The Exchanges

Q Was there a moment where artificial intelligence and machine learning started to come onto the radar for you and made you think that it was worth studying in deeper depth?

A Well, pretty early, honestly, I mean, I definitely by high school, I was reading, uh, you know, the mind's eye and Douglas Hofstetter and, uh, Patrick Winston had a book on artificial intelligence, uh, And of course, if you read Isaac Asimov, it's, you know, iRobot goes back to the fifties and sixties when he was writing some of those stories. So that's been something that, like generations of people, I thought was important. Um, for me, I also just more broadly was looking at digital technologies. And a lot of my work in the nineties was about the internet and search costs and information goods, you know, things made out of bits versus out of atoms have very different properties. So trying to understand the economics of information, um, but always keeping an eye and doing occasional work on AI in particular. And then, uh, I think in the, you know, the early, around 20 10 or thereabouts, um, when a lot of people were worried about, uh, What was happening to wages and work and productivity. I started diving more closely and saw the role of, of AI. I took a ride in the Google self-driving car. I think it was 20 11 actually. We drove up Route one oh one up to San Francisco and turned around. And I was like, wow, this is, seems like it's almost ready for prime time. The highway was driving fine. Um, they, they had the human take it when we turned around, the cloverleaf to turn arou…

AI assessment note: “around 20 10 or thereabouts... I started diving more closely and saw the role”

Q And artificial intelligence doesn't seem to be threatening jobs. Now, maybe I'm making some assumptions here, but can you square those two ideas?

A Yeah, no, absolutely. And I, I, I love Andrew Yang. He's a super smart guy. I've had some good conversations with him and I'm very flattered that he, he cites our work in, in some of his campaign literature, et cetera. And I appreciate that. Um, but you know, we actually, in the book, we were not pushing for universal basic income and we did not Predict mass unemployment. Some people, uh, didn't read the book that carefully and maybe, you know, saw that we were talking about some big changes coming, but we always talked about what we call the great restructuring. The reality is, and not the great mass unemployment or great resignation even, um, the reality is, is that while AI is very powerful, human level, even superhuman in certain specific narrow tasks, we're still very far from artificial general intelligence, you know, AI that can do The broad set of things that humans can do. In fact, I, I did a study that was published in Science with, uh, Tom Mitchell of Carnegie Mellon University, where we looked at about 18,000 specific tasks that humans do in the, in the economy. Uh, O-Net actually publishes a list of 950 occupations, where each of them is about 20 or 30 tasks, so that's up to about 18,000 tasks. And, um, we evaluated them on a set of criteria as to whether Machine learning was likely to be able to do, and, you know, we call this the suitability for machine learning …

AI assessment note: “in not a single occupation... did we find that machine learning could run the table”

Q Do you think that the fear of artificial intelligence taking our jobs was overblown? Is overblown?

A Well, so let me nuance it. It's taking certain tasks. It's not leading to mass unemployment, but it is shifting the demand for different types of skills, and so there are places where there's less demand and there's more demand, and wages in some areas are depressed when, when a machine can do some of the jobs, especially some of the repetitive, rote kind of work, so middle skill, routine, information processing work, a lot of that has been depressed, and median wages have been stagnating in those areas. Um, So there's a effects on demand, but it's not like mass unemployment. It's more, uh, what's happening to wages and income and income inequality that have been the drivers. And, and I do think it's worth thinking about those and taking steps in terms of, uh, education, retraining, maybe, uh, income support, progressive taxation to help cushion that and help smooth the transition to new kinds of jobs. But it, you know, it's not the kind of thing where we like throw up our hands and say, well, There's nothing these people can do. Let's just give them a UBI.

AI assessment note: “It's taking certain tasks. It's not leading to mass unemployment, but it is shifting”

Q of capital and little labor, a lot of automation, very efficient factories. What the, what the, what is our, and our economy is like service or maybe it's entertainment. You ever think about like what the heck we're doing? I mean, what, where, what is our economy actually, if we can build everything we need, you know, with, with very little labor, what, what exactly are we all working for?

A I think that's exactly the question we should all be asking ourselves is, um, and, and, you know, policymakers, managers, economists like me, um, we can make GDP higher and higher. Um, we can reduce the labor content more and more, you know, therefore increasing productivity. Um, and if we're just making more, you know, flat screen TVs, you know, to what end? I'm, I'm not a philosopher, but one thing I would look to is Maslow's hierarchy of needs. You know, those of you know, there's some basic needs like food, safety, clothing, shelter, and then there's some intermediate leads, needs like, uh, relationships and status, and then there's self-actualization. And I, I think that's not a bad, uh, uh, template for how we should think about, um, progress. There's still a lot of people who don't have enough food, clothing, shelter, so let's take care of those needs I'm glad to see that, that, you know, absolute poverty has decreased tremendously over the past 30 years, actually even faster than the UN Development Goals called for. So, so, uh, hooray for technology, and I think, uh, uh, the way that we've made progress on that. Um, there's still a lot of work to be done, but in wealthier societies like ours, you know, we need to think about, okay, how are we gonna get meaning, and what do we wanna spend our time on? Do we wanna spend time, you know, On, on Facebook debating politics. U…

AI assessment note: “one thing I would look to is Maslow's hierarchy of needs.”

Q when I was writing my book, it seemed like it was the hottest thing in the world. Companies like UiPath are raising massive valuations, talking about giving, putting a robot at every desk, give it every employee, every employee their own robot. They're struggling pretty bad right now. Was the technology not there? Was the fact that Organizations can't implement it well enough. Not there. What happened in that situation?

A Well, just to make sure you're, you're listening to robotic process automation generally doesn't refer to like the kind of physical robots that we think of. It's referring to, um, you know, uh, information robots like that will automate filling out a form. And there's a huge amount of white collar work. That's like incredibly boring and routine. We talked about that where, you know, uh, insurance forms or medical forms, whatever all need to be filled out and processed. And the idea of robotic process automation was to automate a lot of that. And, um, you know, like I said, these dirty, these dull, boring jobs can be, um, can be automated and more power to them. I, I think that, uh, RPA was a bit, uh, overhyped, and so there's a bit of a bubble. There's definitely some value there, but in the end, it's, it's what I said earlier. It's, it's kind of focusing on taking what people are already doing, And automating that, um, often they'll literally, like, fill in forms that were made for humans, and so you just, it's like my cashier example. You're not really thinking broadly enough. What you probably want to do is have the information systems connect to each other at a much more fundamental level, not going through this form that was designed for humans, and, uh, and, and I think it's just not being creative enough about how, uh, Ah, data systems can communicate with each other. So…

AI assessment note: “I think that, uh, RPA was a bit, uh, overhyped, and so there's a bit of a bubble.”

Q there a darker side to all this? I was, uh, listening to Amazon's shareholder meeting last week, and it was striking to me that, uh, there were shareholder proposals coming through from workers who felt that they were being managed by robot managers who were tracking their time off task and, you know, assigning them goals and firing them in some cases. Is that the type of automation we want?

A It doesn't sound like it. You know, I'm not familiar with that particular set of, uh, of what they're doing with Amazon in that category. Um, but the broader point is, is spot on, which is that these technologies can be used to make the pie bigger, to create more shared prosperity, create more freedom and wellbeing, or the technologies can be used to concentrate wealth, to reduce freedom, Uh, to, uh, make people a lot, most people worse off. There's no, uh, law of economics that says that everyone's going to benefit from these technologies automatically. And I think it's really important for us to think about what our values are. What are we trying to achieve with these technologies? Our technologies today, as you said, the opening of the podcast are more powerful now than they've ever been. Um, and almost by definition, that means that our tools are able to change the world more than they ever have. Could before. So we have more agency. Our decisions make a big impact. Um, there's only so much somebody could do, you know, with a spear or a rock, you know, a thousand years ago. But today, you can literally, like, change the world in, in quite traumatic ways if, uh, if you use the technology. And that could be done in a way that, that makes the next 10 years the best decade we've ever had, or in a way that makes it one of the worst, or the worst. So I, I really put a lot more ag…

AI assessment note: “It doesn't sound like it. You know, I'm not familiar with that particular set”