Algorithmic Governance Policy and Implementation Approaches in the United States

29 Pages Posted: 2 Sep 2021

See all articles by Karman Lucero

Karman Lucero

Paul Tsai China Center, Yale Law School

Date Written: March 01, 2020

Abstract

This article seeks to illustrate various ways in which governmental and nongovernmental entities in the United States are “governing” the development and deployment of algorithms in different industries and contexts. “Algorithm” here refers to the use of a digital process or set of rules embedded in software designed, but not always executed by, human beings to accomplish a task. Due to advances in computing power and the collection of large amounts of data, a growing number of government and private sector actors are deploying algorithms to make decisions, accomplish tasks, and understand complex systems. The intent of this paper is not to provide an exhaustive review of legal, regulatory, and policy mechanisms that apply to the broad category of artificial intelligence (AI), but instead to present a series of examples that demonstrate the distributed and dynamic nature of algorithmic governance in the United States.

Keywords: governance of algorithms, artificial intelligence regulation in the United States

Suggested Citation

Lucero, Karman, Algorithmic Governance Policy and Implementation Approaches in the United States (March 01, 2020). Available at SSRN: https://ssrn.com/abstract=3902733 or http://dx.doi.org/10.2139/ssrn.3902733

Karman Lucero (Contact Author)

Paul Tsai China Center, Yale Law School ( email )

127 Wall Street
New Haven, CT 06510
United States

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