AI’s Impact on Income Inequality in the US

According to one survey, about half of Americans think that the increased use of AI will lead to greater income inequality and a more polarized society. Roughly two thirds think the government should take action to prevent the loss of jobs due to AI, and 46% of young Americans think that it is at least somewhat likely that AI will replace their job in the next five years.

While economists have generally been less concerned than the public about drastic scenarios of AI-driven job loss in the near-term, they often do share concerns around AI’s potential to exacerbate income inequality. To empirically estimate this possibility, researchers have recently taken to studying the impacts of new AI systems on worker productivity—a key determinant of wages. Interestingly, several studies have now found that within certain occupation groups—including lawyers, software engineers, customer service agents, management consultants, and workers performing professional writing tasks—the lowest skilled or least experienced workers derive much greater productivity gains from AI than their higher skilled, more experienced counterparts.

Some leading economists, such as MIT’s David Autor, have praised these results as supporting the hypothesis that AI could boost middle class wages and help reduce inequality. This would be a welcome course correction for technology’s impact on wages in the U.S. over the last 40 years, during which about 50-70% of the increase in wage inequality has been attributed to the introduction of new automation technologies. In an eloquent Noema magazine piece in February, Autor points to the task-level studies of AI’s impact on programming, writing-intensive work, and customer service work as evidence that AI can help enhance the capabilities of novice workers in these jobs, empowering them in a way that could help diminish inequality.

While this positive vision is a useful target for policymakers, this task-level evidence within occupations can be misleading when attempting to predict the economy-wide impacts of AI on inequality. By relying on it, we risk overlooking broader implications of AI on inequality both now—while AI is mainly used to boost worker productivity on tasks—and in the future, when new systems will become more reliable at fully automating more complex tasks. This commentary argues that there are at least two likely mechanisms through which AI could increase inequality in the U.S.:

1. In the near-term, AI-driven productivity boosts could be skewed towards high-income workers, leaving lower-wage workers behind
2. In the slightly longer term, AI-driven labor automation could increase the share of income going to capital at the expense of the labor share

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