The Occupational Impact of Artificial Intelligence: Labor, Skills, and Polarization

67 Pages Posted: 7 May 2019

See all articles by Edward W. Felten

Edward W. Felten

Princeton University - Center for Information Technology Policy; Princeton University - Woodrow Wilson School of Public and International Affairs; Princeton University - Department of Computer Science

Manav Raj

New York University (NYU) - Leonard N. Stern School of Business

Robert Seamans

New York University (NYU) - Leonard N. Stern School of Business

Date Written: September 8, 2019

Abstract

Although artificial intelligence (AI) promises to spur economic growth, there is widespread concern that it may replace human labor. We investigate the link between AI and labor by creating a new measure that we call the AI Occupational Impact (AIOI). The AIOI measure links advances in specific applications of AI, such as image recognition, translation, or the ability to play strategic games, to workplace abilities and occupations. We use this measure to study the relationship between AI and wages, employment, and labor market polarization. We provide evidence that, on average, occupations impacted by AI experience a small but positive change in wages, but no change in employment. We also provide evidence that the positive correlation with wages is driven primarily by occupations with higher software skill requirements, and that higher-income occupations have a strong positive relationship between our measure of AI impact and both employment and wages. These findings suggest that access to complementary skills and technologies may play an important role in determining the impact of AI, and that AI has the potential to exacerbate labor market polarization.

Keywords: artificial intelligence, automation, economic implications, employment, labor, wages

JEL Classification: J23, J24, O33

Suggested Citation

Felten, Edward W. and Raj, Manav and Seamans, Robert, The Occupational Impact of Artificial Intelligence: Labor, Skills, and Polarization (September 8, 2019). Available at SSRN: https://ssrn.com/abstract=3368605 or http://dx.doi.org/10.2139/ssrn.3368605

Edward W. Felten

Princeton University - Center for Information Technology Policy ( email )

Sherrerd Hall, Third Floor
Princeton, NJ 08544
United States

Princeton University - Woodrow Wilson School of Public and International Affairs ( email )

Princeton University
Princeton, NJ 08544-1021
United States

Princeton University - Department of Computer Science ( email )

35 Olden Street
Princeton, NJ 08540
United States

Manav Raj

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

Robert Seamans (Contact Author)

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

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