Study: Automation drives income inequality | MIT News

If you use self-checkout machines in supermarkets and drugstores, with all due respect, you probably don’t pack your groceries any better than the cashiers used to. Automation only makes bagging cheaper for large retail chains.

“The introduction of self-checkout kiosks won’t change productivity all that much,” says MIT economist Daron Acemoglu. However, on the lost wages for workers, he adds: “There will be quite large distributional effects, particularly for low-skilled workers in the service sector. It’s more of a work-shifting device than a productivity-enhancing device.”

A newly published study co-authored by Acemoglu quantifies the extent to which automation has contributed to income inequality in the US simply by replacing workers with technology — whether it’s self-checkout machines, call center systems, assembly line technology or other devices. In the last four decades, the income gap between higher and less educated workers has widened significantly; The study finds that automation accounts for more than half of this increase.

“This single variable … explains 50 to 70 percent of the changes or variances between group inequality from 1980 to around 2016,” says Acemoglu.

The paper “Tasks, Automation, and the Rise in US Wage Inequality” appears in econometrics. The authors are Acemoglu, Institute Professor at MIT, and Pascual Restrepo PhD ’16, Assistant Professor of Economics at Boston University.

So much “mediocre automation”

Since 1980 in the US, the inflation-adjusted earnings of those with college and postgraduate degrees have risen significantly, while the inflation-adjusted earnings of men without a high school diploma have fallen by 15 percent.

How much of this change is due to automation? Rising income inequality could also be due to declining union penetration, market concentration creating a lack of competition for labor, or other types of technological change, among other things.

To conduct the study, Acemoglu and Restrepo used statistics from the US Bureau of Economic Analysis on the extent to which human labor was used in 49 industries from 1987 to 2016, as well as data on machines and software introduced during that time. The scientists also used data they had previously compiled on the introduction of robots in the US from 1993 to 2014. In previous studies, Acemoglu and Restrepo found that robots themselves have replaced a significant number of workers in the US, helping some companies dominate their industries and contributing to inequality.

At the same time, the researchers used metrics from the US Census Bureau, including data from the American Community Survey, to track work results during that time for about 500 demographic subgroups broken down by gender, education, age, race and ethnicity, and immigration status. when looking at employment, inflation-adjusted hourly wages and more from 1980 to 2016. By examining the links between changes in business practices and changes in labor market outcomes, the study is able to gauge the impact automation has had on workers.

Ultimately, Acemoglu and Restrepo conclude that the impact has been profound. They estimate that since 1980, automation has reduced the wages of men without a high school diploma by 8.8 percent and women without a high school diploma by 2.3 percent, adjusted for inflation.

A key conceptual point, Acemoglu argues, is that automation should be viewed differently from other forms of innovation, with their own distinct implications in the workplace, and not just as part of a broader trend towards lumping technology into everyday life in general should be thrown.

Think again about those self-service checkouts. Acemoglu calls these types of tools “mediocre technology” or “mediocre automation” because of the tradeoffs they contain: such innovations are good for the bottom line, bad for service industry workers, and not very important in terms of overall productivity gains, the true hallmark of an innovation that can improve our overall quality of life.

“Technological changes that create or increase the productivity of industry or the productivity of a type of work [those] big productivity gains, but not big distributional effects,” says Acemoglu. “In contrast, automation produces very large distributional effects and may not have large productivity effects.”

A new perspective on the big picture

The results hold a special place in the automation and workplace literature. Some popular technology reports predict near-total job destruction in the future. Alternatively, many scholars have developed a more nuanced picture, in which technology disproportionately benefits high-skilled workers, but also produces significant complementarities between high-tech tools and the workforce.

The current study departs, at least in degree, from this latter picture, presenting a clearer perspective in which automation reduces the earning power of workers and potentially reduces the extent to which policy solutions—more bargaining power for workers, less market concentration—could mitigate the adverse effects Effects of automation on wages.

“These are controversial results in the sense that they imply a much larger effect for automation than everyone else has assumed, and they also imply less explanatory power for others.” [factors]’ says Acemoglu.

Still, he adds that in an effort to identify the drivers of income inequality, the study “does not completely rule out other non-technological theories. In addition, the pace of automation is often influenced by various institutional factors, including workers’ bargaining power.”

Labor economists say the study is an important addition to the literature on automation, work and inequality and should be considered in future discussions on these topics.

“Acemoglu and Restrepo’s paper proposes an elegant new theoretical framework for understanding the potentially complex implications of technological change for the overall structure of wages,” says Patrick Kline, professor of economics at the University of California, Berkeley. “Your empirical finding that automation has been the dominant driver of wage dispersion in the US since 1980 is intriguing and will certainly reignite the debate about the relative roles of technological change and labor market institutions in creating wage inequality.”

For their part, Acemoglu and Restrepo identify several directions for future research in the publication. This includes examining how companies and workers respond over time to increasing automation; the quantitative impact of technologies that create jobs; and industry competition between companies that have been quick to adopt automation and those that have not.

The research was supported in part by Google, the Hewlett Foundation, Microsoft, the National Science Foundation, Schmidt Sciences, the Sloan Foundation, and the Smith Richardson Foundation.


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