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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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Apple AirTag Stalking Class Action Survives Motion to Dismiss

By Chloe Suzman – Edited by Pantho Sayed

Background

First Amended Class Action Complaint, Hughes v. Apple, Inc., No. 22-cv-07668-VC (N.D. Cal. October 6, 2023), complaint hosted by ArsTechnica. Order Partially Granting Motion to Dismiss, Hughes v. Apple, Inc., No. 22-cv-07668-VC (N.D. Cal. March 15, 2024), order hosted by Casetext. Order Partially Denying and Partially Granting the Motion to Dismiss, Hughes v. Apple, Inc., No. 22-cv-07668-VC (N.D. Cal. March 15, 2024), order hosted by Casetext.

Introduction

On March 15, 2024, Judge Vince Chhabria of the United States District...

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.