How many jobs do robots really replace?


Tuesday, 12 May, 2020


How many jobs do robots really replace?

In a recent article published by MIT, economist Daron Acemoglu stated that his research shows the deployment of robots has an overall negative effect on employment in blue-collar working communities — at least in the US.

In many parts of the US, robots have been replacing workers over the last few decades — but the question is, to what extent in reality? Some technologists have forecast that automation will lead to a future without work, while other observers have been more sceptical about such scenarios.

Now a study co-authored by the MIT professor puts firm numbers on the trend, finding a very real impact — although one that falls well short of a robot takeover. The study also finds that in the US, the impact of robots varies widely by industry and region, and may play a notable role in exacerbating income inequality.

“We find fairly major negative employment effects,” said Acemoglu, although he notes that the impact of the trend can be overstated.

From 1990 to 2007, the study shows, adding one additional robot per 1000 workers reduced the national employment-to-population ratio by about 0.2%, with some areas of the US affected far more than others. This means each additional robot added in manufacturing replaced about 3.3 workers nationally, on average.

That increased use of robots in the workplace also lowered wages by roughly 0.4% during the same time period.

“We find negative wage effects — that workers are losing in terms of real wages in more affected areas — because robots are pretty good at competing against them,” Acemoglu said.

The paper ‘Robots and Jobs: Evidence from U.S. Labor Markets’ appears in advance online form in the Journal of Political Economy. The authors are Acemoglu and Pascual Restrepo PhD, an assistant professor of economics at Boston University.

Displaced in Detroit

To conduct the study, Acemoglu and Restrepo used data on 19 industries compiled by the International Federation of Robotics (IFR), a Frankfurt-based industry group that keeps detailed statistics on robot deployments worldwide. The scholars combined that with US-based data on population, employment, business and wages from the US Census Bureau, the Bureau of Economic Analysis and the Bureau of Labor Statistics, among other sources.

The researchers also compared robot deployment in the US to that of other countries, finding it lags behind that of Europe. From 1993 to 2007, US firms actually did introduce almost exactly one new robot per 1000 workers; in Europe, firms introduced 1.6 new robots per 1000 workers.

“Even though the US is a technologically very advanced economy, in terms of industrial robots’ production and usage and innovation, it’s behind many other advanced economies,” Acemoglu said.

In the US, four manufacturing industries account for 70% of robots: automakers (38% of robots in use), electronics (15%), the plastics and chemical industry (10%), and metals manufacturers (7%).

The study analysed the impact of robots in 722 commuting zones in the continental US — essentially metropolitan areas — and found considerable geographic variation in how intensively robots are utilised.

Given industry trends in robot deployment, the area of the country most affected is the seat of the automobile industry. Michigan has the highest concentration of robots in the workplace, with employment in Detroit, Lansing and Saginaw affected more than anywhere else in the country.

“Different industries have different footprints in different places in the US,” Acemoglu observed. “The place where the robot issue is most apparent is Detroit. Whatever happens to automobile manufacturing has a much greater impact on the Detroit area [than elsewhere].”

In commuting zones where robots were added to the workforce, each robot replaces about 6.6 jobs locally, the researchers found. However, in a subtle twist, adding robots in manufacturing benefits people in other industries and other areas of the country — by lowering the cost of goods, among other things. These national economic benefits are the reason the researchers calculated that adding one robot replaces 3.3 jobs for the country as a whole.

The inequality issue

In conducting the study, Acemoglu and Restrepo went to considerable lengths to see if the employment trends in robot-heavy areas might have been caused by other factors, such as trade policy, but they found no complicating empirical effects.

The study does suggest, however, that robots have a direct influence on income inequality. The manufacturing jobs they replace come from parts of the workforce without many other good employment options; as a result, there is a direct connection between automation in robot-using industries and sagging incomes among blue-collar workers.

“There are major distributional implications,” said Acemoglu. When robots are added to manufacturing plants, “the burden falls on the low-skilled and especially middle-skilled workers. That’s really an important part of our overall research [on robots]; that automation actually is a much bigger part of the technological factors that have contributed to rising inequality over the last 30 years.”

So while claims about machines wiping out human work entirely may be overstated, the research by Acemoglu and Restrepo shows that the robot effect is a very real one in manufacturing, with significant social implications.

“It certainly won’t give any support to those who think robots are going to take all of our jobs,” said Acemoglu. “But it does imply that automation is a real force to be grappled with.”

Editor’s note

How robotics affects the Australian labour market, given Australia’s lower uptake of robotics so far, is not so clear — especially since the recent closure of some manufacturing industries, such as the automobile industry, probably had a much larger effect in real terms. However, the research may give some indication of the future potential effect of robotics as a potential dampener of employment if Australia is to pivot towards more local manufacturing after the pandemic.

Image credit: MIT.

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