Trump Administration Official Says Quiet Part Out Loud on AI-in-Government Plans

2026-02-05 · Source: Tech Policy Press · Field: Government & Public Sector — Digital Government & E-Government, Public Policy & Governance, Regulatory & Compliance · Depth: Intermediate, medium

Summary

The United States Department of Transportation (DOT) plans to use Google Gemini, a large language model, to draft federal transportation regulations, aiming to outsource 80% to 90% of the work. This initiative, presented to DOT staff last month, seeks to "revolutionize" rulemaking by reducing draft creation to under 20 minutes per rule, positioning DOT as the "point of the spear" for a broader federal AI adoption. This approach aligns with previous reports of the US DOGE Service's intent to use AI to rescind half of all federal regulations. However, critics highlight significant legal and policy risks, including LLM "hallucinations," biases, and struggles with complex documents, which could lead to arbitrary and capricious rules under the Administrative Procedure Act (APA). Despite these concerns, DOT officials reportedly prioritize speed and volume over perfection, aiming for "good enough" rules to "flood the zone."

Key takeaway

For legal and policy professionals involved in regulatory oversight, the DOT's plan to use Google Gemini for drafting federal regulations signals a critical need for vigilance. You should prepare to scrutinize new DOT proposals and final rules for potential factual, legal, or logical errors that could render them arbitrary and capricious under the Administrative Procedure Act. Actively push for transparency regarding AI use in rulemaking and be ready to challenge rules that appear to be mere "rubber-stamps" of LLM outputs, as this approach risks undermining good governance and public safety.

Key insights

Over-reliance on LLMs for federal rulemaking introduces significant legal and policy risks due to inherent AI limitations.

Principles

• Federal rulemaking requires rigorous human oversight.
• LLMs are prone to errors, bias, and sycophancy.
• "Good enough" rules risk legal invalidation.

In practice

• Monitor Federal Register for AI-generated rules.
• Scrutinize rules for arbitrary and capricious errors.
• Advocate for AI disclosure in rulemaking.

Topics

• AI in Government
• Large Language Models
• Federal Rulemaking
• Google Gemini
• AI Legal Risks

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech Policy Press.