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Trump Likely To Face Challenges In Plan To Revitalize Manufacturing

AUDIE CORNISH, HOST:

Even if Donald Trump can prevent companies like Carrier from moving production out of the U.S., what about his promise of putting millions of people back to work? Well, Mark Muro of the Brookings Institution says it'll be hard for Trump to deliver on that promise. That's because so much of manufacturing is now automated.

MARK MURO: What's interesting is, today's manufacturing is actually quite successful, and it doesn't take very many people. Output is as high as it's ever been right now, believe it or not, but it takes about a fifth as many people to produce the same amount of output.

We calculate about 25 workers in 1980 were needed to produce a million dollars in manufacturing output. That number's 6.5 now, and that's a problem for promises to bring back millions of jobs.

CORNISH: Now, across the Midwest, you hear stories of a time when jobs were plentiful and moreover that you just needed a high school education in order to make, you know, $20, $25 an hour. Is that just not the case anymore? And what does it mean in terms of education efforts?

MURO: Well, on the one hand, there's increased employment of higher-skilled people - engineers, for instance - who do require not only college but maybe even advanced degrees. And then there's just much more limited hiring of middle- and lower-skilled people.

If the work is extremely repetitive and routine, it can be likely done by a robot. So there are jobs - middle-skilled jobs and lower-skilled jobs - that require community college training, but they're not huge numbers. So this should not be the mainstay of a hope to bring back tens of millions of jobs to America.

CORNISH: But what about retraining? I mean if you're in your 40s, if you have a high school degree, what are the odds that you can train to do a new job in one of these manufacturing facilities?

MURO: I think it's tough but possible.

CORNISH: Will you be paid the same amount?

MURO: You will likely be paid less. You will likely need to pick up a degree of digital knowledge. Much of the manufacturing workplace is dominated by workers minding the machines, minding the robots. So what there is is a lot of low-level programming and key punch work and that kind of stuff.

CORNISH: So what realistically could be done by the next administration or any given the kind of broader trend you're talking about?

MURO: Well, I - you know, again, I think manufacturing can succeed here, is succeeding. It is critically important to really pile onto training and retraining in these programs oriented to this kind of digital, advanced manufacturing. And then I think we need to be thinking about adjustment, not a...

CORNISH: Adjustment sounds like, get used to it.

MURO: It's about being realistic. Many people are going to have to find jobs in other areas. And I think there likely is a public responsibility to help people readjust whether by changing their skills, whether by investing in new training, in education or moving, even. So adjustment has not been something we've done well or focused on much in this country, but I think we should.

CORNISH: Meanwhile, automation is not just happening in manufacturing, right? There are other sectors, too. What does this mean for the U.S. workforce?

MURO: We're doing work here at Brookings focused on what we call the digitization of the entire economy. So you can look at things that might appear like safe havens - truck driving, for instance. Truck driving should be considered an endangered occupation given that driverless trucks are very much a possibility very soon.

So I think that we have a massive retraining and rethinking of the economy ahead of us, and it's not deep in the future now. Automations and digital solutions are pervasive. So a lot of occupations are going to be feeling a lot of unease in the next decade.

CORNISH: Mark Muro is a senior fellow with the Brookings Institution. Thank you for speaking with us.

MURO: Absolutely, thank you. Transcript provided by NPR, Copyright NPR.

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