To the extent that § 553 attempts to create a process that can improve the substance of regulations, it does so with specifically human intelligence in mind. If agencies over-rely on AI to carry out these procedural tasks, they threaten to undermine § 553’s goal of improving the quality of final rules.
Here is the list of works included in the January 2026 Comparative Administrative Law Scholarship Corner, which is curated by Eduardo Jordão (FGV Law School, Rio de Janeiro), with the assistance of Eduarda Onzi. The Scholarship Corner is a resource provided through the Comparative Administrative Law listserv. For more information about this terrific resource, check out my first […]
Federal agencies are rapidly expanding their use of artificial intelligence (AI) in government procurement. Much of the public discussion has centered on relatively narrow applications, such as tools that support market research or flag outdated contract clauses. When used to summarize or organize procurement-related information, these tools may pose manageable risks. More complex challenges arise when they extend into discretionary functions, including core evaluative tasks, that federal procurement doctrine presumes a human decision-maker will perform.
As these federal efforts get underway, agencies in D.C. can draw on the successes of their counterparts in Richmond. Though federal regulations and state regulations differ in certain important respects, there are substantial similarities. Here are some of the possible components of a federal AI-empowered regulatory modernization initiative.
Upon returning to the presidency, Donald Trump appointed Elon Musk as a temporary employee to head a “Department of Governmental Efficiency” (“DOGE”), using the structure of the United States Digital Service, a previously innocuous the White House entity. Executive Order, Establishing And Implementing The President’s “Department Of Government Efficiency,” §2(a) & (b) (Jan. 20, 2025).[1] […]
Can chain-of-thought prompt engineering solve the black box problem?
There’s a better way to develop administrative common law for these changing times: Rather than accept that this law is something that courts make through an exercise of judicial creativity and policy balancing, we should instead embrace an administrative common law that courts find in prevailing practices.
This post is the fifth contribution to Notice & Comment’s symposium on AI and the APA. For other posts in the series, click here. Among the operative principles of administrative law is the requirement that agencies “examine the relevant data and articulate a satisfactory explanation” for their actions, commonly known as the reasoned decisionmaking requirement. What this […]
Halfway through oral argument in Trump v. Cook, Justice Amy Coney Barrett asked Solicitor General John Sauer when a statute authorizing an officer’s removal should be read to require process. “Why shouldn’t we do the same thing that the Shurtleff court did,” Barrett asked, “and say that, well, as we said in Shurtleff, when a […]
The D.C. Circuit did not release any published opinions on administrative law last week. Its only opinion dealt with a motion to unseal applications for non-disclosure orders filed by the government under the Stored Communications Act, 18 U.S.C. § 2705(b). The orders related to a 2017 grand jury subpoena for records of the chief investigative counsel of the […]
Nothing in the APA prohibits agencies from using computational tools to gather, synthesize, or even recommend policy choices—and agencies already often rely on modeling tools to inform regulatory standards. What the APA requires is that the final rule itself be the product of reasoned judgment—supported by evidence, responsive to significant comments, and explained in a coherent manner. If those conditions are satisfied on the face of the rule, it is unlikely that a court reviewing a challenge to the rule will examine how AI was used in the decisionmaking process, perhaps absent some external reason to suspect overreliance on AI. If, on the other hand, the rule ignores key evidence, fails to address major concerns or alternatives, or offers inconsistent reasoning, it will be struck down as arbitrary regardless of whether AI was used in its development.
In a recent Notice and Comment blog post, Bernard Sharfman and Nick Morgan offer a provocative challenge to the bipartisanship requirements of the Securities Exchange Act of 1934. They argue that “it is highly likely that the partisan balance requirement” in section 4(a) of the Securities Exchange Act of 1934 “will run afoul of the […]
For much of modern constitutional law, courts have treated monetary sanctions as a lesser form of state power: important, perhaps, but fundamentally different from incarceration. Loss of liberty was punishment. Money was accounting. In Ellingburg v. United States, decided on January 20, 2026, the Supreme Court quietly but decisively rejected that distinction. Writing for a unanimous […]
This post is the third contribution to Notice & Comment’s symposium on AI and the APA. For other posts in the series, click here. Much of the emerging thinking about the relationship between administrative law and generative artificial intelligence is premised, expressly or implicitly, on the assumption that AI systems might come to play a leading role […]
Agencies will not be able to rely solely on today’s most ubiquitous forms of AI—namely, those based on ChatGPT and similar large language models—to avoid their obligation under the APA’s arbitrary and capricious standard to understand the problems they seek to solve, assess alternative solutions against legally relevant criteria, and make some kind of forecast about how these alternatives would change outcomes in the world. Administrators’ forecasts need to be about tangible outcomes, not about plausible-sounding words in sentences, however confidently they might be expressed.