Ai, Labor, Productivity and the Need for Firm-Level Data

14 Pages Posted: 22 Jan 2018 Last revised: 25 Sep 2021

See all articles by Robert Seamans

Robert Seamans

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

Manav Raj

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

Date Written: January 2018

Abstract

We summarize existing empirical findings regarding the adoption of robotics and AI and its effects on aggregated labor and productivity, and argue for more systematic collection of the use of these technologies at the firm level. Existing empirical work primarily uses statistics aggregated by industry or country, which precludes in-depth studies regarding the conditions under which robotics and AI complement or are substituting for labor. Further, firm-level data would also allow for studies of effects on firms of different sizes, the role of market structure in technology adoption, the impact on entrepreneurs and innovators, and the effect on regional economies amongst others. We highlight several ways that such firm-level data could be collected and used by academics, policymakers and other researchers.

Suggested Citation

Seamans, Robert and Raj, Manav, Ai, Labor, Productivity and the Need for Firm-Level Data (January 2018). NBER Working Paper No. w24239, Available at SSRN: https://ssrn.com/abstract=3106680

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

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

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