At its 74th Plenary Session in June, the Assembly of the Administrative Conference of the United States adopted four new recommendations. One of these (Recommendation 2021-1, Managing Mass, Computer-Generated, and Falsely Attributed Comments) provoked three (!) separate statements, from Senior Fellows Randy May, Nina Mendelson, and Dick Pierce. The dialogue offers a fascinating window into the present debate over the purpose, promise, and limitations of the informal rulemaking process. So I will post those statements separately over the next few days. Finally, you may recall that there were five proposed recommendations up for discussion at the Plenary. One was sent back to the Committee on Judicial Review for further discussion. That committee is scheduled to meet this summer to do that work (more details at the end of this post).

First (and cribbing from the Federal Register notice), here are the newly adopted recommendations include:

Recommendation 2021-1, Managing Mass, Computer-Generated, and Falsely Attributed Comments. This recommendation offers agencies best practices for managing mass, computer-generated, and falsely attributed comments in agency rulemakings. It provides guidance for agencies on using technology to process such comments in the most efficient way possible while ensuring that the rulemaking process is transparent to prospective commenters and the public more broadly.

Recommendation 2021-2, Periodic Retrospective Review. This recommendation offers practical suggestions to agencies about how to establish periodic retrospective review plans. It provides guidance for agencies on identifying regulations for review, determining the optimal frequency of review, soliciting public feedback to enhance their review efforts, identifying staff to participate in review, and coordinating review with other agencies.

Recommendation 2021-3, Early Input on Regulatory Alternatives.This recommendation offers guidance about whether, when, and how agencies should solicit input on alternatives to rules under consideration before issuing notices of proposed rulemaking. It identifies specific, targeted measures for obtaining public input on regulatory alternatives from knowledgeable persons in ways that are cost-effective and equitable and that maximize the likelihood of obtaining diverse, useful responses.

Recommendation 2021-4, Virtual Hearings in Agency Adjudication. This recommendation addresses the use of virtual hearings—that is, proceedings in which participants attend remotely using a personal computer or mobile device—in agency adjudications. Drawing heavily on agencies’ experiences during the COVID-19 pandemic, the recommendation identifies best practices for improving existing virtual-hearing programs and establishing new ones in accord with principles of fairness and efficiency and with due regard for participant satisfaction.

The embedded links above will take you to the appropriate project page on ACUS’s website, where you can find all of the documents underlying each recommendation (research reports, draft recommendations, staff research memos, member comments, etc.). The full text of each recommendation is published in the Federal Register notice and available on ACUS’s website.

The recommendation that is headed back to committee is about Clarifying Statutory Access to Judicial Review of Agency Action. In the lead-up to the Plenary, several members raised concerns about how the recommendation would apply to direct final rules and interim rules. The Assembly decided it would be prudent to give the Committee on Judicial Review the time and opportunity to address these concerns. The committee will do that work at a meeting to be held from 1-4 pm Eastern on July 22, 2021.

This post is part of the Administrative Conference Update series, which highlights new and continuing projects, upcoming committee meetings, proposed and recently adopted recommendations, and other news about the Administrative Conference of the United States. The series is further explained here, and all posts in the series can be found here.