SYLVIE DOUGLIS, BYLINE: NPR.
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DARIAN WOODS, HOST:
Greg Rosalsky.
GREG ROSALSKY, BYLINE: Darian Woods.
WOODS: You write the Planet Money Newsletter. You've been writing a lot recently about artificial intelligence and whether or not it's too overhyped.
ROSALSKY: Yes, I have. But, you know, publishing this kind of stuff can be a little bit risky. Like, you know, if AI does end up transforming the economy, like, I don't want to be the guy who, like, once said, like, predictions like that were overblown.
WOODS: Yes, you do not. So on THE INDICATOR, we're going to do this two-parter. We're going to have one episode making the case for why AI won't have a massive effect on the economy and another for why it will.
ROSALSKY: And just so nobody confuses each episode with our own, you know, personal prognostications, we are going to decide who reports on which side with a coin flip.
WOODS: A digital coin flip. Let's get ChatGPT to decide.
ROSALSKY: What? I didn't even know we were going to do this.
WOODS: (Laughter).
ROSALSKY: This is freaky.
WOODS: So Greg, heads, you take AI is overrated. Tails, AI is underrated.
ROSALSKY: (Laughter).
WOODS: ChatGPT, can you please flip a heads or a tails randomly?
AI-GENERATED VOICE: Sure. It's heads.
WOODS: It's heads.
ROSALSKY: Whoa.
WOODS: Greg, you're going to look at whether AI is overhyped.
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WOODS: This is THE INDICATOR FROM PLANET MONEY. I'm Darian Woods.
ROSALSKY: And I'm Greg Rosalsky.
WOODS: Today on the show, I'm going to make the case for why AI, like chatbots and image generators, will have a huge effect on the wider economy.
ROSALSKY: And tomorrow, I'm going to argue the opposite.
WOODS: May the best human win.
ROSALSKY: (Laughter).
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WOODS: All right, Greg. I want to convince you that generative AI will have massive effects on the wider economy.
ROSALSKY: OK. I guess I'm all ears.
WOODS: I'll start with some examples of how existing products and services are being made more productively right now with AI. Paul Daugherty is the chief technology and information officer for Accenture, which is an IT consulting company.
PAUL DAUGHERTY: We've had $2 billion of generative AI sales just partway through our fiscal year.
WOODS: So in a gold rush, you are teaching the gold miners where to look for gold.
DAUGHERTY: (Laughter) We are - yeah, we're maybe providing some of the maps as to where to go, where do you find the value and how do you get there exactly.
ROSALSKY: OK. So AI is great for consultants, huh?
WOODS: Yeah. That is true. I understand your cynicism, Greg. But Paul gives a bucketload of real examples. Take this government agency in Europe for pensions and welfare.
DAUGHERTY: They received, you know, 20,000-plus emails and letters every day. They didn't have enough people to even read them all.
WOODS: So generative AI could analyze the letters. It summarized what they were about, and it flagged those that required more attention. And it eliminated a backlog of 8 million letters. It reduced how long people were waiting to hear back from that government agency.
DAUGHERTY: So six to eight weeks faster response time - big increase.
WOODS: That's a lot.
DAUGHERTY: This would have taken a 700% increase in their human staffing to do it if they had to do it with people.
WOODS: Also, there's the example of call centers.
ROSALSKY: Classic AI use case here.
WOODS: Yes. So one company used it to understand what the customer was inquiring about and find the right solution.
DAUGHERTY: The result, in this case, was over a 30% improvement in productivity, and there was over a 60% increase in the measure of customer satisfaction.
WOODS: Paul says generative AI is also helping businesses expand. So take the insurance industry.
DAUGHERTY: Insurance - you might not think of it as the most exciting, you know, new industry to adapt technology. But in this case, they are at the forefront of applying generative AI.
WOODS: So when you apply for insurance, the company has to assess your risk. And for certain types of insurance, that's a lot of work. So let's take business interruption insurance and other commercial insurance. Paul says many insurance companies only take in about 20% of new requests, and that's because they simply don't have enough qualified underwriters to assess all of the thousands of pages of documents.
DAUGHERTY: With generative AI, you can do that a lot more effectively. And, in fact, we're seeing them add new underwriters because they can now onboard people with this technology to help them become proficient much more quickly.
WOODS: And look, Greg, I admit these examples are not the sexiest.
ROSALSKY: Yeah. It's no AI-generated video of, like, an alligator in space.
WOODS: Yeah. Maybe that would convince you. But, you know, I would argue that this is the point. A lot of the boring, behind-the-scenes processes that make our economy tick are being quietly transformed in ways that'll make all of our lives better and easier.
ROSALSKY: Maybe. But, like, we're not talking, like, plumbing and electricity here.
WOODS: Bear with me, Greg. I've got more examples. So those were examples of how generative AI is helping existing products. There is a second category of how AI is reshaping the economy, which is completely new products. Like, there's this company called GameChanger, and it has this product where you add in the scores for your kids' Little League team. And then, using a type of AI, it spits out this newspaper-style article afterwards with a recap.
DAUGHERTY: Play-by-play coverage of your son or your daughter or the kids on the team - and, yeah, you could envision all sorts of creativity and fun with this. I think it shows, you know, the promise and potential that the technology will have.
WOODS: You know, the wider implication of thousands and thousands of companies doing little things like this all across the world could be pretty vast. Tyler Cowen is an economist and a friend of the show.
TYLER COWEN: We're already using them to find new materials in the laboratory, to find new antibiotics, to crack problems in biology.
WOODS: Tyler sees those examples of what we're already doing now, and he thinks there is real promise ahead.
COWEN: It's going to increase the pace of scientific advance. So 20, 30 years from now, we're going to have much higher living standards because of generative AI.
WOODS: Tyler says generative AI has gifted us a tool that we've never had before.
COWEN: What is really scarce in our world is intelligence. Material resources matter. But the way you get more of them or get them more cheaply is to somehow apply intelligence. Now, for, really, the very first time in human history, we've created a fairly general kind of intelligence that, for many tasks, is already smarter than we are. Think of it this way. Every person has at his or her disposal now a free research assistant, a free colleague and a free architect. That's not everything. It doesn't mean you have a free carpenter or free energy, but that's an awful lot. And just the number of projects that will stem from human ingenuity - I think it's going to astonish us.
WOODS: Tyler puts generative AI on par with one invention in Europe in the 1400s.
COWEN: I'm inclined to cite the printing press, which brought great benefits and a lot of knowledge and intelligence. It did make the world more chaotic in some negative ways. I think we need to work very hard to make sure we do better the next time around. But this seems to be a truly transformational breakthrough.
WOODS: You know, even if we're not seeing it exactly now, the way Tyler sees technology is that it takes time for it to diffuse through the economy.
COWEN: What we do now is we have processes already in place, and we tack the AI on top of those processes. And that can be a gain. But the real gain is much longer-run, when you reorganize how the whole thing is done.
WOODS: So to truly benefit the wider economy, all our processes, our norms and our businesses need to adjust. Like, just because we had the technology of video conferencing software didn't mean that many people were working remotely pre-2020. The norms needed to change.
COWEN: There's human bottlenecks, institutional bottlenecks, inertia, fear. So again, that's a 10- to 20-year project, even in cases where the quality of the AI is good enough.
WOODS: And Greg, I'm not sure if you're aware, but Tyler has been using generative AI in his own work. He wrote this book himself. It was called "GOAT: Who Is The Greatest Economist Of All Time And Why Does It Matter?" And it has this accompanying chatbot based on the book. Also, on his podcast, "Conversations With Tyler," he has this interview with the long-dead Irish writer Jonathan Swift. The answers were from ChatGPT, and a human voiced the answers.
I did enjoy the Jonathan Swift...
COWEN: Oh, yeah, yeah.
WOODS: ...Interview.
COWEN: He was very good.
WOODS: He was a good guest.
COWEN: Yeah. Better than many human guests.
WOODS: Not as good as you, though, Greg.
ROSALSKY: Wow. Was there some sarcasm in your voice there?
WOODS: Oh, no.
ROSALSKY: 'Cause...
WOODS: I'm saying there is the promise of AI, but we'll have things that can't do, like, you know, the warm, human touch of Greg Rosalsky.
ROSALSKY: (Laughter) OK. Well, for a nice and warm human touch and a counterpoint to Darian's episode here, stay tuned tomorrow for the case for why AI is overrated.
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WOODS: This episode was produced by Corey Bridges with engineering by Valentina Rodríguez Sánchez. It was fact-checked by Sierra Juarez. Paddy Hirsch edited the episode, and Kate Concannon edits the show. THE INDICATOR is a production of NPR.
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