Algorithmic Social Engineering

AEA Papers & Proceedings, 110 (forthcoming, 2020)

6 Pages Posted: 18 Feb 2020

See all articles by Bo Cowgill

Bo Cowgill

Columbia University - Columbia Business School

Megan T. Stevenson

George Mason University - Antonin Scalia Law School, Faculty

Date Written: January 22, 2020

Abstract

We examine the microeconomics of using algorithms to nudge decision-makers towards particular social outcomes. We refer to this as "algorithmic social engineering." In this article, we apply classic strategic communication models to this strategy. Manipulating predictions to express policy preferences strips the predictions of informational content and can lead decision-makers to ignore them. When social problems stem from decision-makers’ objectives (rather than their information sets), algorithmic social engineering exhibits clear limitations. Our framework emphasizes separating preferences and predictions in designing algorithmic interventions. This distinction has implications for software architecture, organizational structure, and regulation.

Suggested Citation

Cowgill, Bo and Stevenson, Megan, Algorithmic Social Engineering (January 22, 2020). AEA Papers & Proceedings, 110 (forthcoming, 2020). Available at SSRN: https://ssrn.com/abstract=3523999

Bo Cowgill

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

Megan Stevenson (Contact Author)

George Mason University - Antonin Scalia Law School, Faculty ( email )

3301 Fairfax Drive
Arlington, VA 22201
United States

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