The Danger of Rigged Algorithms: Evidence from Immigration Detention Decisions

26 Pages Posted: 8 Jul 2021

See all articles by David Hausman

David Hausman

Stanford University, Department of Political Science; Stanford Immigration Policy Lab

Date Written: June 30, 2021

Abstract

This article illustrates a simple risk of algorithmic risk assessment tools: rigging. In 2017, U.S. Immigration and Customs Enforcement removed the “release” recommendation from the algorithmic tool that helped officers decide whom to detain and whom to release. After the change, the tool only recommended detention or referred cases to a supervisor. Taking advantage of the suddenness of this change, I use a fuzzy regression discontinuity design to show that the change reduced actual release decisions by about half, from around 10% to around 5% of all decisions. Officers continued to follow the tool’s detention recommendations at almost the same rate even after the tool stopped recommending release, and when officers deviated from the tool’s recommendation to order release, supervisors became more likely to overrule their decisions. Although algorithmic tools offer the possibility of reducing the use of detention, they can also be rigged to increase it.

Keywords: immigration, risk assessment, algorithmic decisionmaking, empirical legal studies

Suggested Citation

Hausman, David, The Danger of Rigged Algorithms: Evidence from Immigration Detention Decisions (June 30, 2021). Available at SSRN: https://ssrn.com/abstract=3877470 or http://dx.doi.org/10.2139/ssrn.3877470

David Hausman (Contact Author)

Stanford University, Department of Political Science ( email )

Stanford, CA 94305
United States

Stanford Immigration Policy Lab ( email )

30 Alta Road
Stanford, CA 94305
United States

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