Document Type

Article

Abstract

Administrative agencies’ growing use of automated decisionmaking tools poses threats to core democratic values, such as agency flexibility, expertise, fairness, transparency, and accountability. But decades of privatization have wrought similar, lasting harms to the United States’ public institutions. This Article argues that the thoughtful criticisms and prescriptions from the burgeoning literature on the government’s use of artificial intelligence should be used to strengthen the scrutiny accorded to privatization.

Specifically, this Article challenges the perception that automated decisionmaking poses a greater threat to public values than privatization. Indeed, the two share several characteristics and goals. These include, for example, a fixation on efficiency, reliance on oversimplified cost-benefit analyses, erosion of agency expertise and resources, and separation between public officials and their decisions’ impact on individuals. In that separation, algorithms and private actors make important decisions often carrying political and fairness consequences. As policymakers adapt the latest expert guidance regarding algorithms to the problems of privatization, they should prioritize the needs and voices of the marginalized individuals who have been most harmed by the privatization movement.

DOI

10.37419/LR.V12.I2.8

First Page

831

Last Page

889

Recommended Citation

Landyn Rookard, The Common Threats of Artificial Intelligence and Privatization, 12 Tex. A&M L. Rev. 831 (2025).
Available at: https://doi.org/10.37419/LR.V12.I2.8

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