Automation Will Replace Production, Food, and Transportation Jobs First

Job displacement from automation will be distributed unevenly. 

The benefits of automation, and the detriments, will be unevenly shared. That’s because different jobs, regions, and groups of people will have varying degrees of susceptibility to job displacement, according to a new paper from the researchers at the Brookings Institute.

Production, food service, and transportation jobs appear to be the most susceptible to the trend, with between 70 and 100 percent of their tasks likely to be automated. On the other end of the spectrum? Business jobs, a fact that’s sure to be a huge relief to the business executives who recently gathered to discuss the problem of automation, among others, at last week’s World Economic Forum in Davos. In 2017, roughly half of businesses used machines to replace at least some human labor, the NYT recently reported. Next year, that proportion is expected to climb to 72 percent.

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Which jobs are most susceptible to automation? 

Some of the findings aren’t that much of a surprise, for example that rural, less populated regions are more likely to see job displacement from task automation than growing cities. Workers that are more educated are also less susceptible to the trend, because their skills are more difficult to replicate through machinery or A.I.. But Brookings also notes some surprising demographic factors at play, too.

Hispanic workers, for example, have an average automation potential of 47 percent, eight percentage points higher than Asian and Pacific Islanders. Most surprisingly, young people seem to face the highest risk of automation potential, with almost half of the work done by 16 through 24-year-olds likely to be automated. This mostly has to do with the type of work that young people tend to: This demographic makes up just 9 percent of the workforce, but 24 percent of food service jobs, Brookings found.

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Younger employees will be more susceptible to automation than older ones. 

Nobody is more disproportionately susceptible to automation, however, than working men, at least demographically. Again, this mostly has to do with the types of jobs men are more likely to do: Men hold about 70 percent of production jobs, 80 percent of transportation jobs, and more than 90 percent of construction jobs, three of the six most-likely-to-be-automated fields. This is exacerbated by the fact that the opposite is true for women, who tend over-index in fields that are also safer from automation, for example healthcare, personal care, and education.

Of course, automation isn’t a net-negative, Brookings finds, for a few key reasons. Automation increases demand, for one, which creates more demand for labor elsewhere. Self-driving trucks will put truck drivers out of work, for example, but by drastically reducing shipping costs it will make it cheaper for manufacturers to simply make more stuff, offsetting some of the job loss.

To ensure that society experiences the fruits of automation, Brookings recommends a host of policies, mostly having to do with education, re-training, and local grants to mitigate the impact in regions that are particularly vulnerable to closures having an outsize impact on employment. The authors also propose something not unlike a universal basic income, what they call a “universal adjustment benefit.” The perks in this UAB would essentially be threefold: expanded access to career counseling, job re-training, and targeted income support, for example moving support for people who are willing to re-locate to change jobs.