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Algorithmic Rulemaking vs. Algorithmic Guidance

Peter Henderson & Mark Krass

Algorithms are coming to government. One legal question raised by this change is the extent to which the Administrative Procedure Act (“APA”) will regulate the use of algorithms as decision-support tools for agency adjudicators. Under the APA, “rules” are officially binding statements of policy subject to notice and comment as well as rigorous pre-implementation judicial review, whereas “guidance,” officially defined as non-binding advice, is effectively unreviewable. The implementation of algorithmic tools often occupies a gray zone between the two. To...

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Video Game Addiction Lawsuits: Securing Insurance Proceeds for the Next “World-Wide Epidemic”

By David M. Cummings, Stuart Irvin & Sara Mohammed - Edited by Pantho Sayed

David M. Cummings is a partner at Reed Smith LLP and a member of the firm’s Insurance Recovery Group. Stuart Irvin is a partner at Reed Smith LLP and Co-Chair of the firm’s Video Games & Esports practice. Sara Mohammed is an associate at Reed Smith LLP and a member of the firm’s Entertainment and Media Group. Introduction In 2018, the World Health Organization (“WHO”) added “gaming disorder” as a behavioral addiction in its diagnostic system, the International Classification of...

Algorithmic Rulemaking vs. Algorithmic Guidance

Algorithms are coming to government. One legal question raised by this change is the extent to which the Administrative Procedure Act (“APA”) will regulate the use of algorithms as decision-support tools for agency adjudicators. Under the APA, “rules” are officially binding statements of policy subject to notice and comment as well as rigorous pre-implementation judicial review, whereas “guidance,” officially defined as non-binding advice, is effectively unreviewable. The implementation of algorithmic tools often occupies a gray zone between the two. To help clear the thicket, we provide a deep dive into the computer science and economics literature to provide a set of workable heuristics that help distinguish algorithmic rulemaking from algorithmic guidance. These heuristics align with best practices in the computer science literature and provide insights into agency incentives for adopting safer algorithms. We suggest that the specter of rulemaking may have value in nudging agencies toward best practices aligned with existing algorithmic safety recommendations. Specifically, avoidance of APA rulemaking may encourage agencies to prevent automation bias and other potential harms from algorithmic deployments. In this way, distinguishing algorithmic rules and guidance under the existing framework of the APA may dovetail with best practices in computer science.