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Automation Could Displace 800 Million Workers Worldwide By 2030, Study Says

Employees work on automobile parts at a production line at the BMW factory in Shenyang, China, on Nov. 22. Twelve percent of workers in China could need to switch jobs by 2030, researchers say.
AFP/Getty Images
Employees work on automobile parts at a production line at the BMW factory in Shenyang, China, on Nov. 22. Twelve percent of workers in China could need to switch jobs by 2030, researchers say.

A coming wave of job automation could force between 400 million and 800 million people worldwide out of a job in the next 13 years, according to a new study.

A report released this week from the research arm of the consulting firm McKinsey & Company forecasts scenarios in which 3 percent to 14 percent of workers around the world — in 75 million to 375 million jobs — will have to acquire new skills and switch occupations by 2030.

"There are few precedents" to the challenge of retraining hundreds of millions of workers in the middle of their careers, the report's authors say.

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The impact will vary between countries, depending on their wealth and types of jobs that currently exist in each. In 60 percent of jobs worldwide, "at least one-third of the constituent activities could be automated," McKinsey says, which would mean a big change in what people do day-to-day.

McKinsey looked at 46 countries and more than 800 different jobs in its research.

In the year 2030 in countries with "advanced economies," a greater proportion of workers will need to learn new skills than in developing economies, researchers say. As many as a third of workers in the U.S. and Germany could need to learn new skills. For Japan, the number is almost 50 percent of the workforce, while in China it's 12 percent.

Jobs that involve predictable, repetitive tasks are more easily automated, "such as operating machinery and preparing fast food," and data processing, like paralegal work and accounting. However, McKinsey estimates less than 5 percent of jobs can be fully automated.

Jobs that pay "relatively lower wages" and aren't as predictable are less likely to face full automation, because businesses don't have as much incentive to spend on the technology. This applies to jobs like gardening, plumbing and child care, according to the authors.

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Occupations that pay more but involve managing people and social interactions face less risk of automation due to the inherent difficulty in programming machines to do those types of tasks.

In the short term, automation and new technology could mean "significant" displacement of workers, the report says. But the authors argue that in the long term as technology has changed, "it creates a multitude of new jobs, more than offsetting" the number of those lost.

They note, however, those new jobs don't always pay as much as the old ones.

A rising middle class in countries like China and India, and with it more consumption, will have a big impact on the direction of economies. "As incomes rise, consumers spend more on all categories," the report says. "But their spending patterns also shift, creating more jobs in areas such as consumer durables, leisure activities, financial and telecommunication services, housing, health care, and education."

Many countries are getting older as well — Japan is a notable example. And McKinsey researchers expect aging populations to need more medical care — more doctors, nurses, home health workers and aides — while demand goes down for children's teachers and doctors.

Tech jobs will be needed as technology advances, like "computer scientists, engineers and IT administrators," who could see job growth as companies spend more in this area, the report says.

Jobs gained "could more than offset the jobs lost to automation," the researchers say. But, they say, "it will require businesses and governments to seize opportunities to boost job creation and for labor markets to function well."

The McKinsey researchers recommend "an initiative on the scale of the Marshall Plan involving sustained investment, new training models, programs to ease worker transitions, income support and collaboration between the public and private sectors" to help economies and employment grow in the future.

Copyright 2017 NPR. To see more, visit http://www.npr.org/.