Experience Stern | Faculty & Research

Artificial intelligence (AI), like other technologies in the past, will likely affect the economy in many ways, potentially stimulating growth and changing the way people work. The effect of AI on work will be multifaceted and will likely vary across occupations and industries. The public release of tools such as Dall-E 2, which generates digital images from natural language prompts, in September 2022 and ChatGPT, which generates text responses to natural language prompts, in November 2022 has drawn the attention of the general public to progress in generative AI technologies, stimulating excitement in the potential of these technologies, but also concern over potential negative effects on employment. The expanded scope of uses presented by generative AI technologies has raised questions regarding whether such technologies may affect a broader range of occupations, including those that are highly creative.

Recent research, including our own9 and work by the Pew Research Center, suggests there is a strong positive correlation between exposure to generative AI and median salaries, the required level of education, and the presence of creative abilities within an occupation, and that occupations with a higher percent of female or Asian workers are more exposed, whereas occupations with a higher percent of Black or Hispanic workers are less exposed to generative AI. The big unknowns are the conditions under which generative AI will substitute for work previously done by humans, or complement work done by humans (for example, Frank et al. While recent research suggests that generative AI is likely to increase high-skill worker productivity, especially for lower-performing workers (for example, Choi and Schwarcz, Dell’Acqua et al., Noy and Zhang, and Peng et al.), whether and under what conditions generative AI automates vs. augments workers remains an important and, to our knowledge, unanswered question.

We highlight two ways in which the government can help address heterogeneous effects from advances in AI. First, statistical agencies should work with academic scholars to develop an understanding about conditions under which AI automates or augments human work. Second, the uncertain and different effects across occupations means initial labor policies need to be flexible and broad-based, not targeted at specific occupations or groups.

Read the full Communications of the ACM article.
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Robert Seamans is Associate Professor of Management and Organizations and Director of the Center for the Future of Management