Artificial Intelligence and Federal Rulemaking
Summary
The report discusses the potential for artificial intelligence to increase efficiency in federal rulemaking while warning that its use must complement, rather than replace, rigorous human reasoning to avoid flawed regulations.
Key insights
- Integrating AI tools into federal rulemaking could make the regulatory process significantly more efficient, allowing the government to be more responsive and effective in its governance.
- While the Administrative Procedure Act (APA) does not prohibit the use of AI for drafting rules, reviewing public comments, or performing analyses, relying on AI may prioritize efficiency over caution, increasing the risk of finalizing fundamentally flawed rules.
- To prevent logical or factual flaws that could lead to legal challenges, agencies must rigorously review model training data, parameters, and methodology, ensure clean data and accurate prompts, and check outputs for bias or hallucinations.
Cite the original document
- APA
- Ph.D., J. J. M. S. B. Ü. (2026). Artificial Intelligence and Federal Rulemaking. Institute for Policy Integrity. https://policyintegrity.org/publications/detail/artificial-intelligence-and-federal-rulemaking
- Chicago
- Ph.D., Jack Jones, Max Sarinsky, Burçin Ünel,. Artificial Intelligence and Federal Rulemaking. Institute for Policy Integrity, 2026. https://policyintegrity.org/publications/detail/artificial-intelligence-and-federal-rulemaking.
- Wikipedia
- {{cite report |last1=Ph.D. |first1=Jack Jones, Max Sarinsky, Burçin Ünel, |title=Artificial Intelligence and Federal Rulemaking |publisher=Institute for Policy Integrity |date=29 July 2026 |url=https://policyintegrity.org/publications/detail/artificial-intelligence-and-federal-rulemaking |access-date=23 October 2026 |via=Climate Insights Directory}}
- BibTeX
- @techreport{phd2026artificial, author = {Ph.D., Jack Jones, Max Sarinsky, Burçin Ünel,}, title = {{Artificial Intelligence and Federal Rulemaking}}, institution = {Institute for Policy Integrity}, year = {2026}, month = jul, url = {https://policyintegrity.org/publications/detail/artificial-intelligence-and-federal-rulemaking}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }
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