The Causal Impact of ChatGPT on Occupational Wage Disparities in the United States

Abstract

Generative artificial intelligence, represented by ChatGPT, has quickly become one of the most influential technologies shaping the future of work. Although scholars have long debated how automation and AI might transform employment, direct evidence on its effect on wage inequality across occupations is still scarce. This study investigates whether the introduction of ChatGPT has shifted wage patterns in the United States by drawing on data from the Bureau of Labor Statistics Occupational Employment and Wage Statistics for the years 20202024. To distinguish between occupations more and less exposed to generative AI, we employed a genetic algorithm that allows group classifications to emerge from observed wage dynamics rather than from predetermined indices. The subsequent difference-in-differences analysis shows that occupations with higher exposure to ChatGPT experienced notably slower wage growth compared with those less exposed, suggesting a widening of existing disparities. The study not only provides new empirical evidence on the labor market consequences of generative AI but also demonstrates the value of combining machine learning with econometric techniques. The findings carry important implications for policy, underscoring the need for reskilling initiatives and other measures to prevent the unequal distribution of AIs economic benefits.

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