Old And Young Populations Need Automation, But for Different Reasons
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Old And Young Populations Need Automation, But for Different Reasons

Meeting GDP and development goals will need a combination of humans and machines working together.

Workplace automation is a source of uncertainty in contemporary politics and economics, looming large in the future while we shakily chart a path towards it in the present. It's safe to say this uncertainty comes with more than a pinch of anxiety: Over the 38 percent of US jobs that will be "lost to automation" as a PwC report claimed, or the driving jobs that will be "all but obsolete" within decades.


That's why it's surprising—in a very welcome way—to hear Michael Chui, partner at the McKinsey Global Institute, argue that automation is not a threat, but rather a necessity in order for countries around the world to meet their growth and development goals.

Over the past two years, Chui and his co-authors have been collecting data from government agencies across the world about workforce demographics, wage rates, and technological adoption, as well as surveying a wealth of academic literature and other McKinsey studies. The resulting analysis was compiled into a report titled A Future That Works, published earlier this year, and has been expanded into a series of articles across various platforms, including a recent feature in Harvard Business Review on the countries most and least likely to be affected by automation.

One of the findings of the research is that regardless of whether countries have fat or lean economies and youthful or aging populations, automation is far more likely to bring net benefits than losses, albeit for different reasons.

"As countries age they have a lower ratio of workers to people who need to be supported, and as a result we simply need more productivity per hour worked. For countries lower on the GDP per capita scale with aging populations this still holds," Chui said in a phone call.

Initially, Chui and his co-authors had believed that for countries with younger populations such as India or Mexico, widespread automation would occur just as large numbers of humans were joining the workforce, leading to competition and suboptimal outcomes—but in fact, they concluded this was not the case.


"What we actually found was, those countries are lower on the GDP per capita scale, so their aspirations for economic growth are still high," said Chui. "So even for young countries, with all those young people working plus the robots, you still need more productivity for them to reach their growth aspirations."

An upshot of this is that while much of the discussion around automation has focused on the idea of an ensuing labor surplus, in reality a labor deficit is more likely, which should be reflected by our policy responses in the present.

"Rather than aiming to manage for mass unemployment, we really need to make decisions that allow for mass redeployment of labor, so that all the people can be working with all the machines to give us economic growth," Chui said.

He also stresses that we can see this kind of redeployment historically in the transition from agriculture to industry, where the technology that displaced jobs also created new ones, and investment from both the public and private sectors helped workers retrain.

"People think this is unprecedented, but it's precedented!" Chui said. "Having a double digit percentage of jobs in the economy change in a few decades did happen, and we don't have 35 percent unemployment from the early 1900s 'til now."

Even if, from a personal standpoint, aspects of our working lives seem to be changing fast, Chui also points out that macro level societal changes move far more slowly.

"It will take quite a while for all this to happen, so there will be time to adapt as we adopt," he said.

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