A study co-authored by MIT economist Daron Acemoglu highlights a troubling trend in how U.S. companies implement automation. Instead of maximizing productivity, firms often deploy automation to replace employees earning a “wage premium,” which has implications for income inequality.
Targeting Wage Premiums
The research indicates that since 1980, automation has disproportionately affected non-college-educated workers who earn higher salaries than their peers. This targeted approach has not only exacerbated income inequality but has also yielded a modest increase in productivity. Acemoglu states, “There has been an inefficient targeting of automation. The higher the wage of the worker in a particular industry or occupation or task, the more attractive automation becomes to firms.” This suggests that companies prioritize short-term financial gains over long-term efficiency.
Impact on Income Inequality
The study estimates that automation accounts for 52 percent of the growth in income inequality from 1980 to 2016, with approximately 10 percentage points attributed to the replacement of higher-paid workers. This targeting has mitigated 60-90 percent of the productivity gains expected from automation. Acemoglu notes, “It’s one of the possible reasons productivity improvements have been relatively muted in the U.S., despite the fact that we’ve had an amazing number of new patents, and an amazing number of new technologies.”
Methodology and Findings
To arrive at these conclusions, Acemoglu and co-author Pascual Restrepo analyzed data from various sources, including U.S. Census Bureau statistics and the American Community Survey. Their granular analysis covered 500 demographic groups across 49 U.S. industries, revealing that the most significant impacts of automation are felt by workers in the 70th-95th salary percentiles. This group has borne the brunt of automation’s effects, contributing to about one-fifth of the overall growth in income inequality.
Productivity vs. Profitability
The study raises critical questions about the choices made by firm managers. Acemoglu points out that managers may adopt automation that reduces productivity if it leads to lower costs and higher profits. This dynamic has been evident in the U.S. economy since 1980, where profitability does not equate to productivity. He emphasizes that “good automation at the margins is being bundled with not-so-good automation,” suggesting that the current approach to automation may overlook opportunities for genuine productivity enhancement.
In conclusion, the study underscores the need for a reevaluation of how automation is integrated into business practices. Acemoglu hopes this research will encourage a more nuanced understanding of the trade-offs involved in automation, particularly regarding its effects on inequality and productivity.
This article was produced by NeonPulse.today using human and AI-assisted editorial processes, based on publicly available information. Content may be edited for clarity and style.
