10-Year Moratorium on State AI Regulation in GOP Budget Bill

In a late-night maneuver during the May 2025 Budget Reconciliation markup, House Republicans inserted sweeping language that would bar state and local governments from enacting or enforcing any artificial intelligence regulations for a full decade. The provision, championed by Rep. Brett Guthrie (R-KY), represents one of the most expansive federal preemption efforts targeting AI oversight in U.S. history. Critics warn it not only undermines federalism but also stifles crucial experimentation in areas such as healthcare, hiring, and public safety where AI systems increasingly influence outcomes.

Background: AI Oversight at the State Level

States across the U.S. have begun pioneering laws and pilot programs designed to mitigate AI risks. Key examples include:

• California’s Senate Bill 318 (effective 2024), requiring healthcare providers to disclose when patient communications involve generative AI chatbots trained on medical data.
• New York’s 2021 “Bias Audit Act,” mandating third-party fairness audits for automated recruiting tools, with metrics based on demographic parity and disparate impact ratios.
• Illinois’ Future of Artificial Intelligence Act, which sets transparency standards for predictive policing systems by mandating public reporting of model error rates (e.g., false positives/negatives).

Under the new amendment’s broad language—“no State or political subdivision thereof may enforce any law or regulation regulating artificial intelligence models, artificial intelligence systems, or automated decision systems during the 10-year period”—all existing and pending statutes fall under the ban. That includes California’s upcoming 2026 requirement for public documentation of training datasets, model architectures, and fine-tuning procedures.

Technical Scope and Definitions

The amendment defines “artificial intelligence system” to encompass:

• Generative models utilizing transformer or diffusion architectures (e.g., GPT-X series, DALL·E, Stable Diffusion).
• Automated decision systems based on traditional machine learning pipelines (e.g., credit scoring with logistic regression or random forest classifiers).
• Hybrid rule-based/ML systems such as expert systems augmented with deep learning modules for image or speech recognition.

By coupling “models” and “systems,” the text captures everything from edge-deployed anomaly detectors with under 10 million parameters to trillion-parameter large language models running in cloud data centers. In effect, no algorithmic application can escape the moratorium’s clutches.

Legal Analysis: Federalism and Preemption

Constitutional scholars note that while Congress holds clear authority under the Commerce Clause to regulate AI’s interstate impacts, a blanket preemption of state law raises separation-of-powers issues:

• Federal Preemption Doctrine: Courts consider whether the federal statute “occupies the field” such that concurrent state standards are disallowed.
• Anti-Commandeering Principle: The amendment effectively prohibits states from using their own police powers to address local harms, potentially clashing with Tenth Amendment protections.

Professor Philip Wallach of the Brookings Institution argues, “This measure transcends traditional preemption by not just harmonizing standards but nullifying state innovation. It sets a dangerous precedent for future technology regulation.”

Technical Implications for AI Governance

Experts warn that halting state-level oversight jeopardizes pilot programs and safety mechanisms that serve as real-world testbeds:

• Bias Audits: Independent evaluators currently use statistical tests—such as calibrated fairness and equalized odds—to detect discriminatory behavior in hiring algorithms. Under a moratorium, funding for these audits could dry up.
• Explainability Frameworks: Initiatives like LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations) adopted by several states for algorithmic transparency would face legal barriers.
• Data Documentation: California’s forthcoming Dataset Transparency Law, which requires model documentation following the IEEE P7000 standard, would be invalidated.

Without these safeguards, developers may continue deploying black-box systems with opaque decision logic, heightening risks of deepfake scams, unfair lending, or erroneous medical triage.

Industry and Expert Perspectives

Big Tech and allied lobbyists have celebrated the amendment as a “uniform national standard.” However, consumer advocates and AI ethicists decry it as a “gift to industry” that abandons citizens to unchecked algorithmic power.

• Jan Schakowsky (D-IL), top Democrat on the House Commerce Subcommittee: “This is a giant gift to Big Tech—states should be able to protect their own citizens.”
• Cindy Cohn, Executive Director of the Electronic Frontier Foundation: “Local governments must retain the ability to experiment with and enforce AI safety measures or we risk entrenching systemic bias at scale.”
• Kate Crawford, co-founder of the AI Now Institute: “Diverse regulatory ecosystems drive better outcomes. A 10-year freeze stifles the feedback loops that make governance robust.”

Comparative Regulatory Landscape

While U.S. states face a decade-long freeze, international efforts accelerate:

• European Union’s AI Act (provisionally agreed April 2025): Imposes risk-based requirements on high-impact systems, including mandatory conformity assessments and post-market surveillance.
• United Kingdom’s AI Safety Summit (November 2024): Led to a charter for voluntary commitments by developers on transparency and incident reporting.
• Canada’s Artificial Intelligence and Data Act (Bill C-27): Introduces obligations for “high-impact” AI systems with criminal penalties for non-compliance.

The proposed U.S. federal moratorium diverges sharply from global trends favoring dynamic oversight and iterative rule-making.

Next Steps and Outlook

The amendment faces uncertain prospects in the Senate, where a handful of moderate Republicans and all Democrats may push back. Meanwhile, the Federal Trade Commission has opened a public comment period on an unfair or deceptive acts framework for AI, signaling that federal agencies are still pursuing AI safety in parallel. White House officials have hinted at a presidential veto if federal preemption impedes core consumer protections.

Conclusion

The House GOP’s insertion of a decade-long ban on state and local AI regulation in the Budget Reconciliation bill marks a pivotal battle in U.S. tech policy. By freezing state innovation, the measure risks delaying the deployment of critical safety tools and narrowing the diversity of regulatory experiments. As the debate moves to the Senate and public comment windows remain open at federal agencies, stakeholders on all sides are mobilizing to shape America’s approach to the next wave of AI governance.