After we hear about automation and artificial intelligence replacing jobs, it could seem to be a tsunami of technology goes to wipe out staff broadly, within the name of greater efficiency. But a study co-authored by an MIT economist shows markedly different dynamics within the U.S. since 1980.
Moderately than implement automation in pursuit of maximal productivity, firms have often used automation to switch employees who specifically receive a “wage premium,” earning higher salaries than other comparable staff. In practice, meaning automation has continuously reduced the earnings of non-college-educated staff who had obtained higher salaries than most employees with similar qualifications.
This finding has no less than two big implications. For one thing, automation has affected the expansion in U.S. income inequality even greater than many observers realize. At the identical time, automation has yielded a mediocre productivity boost, plausibly attributable to the main target of firms on controlling wages quite than finding more tech-driven ways to reinforce efficiency and long-term growth.
“There was an inefficient targeting of automation,” says MIT’s Daron Acemoglu, co-author of a broadcast paper detailing the study’s results. “The upper the wage of the employee in a selected industry or occupation or task, the more attractive automation becomes to firms.” In theory, he notes, firms could automate efficiently. But they’ve not, by emphasizing it as a tool for shedding salaries, which helps their very own internal short-term numbers without constructing an optimal path for growth.
The study estimates that automation is chargeable for 52 percent of the expansion in income inequality from 1980 to 2016, and that about 10 percentage points derive specifically from firms replacing staff who had been earning a wage premium. This inefficient targeting of certain employees has offset 60-90 percent of the productivity gains from automation throughout the time period.
“It’s one among the possible reasons productivity improvements have been relatively muted within the U.S., despite the proven fact that we’ve had a tremendous number of latest patents, and a tremendous number of latest technologies,” Acemoglu says. “Then you definitely take a look at the productivity statistics, and so they are fairly pitiful.”
The paper, “Automation and Rent Dissipation: Implications for Wages, Inequality, and Productivity,” appears within the May print issue of the Quarterly Journal of Economics. The authors are Acemoglu, who’s an Institute Professor at MIT; and Pascual Restrepo, an associate professor of economics at Yale University.
Inequality implications
Dating back to the 2010s, Acemoglu and Restrepo have combined to conduct many studies about automation and its effects on employment, wages, productivity, and firm growth. Usually, their findings have suggested that the results of automation on the workforce after 1980 are more significant than many other scholars have believed.
To conduct the present study, the researchers used data from many sources, including U.S. Census Bureau statistics, data from the bureau’s American Community Survey, industry numbers, and more. Acemoglu and Restrepo analyzed 500 detailed demographic groups, sorted by five levels of education, in addition to gender, age, and ethnic background. The study links this information to an evaluation of changes in 49 U.S. industries, for a granular take a look at the way in which automation affected the workforce.
Ultimately, the evaluation allowed the students to estimate not only the general amount of jobs erased attributable to automation, but how much of that consisted of firms very specifically attempting to remove the wage premium accruing to a few of their staff.
Amongst other findings, the study shows that inside groups of staff affected by automation, the most important effects occur for staff within the Seventieth-Ninety fifth percentile of the salary range, indicating that higher-earning employees bear much of the brunt of this process.
And because the evaluation indicates, about one-fifth of the general growth in income inequality is attributable to this sole factor.
“I believe that may be a big number,” says Acemoglu, who shared the 2024 Nobel Prize in economic sciences together with his longtime collaborators Simon Johnson of MIT and James Robinson of the University of Chicago.
He adds: “Automation, in fact, is an engine of economic growth and we’re going to make use of it, however it does create very large inequalities between capital and labor, and between different labor groups, and hence it could have been a much greater contributor to the rise in inequality in the USA over the past several a long time.”
The productivity puzzle
The study also illuminates a basic selection for firm managers, but one which gets missed. Imagine a kind of automation — call-center technology, for example — which may actually be inefficient for a business. Even so, firm managers have incentive to adopt it, reduce wages, and oversee a less productive business with increased net profits.
Writ large, some version of this seems to have been happening to the U.S. economy since 1980: Greater profitability shouldn’t be the identical as increased productivity.
“Those two things are different,” says Acemoglu. “You possibly can reduce costs while reducing productivity.”
Indeed, the present study by Acemoglu and Restrepo calls to mind an commentary by the late MIT economist Robert M. Solow, who in 1987 wrote, “You possibly can see the pc age in every single place but within the productivity statistics.”
In that vein, Acemoglu observes, “If managers can reduce productivity by 1 percent but increase profits, a lot of them is likely to be glad with that. It is determined by their priorities and values. So the opposite vital implication of our paper is that good automation on the margins is being bundled with not-so-good automation.”
To be clear, the study doesn’t necessarily imply that less automation is at all times higher. Certain sorts of automation can boost productivity and feed a virtuous cycle during which a firm makes extra money and hires more staff.
But currently, Acemoglu believes, the complexities of automation are usually not yet recognized clearly enough. Perhaps seeing the broad historical pattern of U.S. automation, since 1980, will help people higher grasp the tradeoffs involved — and not only economists, but firm managers, staff, and technologists.
“The vital thing is whether or not it becomes incorporated into people’s pondering and where we land by way of the general holistic assessment of automation, by way of inequality, productivity and labor market effects,” Acemoglu says. “So we hope this study moves the dial there.”
Or, as he concludes, “We could possibly be missing out on potentially even higher productivity gains by calibrating the sort and extent of automation more rigorously, and in a more productivity-enhancing way. It’s all a selection, one hundred pc.”