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Title: The U.S. AI Workforce
Citation Type: Miscellaneous
Publication Year: 2021
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Abstract: Having access to the right talent is critical to maintaining a competitive edge in artificial intelligence. In the United States, policymakers are actively discussing legislative proposals to grow and cultivate a globally competitive domestic AI workforce. However, little data is available on the U.S. AI workforce and associated talent pipelines outside of the PhD segment. Yet having access to good workforce data is critical to actually “winning” the competition for AI talent. This brief provides two contributions to better understand the U.S. AI workforce: (1) a definition of the AI workforce based on the government occupational classification system, identifying 54 occupations that either participate or could participate in AI product and application development, and (2) a preliminary assessment and characterization of the supply of AI talent, which consisted of 14 million workers in 2018 (about 9% of total U.S. employment). Our definition of the AI workforce enables supply-side analysis that is more comprehensive than other commonly used sources, because it is linked to the federal occupation classification system. While many supply-side analyses of the AI workforce rely on sources such as LinkedIn, we use data from the U.S. Census Bureau. Our definition also enables greater analytic consistency across federal government and other datasets that link to this classification system, such as Burning Glass.
Url: https://cset.georgetown.edu/wp-content/uploads/US-AI-Workforce_Brief.pdf
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Authors: Gehlhaus, Diana; Mutis, Santiago
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Data Collections: IPUMS USA
Topics: Labor Force and Occupational Structure
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