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Well, as AI has become more of a growing part of our professional lives, the question has been asked about how much
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it might impact a thing like the workplace. And that question has seemingly been buried by many members of
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the seauite up until now. We're starting to hear leaders of companies have comments about just how many of their
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employees might no longer have a job in the years ahead. To more on that, we're
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joined by Peter Capelli, who is a management professor here at Wharton. He's also director of the Center on
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Human Resources. Peter, great to talk to you again. How are you, sir? >> Good. Thank you, Dan.
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>> I guess it's probably not a surprise that at some point we were going to have
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to see leaders of companies address this issue because it's just one that is
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seemingly on the forefront of a lot of people's minds. >> Yeah, it's a good thing that they're
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addressing it. I think as we'll see in a couple of minutes in the conversation,
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unfortunately they what they really should be telling people is a lot of we don't know yet. Uh and I think I'm not
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sure what they're telling them is the most useful thing yet. It's kind of
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scaring people. >> Right. Well, but the comments uh from people like Jim Farley, the Ford CEO,
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saying half of all white collar jobs will be gone. Uh is that an overestimate or is that to a degree somewhat on
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point? Well, uh, we've had those, uh, kind of forecasts for about 20 years now and
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they haven't worked out, right? So, I would say if you were a betting person,
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you would bet against that and nothing I'm seeing right now suggests that that's going to happen. Um, but, you
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know, the effects might be very different depending what kind of job you've got.
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>> Why do you think that is that maybe those some of those estimates are maybe
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a little bit high? What is it about, I guess, the structure of the company, the jobs themselves that that you see that
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is still going to require that human connection? >> Well, I think we really don't we know
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very little about how these tools can actually be used. So, the story has been driven largely by people who build them
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talking about what could be done. So we will all remember by 2019 driverless trucks would have taken over and you
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need to get rid of your truck drivers because there was you know they were going to be obsolete and there were
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companies that actually did that and then of course they got completely surprised when it hadn't happened at
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all. So, you know, the forecasts have been wildly wrong. And if you are a a person concerned about risk, I would not
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pay much attention to the forecasts because they have been wildly wrong. They've been driven largely by people
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who build the systems, thinking about what they could do rather than what's cost effective to do and what is sort of
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reasonable to do. Right? So, we're only getting a sense of that now. Is there
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some of this that we may see companies make some of these moves and then have to do a 180, a U-turn to bring people
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back in as they learn what they can and can't use? >> Yeah, I I understand there's already
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been a little bit of that in various places, but yes, I think there we probably will see that. And I I think
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there's a a reason for it that u we may have talked about before and that is you
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know in the finance world there is a real preference for companies to squeeze down headcount. Part of the reason for
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that is companies are assessed on profit per employee profit you know cost per employee everything per employee. So if
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you can get your headcount down that's really a nice thing. And employers don't
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think very much about the costs of losing people. And some of that is because human capital has no accounting
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value. Uh and so you know if you lay people off usually the investors if they do anything they just cheer. Nobody's
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thinking about what has to happen if in fact you fall short of talent. What happens then? You know we know what the
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answers are and they're not pretty but in the investment world we're not seeing
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them. So I would imagine that you probably could bet on some of that happening. Yes.
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>> And there are probably and it's and this may be a question where you know it's
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going to depend on the firm or the sector but there probably are jobs that as you go along and you look at these
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different companies different sectors that there will be jobs that would be more susceptible than others within the
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firm to potentially get cut. >> Sure. I think that's right. Now, what we're learning is those jobs appear to
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be the exact opposite of what people said they would be. So, you know, up until just a little while ago, people
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thought the simple jobs would be the ones most easily replaced. And that is not turning out to be the case. One of
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the reasons why is in simple jobs like sorting and coding, right? Or moving data from one pile to another, one set
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of documents to another. The problem with that is it has to be absolutely right. And to make sure it's absolutely
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right, you have to build the algorithms, train them on real data to make sure that it can tell what is in pile A and
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what should be in pile B. And it takes a long time to get that right and it's
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really expensive to do. On the other hand, things which are you can do right now with no training is ask the internet
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to provide a summary of what we know about the tire industry in China, right? Uh those answers are probably not going
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to be that great right now. They won't be as good as some expert would give you, but they're cheap and they're free
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and they're quick, right? So, it turns out that if you're doing some knowledge
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work, um maybe those jobs are pretty susceptible. But even there, the reality is nowhere near the hype. Let me give
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you an example. If you look at computer programmers, which is one of those where
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people are saying they're just going to be obsolete, right? Well, there have
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been for a long time tools that would help you automate programming. They'll
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suggest code that other people have already written on this topic you're trying to do with this question. So,
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that stuff's been around for a while. AI, generative AI, arguably better than
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that. But when you look at what programmers actually do on their job, it appears they only spend about 30% of
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their time actually coding, >> right? >> So what are they spending the rest of
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the time on? Negotiating a budget, talking to their clients and users to see what is it you actually need.
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Negotiating between the budget and the clients. Here's what we think we can do.
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That's where they're spending their time. So if AI took over completely the
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programming task, you still got 70% of the work that so far it looks like people do.
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>> So what does this potentially mean then as we look down the road for the next
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generation? Because obviously we're learning about a lot of this right now. that next generation coming into the
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workforce, they have to I guess if you know if you're in high school now and
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you're going to college now, you have to have the expectation that AI is going to
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be part of the mix. But you know, how much could it potentially develop? And I guess to a degree this there's a lot of
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still unknowns that haven't been answered yet. >> Yeah. And I think that is the point. Uh
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what is a mistake is making a guess and investing a lot of money in that guess. So saying for example, you know, they
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can never automate art. Uh so I'm going into art and then it turns out they can
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automate art pretty well. You know, it's just hard to know. So don't place a
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single bet and say this is the field I'm going into because, you know, we can't
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automate it. And some of the ones that, you know, it we thought they were going to automate pretty easily, it turns out
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it's hard to do. So I guess I would just not worry about it all that much trying
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to guess where the technology will go. I think the problem companies have right now and I think you hear it from the
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CEOs is that they're under pressure to respond to the hype and the hype is AI
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is the way to cut headcount. So get busy and do it. Right. Right. So there was an
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interesting survey uh of top executives saying 74% of them said that they felt their job was on the line if they
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couldn't deliver these cuts basically and they can't. They also said about a
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third of what they're doing with AI is performative. It's not actually doing
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what they say it's doing and they're kind of pretending. That doesn't mean
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they're necessarily lying but they're counting a lot of stuff as AI which is
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not even AI at all. Right? So the problem is we don't know. The CEOs are under pressure because the boards in
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particular think we do know and so they're responding in ways which are probably going to be dysfunctional.
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>> Peter, great to talk to you and get your insight as always. Thank you, sir.
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>> Thank you, Dan. >> Peter Capelli, management professor here at the Wharton School and director for
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the Center on Human Resources.