initially put this AI in Action conference series together with the objective of creating a forum where industry experts, policymakers, and academics, the key leaders of AI, to come together and to share knowledge about policy and artificial intelligence. The purpose of today's conference is to provide real-time information on the extent to which artificial intelligence is going to affect existing jobs as well as jobs in the future. The way in which the conference is organized is that we'll start with academics who are going to share real-time data in academic research on the extent to which artificial intelligence is beginning to affect jobs, and then we'll follow up with industry experts that will share examples of how AI is actually being implemented within the firms and how it's beginning to affect employment.

**Sam Ransbotham** (1:15)
Sounds great. So we've got two speakers from the event who are going to join us for our podcast episode today, so let's get started with the first one.
Our first guest is Carl Frey. He's from the University of Oxford, and the keynote speaker at the Jobs in the Age of Artificial Intelligence event at Georgetown and the World Bank. Picking up on his keynote, I just thought I'd ask a few questions. So first, you have a very influential paper about how skills and jobs are going to change in our coming future. And at the time, you were thinking it was creativity, social intelligence, and perception were going to be the big key trends in the future. What's changed about your thinking?

**Carl Benedikt Frey** (1:59)
Back in 2013, as you mentioned, we outlined the three key bottlenecks to automation. And one of them was complex social interactions. And the state-of-the-art chatbots at the time are quite well exemplified by Eugene Ghostman, which was a chatbot that essentially tried to mimic human capabilities, but essentially pretended to be a 13-year-old Russian boy speaking English as his second language. And essentially that way, fooling a lot of people in these low-brow price competitions that it was actually a person. And the chatbots that we have today are obviously much more capable, right? So there's no question that in the virtual space, at least, we've seen a lot of progress when it comes to automation. But I think what's very likely is that, as we see these technologies improve, it's going to increase the value of in-person communication. So think of it this way. If AI writes your love letters in everybody else's, the first date becomes more important. As a company, if everybody is selling their product using AI, how do you distinguish yourself in such a marketplace? Well, it's going to be through in-person communication. So I think that bottleneck still holds at least in part. The second bottleneck has to do with creativity. And obviously, creativity is hard because we struggle to define it in the first place. But it essentially has something to do with coming up with novel ideas and artifact that somehow makes sense, that has some commercial or symbolic value.
I think it's still the case that when it comes to frontier capabilities, we are still quite far off from automating those away when it comes to creativity.

**Sam Ransbotham** (3:55)
So even if we have Cyrano de Bergerac writing our love letters for us, an automated AI version of that, there's still the first date is important. There's still that. What you're speaking to is the idea that some things have become scarce and some things have become not scarce.

**Carl Benedikt Frey** (4:10)
Exactly.

**Sam Ransbotham** (4:10)
And that's changing on us. What's going to be scarce coming up?

**Carl Benedikt Frey** (4:14)
Well, I do think that everything that is in person is more likely to become scarce to begin with, for example. And I do think that these algerates are very good at rehashing existing concepts, and to some degree are also prediction. But a lot of the things that we do are more than just extrapolating from past patterns, right? So if you would have trained an algorithm in 1900 to predict is human flight likely to be possible, you would have essentially had an algorithm planning through a lot of failed experiments. You might have to have looked to data on birds, which was what suggested that it's possible to fly in the first instance. But even if you look at that data, you would have found that birds that weigh more than 50 pounds tend not to fly, and below that they just rise with a lot of difficulty.