The Effects of AI, Data-Driven Decision-Making and Management Practices on Inequality and Firm Performance

Awarded Scholars:
Eric Brynjolfsson, Massachusetts Institute of Technology
John van Reenen, London School of Economics
Kristina McElheran, University of Toronto
Project Date:
Dec 2019
Award Amount:
$152,174
Project Programs:
Future of Work

CO-FUNDED WITH THE W.K. KELLOGG FOUNDATION

The past two decades have witnessed major advances in information technology capabilities, machine language and robot-enhanced practices, including programs to input, process and output large amounts of data, the application of statistical and mathematical methods to decision-making, and the simulation of higher-order thinking through computer programs.  The pace of progress and adoption of these technologies is expected to transform the world of work. This expectation has raised concerns about their implications for job tasks, productivity, the organization of work, and their effects on the competitiveness of firms, workers and communities.  While speculation abounds concerning the transformative potential of these technologies, systematic data on their diffusion and economic implications remain sparse. To redress the lack of high-quality, representative data, economists Erik Brynjolfsson, John Van Reenen and Kristina McElheran propose to partner with the U.S. Bureau of the Census to both update the Management and Organizational Practices Survey (MOPS) and add new questions relating to the presence, use, and planned use of advanced technologies.  The MOPS, which is mandatory, uses the Annual Survey of Manufacturing (ASM) survey panel to collect information on management and organizational practices at the establishment level.  A supplement to the ASM, MOPS is conducted every five years (since 2010) and includes a probability sample of 50,000 manufacturing establishments (the mail panel).            

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