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How many jobs do robots really replace?

How many jobs do robots really replace? article image

MIT, a world-famous private research university in Cambridge, Massachusetts has released a report by economist and MIT Professor Daron Acemoglu examining the effects of robots and automation on employment in the US. Here is a summary of his findings and the results may surprise you…

In many parts of the US robots have been replacing workers over the last few decades.

But to what extent, really? Some technologists have forecast that automation will lead to a future without work, while other observers have been more skeptical about such scenarios.

Now a study co-authored by an 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.

From 1990 to 2007, adding one additional robot per 1,000 workers reduced the national employment-to-population ratio by about 0.2 percent, Professor Acemoglu’s study shows, 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 percent during the same time period.

To conduct the study, Acemoglu and co-author Pascual Restrepo, an assistant professor of economics at Boston University used data on 19 industries. This data was 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.

Lagging behind Europe

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 1,000 workers; in Europe, firms introduced 1.6 new robots per 1,000 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,” Prof Acemoglu says.

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

Across the US, 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 utilized.

Significant social implications

In conducting the study, the researchers 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.

While claims about machines wiping out human work entirely may be overstated, the research 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,” Prof Acemoglu says. “But it does imply that automation is a real force to be grappled with.”

Within industries adopting automation, the study shows, the average “displacement” (or job loss) from 1947-1987 was 17 percent of jobs, while the average “reinstatement” (new opportunities) was 19 percent.

But from 1987-2016, displacement was 16 percent, while reinstatement was just 10 percent. In short, those factory positions or phone-answering jobs are not coming back.

“A lot of the new job opportunities that technology brought from the 1960s to the 1980s benefitted low-skill workers,” Prof Acemoglu adds. “But from the 1980s, and especially in the 1990s and 2000s, there’s a double whammy for low-skill workers: They’re hurt by displacement, and the new tasks that are coming, are coming slower and benefitting high-skill workers.”

Firms that quickly adopted robots became more productive

The new paper is one of several studies Acemoglu and Restrepo have conducted recently examining the effects of robots and automation in the workplace. In a just-published paper, they concluded that across the US from 1993 to 2007, each new robot replaced 3.3 jobs.

In still another new paper, Acemoglu and Restrepo examined French industry from 2010 to 2015. They found that firms that quickly adopted robots became more productive and hired more workers, while their competitors fell behind and shed workers — with jobs again being reduced overall.

In the current study, Acemoglu and Restrepo construct a model of technology’s effects on the labour market, while testing the model’s strength by using empirical data from 44 relevant industries. (The study uses US Census statistics on employment and wages, as well as economic data from the Bureau of Economic Analysis and the Bureau of Labour Studies, among other sources.)

The result is an alternative to the standard economic modelling in the field, which has emphasised the idea of “skill-biased” technological change – meaning that technology tends to benefit select high-skilled workers more than low-skill workers, helping the wages of high-skilled workers more, while the value of other workers stagnates. Think again of highly trained engineers who use new software to finish more projects more quickly: They become more productive and valuable, while workers lacking synergy with new technology are comparatively less valued.

However, Acemoglu and Restrepo think even this scenario, with the prosperity gap it implies, is still too benign. Where automation occurs, lower-skill workers are not just failing to make gains – they are actively pushed backward financially.

Productivity gains should be higher

Acemoglu and Restrepo note, the standard model of skill-biased change does not fully account for this dynamic; it estimates that productivity gains and real (inflation-adjusted) wages of workers should be higher than they actually are.

More specifically, the standard model implies an estimate of about 2 percent annual growth in productivity since 1963, whereas annual productivity gains have been about 1.2 percent; it also estimates wage growth for low-skill workers of about 1 percent per year, whereas real wages for low-skill workers have actually dropped since the 1970s.

“Productivity growth has been lacklustre and real wages have fallen,” Prof Acemoglu says. “Automation accounts for both of those. And demand for skills has gone down almost exclusively in industries that have seen a lot of automation,” he adds.

However, Prof Acemoglu contends, the net negative consequences of technology on jobs is not inevitable. We could, perhaps, find more ways to produce job-enhancing technologies, rather than job-replacing innovations.

“It’s not all doom and gloom,” he says.

“There is nothing that says technology is all bad for workers. It is the choice we make about the direction to develop technology that is critical.” 

The new paper, “Unpacking Skill Bias: Automation and New Tasks,” will appear in the May issue of the American Economic Association: Papers and Proceedings. The authors are Professor Daron Acemoglu, who is an Institute Professor at MIT, and Pascual Restrepo, an assistant professor of economics at Boston University.

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