The Impact of Automation on Income Inequality and Productivity in the U.S.
When the topic of automation and artificial intelligence replacing jobs arises, it often conjures images of a technological wave dismantling the workforce in favor of efficiency. However, a revealing study co-authored by MIT economist Daron Acemoglu uncovers a more nuanced reality in the United States since 1980.
Contrary to the assumption that companies pursue automation solely for productivity maximization, the study finds that businesses frequently automate to replace employees who earn a “wage premium,” meaning those who receive higher salaries than their peers with comparable qualifications. This strategy has disproportionately affected workers without college degrees who had previously secured relatively higher wages.
Significant Implications on Income Inequality
The research indicates two major implications of this trend. Firstly, automation has significantly contributed to the widening income inequality gap in the U.S., more so than many analysts have previously recognized. Secondly, the focus on wage control over efficiency has resulted in lackluster productivity gains, as companies prioritize short-term financial outcomes over sustainable growth.
Acemoglu explains, “There was an inefficient focus on automation. The higher the wages of the worker in a particular industry, job, or task, the more attractive automation becomes for companies.” While companies could potentially automate more efficiently, they have largely utilized it as a means to cut salaries, thus stifling optimal growth trajectories.
The study, published in the May issue of the Quarterly Journal of Economics, estimates that automation has accounted for 52% of the increase in income inequality from 1980 to 2016. Approximately ten percentage points of this can be attributed to the replacement of workers earning a wage premium. This targeted approach has obliterated 60-90% of potential productivity gains from automation during this period.
Acemoglu, who shared the 2024 Nobel Prize in Economics with collaborators Simon Johnson and James Robinson, remarks: “Automation is of course an engine of economic growth and we will use it, but it leads to very large inequalities between capital and labor and between different groups of workers and therefore may have contributed much more to the rise in inequality in the United States in recent decades.”
The Puzzle of Productivity
The study further highlights a crucial decision-making aspect often overlooked by business managers. Consider an instance where automation, like call center technology, might not enhance productivity but allows managers to cut wages and maintain higher net profits. This scenario has seemingly played out across the U.S. economy since 1980, where profitability does not equate to increased productivity.
Acemoglu notes, “These two things are different. You can reduce costs while reducing productivity.” This observation echoes the sentiment of the late economist Robert M. Solow, who famously stated in 1987: “You can see the computer age everywhere except in the productivity statistics.”
The study underscores that while automation is not inherently negative, its implementation should be carefully calibrated to enhance productivity. There exists potential for more significant productivity gains if automation is applied judiciously and strategically.
In conclusion, the research encourages a comprehensive understanding of automation’s broader historical patterns in the U.S. since 1980. It aims to inform not just economists but also business managers, workers, and technologists about the trade-offs involved in automation decisions.
Acemoglu emphasizes, “What’s important is whether it feeds into people’s thinking and where we end up in the overall holistic assessment of automation, in terms of inequality, productivity and labor market impacts. So we hope that this study will take the decisive step towards that.”
For further details, you can read the original study here.
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