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Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data

Manav Raj, Robert Seamans

Chapter in NBER book The Economics of Artificial Intelligence: An Agenda (2019), Ajay Agrawal, Joshua Gans, and Avi Goldfarb, editors (p. 553 - 565)
Conference held September 13-14, 2017
Published in May 2019 by University of Chicago Press
© 2019 by the National Bureau of Economic Research

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 examines robotics rather than AI, and uses statistics aggregated by industry or country, which precludes in-depth studies regarding the conditions under which these technologies complement or substitute 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.

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