00:00You have a new report that you put out today. Walk us through this about this AI apocalypse
00:04potentially for millions of workers. And you ask, you pose that as a question.
00:08And you're saying the reality potentially, but maybe we're just not there just yet.
00:14So great to be here, Jess. So the big question, there's so many big questions about AI.
00:21One big question is, what does this mean for the economy? Is this going to be a boom
00:27for worker productivity and wages? Is it going to make us all smarter, all better at our jobs,
00:33all more valuable to our employees? Or is this going to be something more like factory automation,
00:40which put a bunch of blue collar workers out of a job in the 80s, 90s and 2000s? Are we
00:47going to see
00:47a wave of white collar redundancies as Claude and other models put us out of a job? So Bloomberg
00:55economics, we've been making the calculations, running the models and doing that for the US
01:01and a range of other countries. We don't have definitive answers, right? This technology
01:07is still evolving. But what we do have is a kind of a range for what the estimate might be.
01:14At the top end, if we look at AI hitting its full potential, we're looking at hundreds of millions
01:21of workers, perhaps as many as 380 million workers worldwide, who are going to see their jobs
01:29significantly impacted, significantly disrupted by this new technology.
01:34When you say disrupted or impacted, does that mean they'll be using AI in some way in their jobs?
01:41Does that mean they will be displaced by AI? What can you tell us?
01:46So the way these calculations work is the first step is to break down a job into a set of
01:53tasks,
01:54right? And then to think about which of those tasks AI could do and which of those tasks AI can't
02:03do,
02:03right? So maybe think about two stylized examples, right? Think about a computer coder. Well,
02:09most of the tasks a computer coder does, AI can do. So computer coders are one of the jobs which
02:17has already been pretty significantly disrupted by AI. Well, now think about the other end of the
02:22spectrum. Think about perhaps a hairdresser. Well, could AI help with the bookings? Sure,
02:31a little bit. Could it help with keeping up with latest trends, latest styles? Yeah,
02:36a little bit. But most of it, AI is not going to be able to do, right? So that hairdresser,
02:41their job's pretty secure. So what we did was we looked at all of the jobs in the economy,
02:46and then we broke those jobs into tasks. And then we looked at which tasks AI is going to be
02:54able to
02:54do and which tasks AI is not going to be able to do. And for jobs where more than 50
03:00% of the tasks,
03:01more than 50% of what's done in that job, AI could have a significant impact. Well, those are the
03:08ones which we include in our calculation. And if you add that up across all the countries we look at
03:13worldwide, well, that's how you get to our 380 million number for the number of jobs that are going
03:19to be significantly impacted potentially by this new technology. Well, Tom, I think we're all running
03:24out to be hairstylists now. What other jobs or industries, sectors were, I don't want to say AI
03:32proof, but may fare better, let's say, in terms of workers not being displaced?
03:38So I think the way to think about this is really, to put it crudely, white collar, blue collar, right?
03:471980s, 1990s, 2000s, blue collar workers faced two massive disruptions. First, from factory automation,
03:56the arrival of robots on the factory floor. And secondly, if you were a worker in the US or Europe,
04:03from the rise of the rest, right, the rise of China, globalization and your job being outsourced.
04:09But white collar workers, they were pretty secure, right? The AI revolution is going to be hitting the
04:17white collar workers hard, right? You're an accountant, you're a computer coder, you're a trader,
04:26you're an economist, unfortunately. AI is going to bring some pretty significant disruption.
04:33If you're in the blue collar world, if you're working in a factory, if you're working in, I guess,
04:40what you might call the sort of the human touch services professions, you're a hairdresser,
04:46you're a sports coach, well, AI ain't coming for you. That's where the greatest security is going to be.
04:53So tell me what exactly are AI skills in the sense of, is that something like you're getting a STEM
05:00related degree, those types of industries, how do you acquire those types of skills?
05:04Oh, that's a really interesting question. And I think one of the sort of funny facets of this kind
05:11of dynamic is, is AI going to have a huge impact on the labor market? Yes. Could that impact be
05:19significantly negative? Could we see a wave of unemployment? Yes. Anthropic just put out a report
05:27saying that potentially unemployment in the United States could move above 10% as AI displaces
05:35knowledge workers. But right now, if we look at the impact of AI on the labor market, well, first,
05:42it's difficult to see much evidence of significant displacement, not many people losing their jobs
05:49because of AI right now. And in fact, it's a little bit the reverse, right? Huge demand for people
05:55at the really, really top end of the job spectrum to build the models. Demand for people to help train
06:04the models, right? You're a specialist in a particular sector. Well, right now, there's demand
06:10to help train AI models to make people in that sector smarter, perhaps in the long run, to replace
06:17some of those workers. And of course, demand for all of those construction workers to build the data
06:24centers, the kind of the brains of the AI universe. So one of the interesting findings from our research
06:30was, if you look, you know, not too far into the future, three, four years into the future, scope for
06:36huge disruption, right? More productivity if we want to be positive about it, more unemployment if we want
06:42to be negative about it. But right now, we don't see much, so much of that downside. But in some
06:49parts of the
06:49world, where we're building the models, where we're building the data centers, actually, we are seeing
06:54a boost to employment. Interesting. But Tom, what about new grads, those people who are in college
07:01right now? We're hearing a lot about people who went in getting one degree, maybe in computer
07:06programming or in finance. They're coming out, they're having a hard time finding jobs because AI is
07:12being used by so many companies for sort of that low and, you know, those entry level positions. Are
07:18you finding that that's the case? You know, it's funny, I was having a chat with a friend of mine
07:24over the weekend, a young guy who's just graduating in computer engineering. And I said, you know, are you
07:30worried about this? And, you know, this is just one anecdote. But he said, everything I read in the
07:37newspapers, everything I read online tells me, I have no career, I have no future. Everything I see
07:44in my email as I apply for jobs, as I apply for internships, tells me I'm going to get a
07:50job next
07:51week, right? So just one example. Certainly, a lot of news out there about young grads finding it harder
08:01to get that first step on the jobs ladder. Are we seeing that so much in the data yet? Well,
08:07something to pay close attention to. What are your thoughts on the AI boom and bust here? What are
08:12the risks? And what do you think are the potential optimistic signs there that people might be
08:16overlooking? So if we think about like the history of technology, right, game changing technologies,
08:25like railways, like the internet, what we see very often is a pattern where there's huge enthusiasm
08:35for the technology, capital piles in, valuations go sky high. But then the profits, they're not so
08:44quick to materialize. And there's a moment of pessimism. And there's a crash, right? And then
08:51people work out what's really going on. And we see the benefits, right? We saw that most vividly
08:58with the dot com boom bust cycle, the late 90s, early 2000s, right? The market roared,
09:05the market crashed. Did that mean it was the end of the dot com story? No, in some ways, it
09:10was just
09:10the beginning. And the internet revolution was very much the story of the 2000s. Well, I think the
09:17concern with AI is that we see something similar, right? This does turn out to be a game changing
09:23technology for good or ill. But before we get to that broad application, right, before we get to
09:30that world where AI is kind of part of our lives, making us all more productive, we have that boom
09:37bust cycle in the markets. And with valuations for AI companies in the US extremely high, well,
09:45some people think that that boom bust cycle is actually something that we're looking in right now.
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