Four Key Pages That Could Transform American AI Policy

Rather than leaving Americans vulnerable, this framework offers a more comprehensive AI policy agenda than any previous administration has proposed. Furthermore, it creates significant room for states to exercise their authority—allowing them to enforce general laws, manage zoning for AI infrastructure, and oversee their AI applications in public services. This is a more federalism-friendly approach than the Constitution requires.

Another common criticism suggests that this is purely a partisan maneuver. However, both political parties are concerned about issues like deepfakes involving children, scams targeting seniors, and the need for small business owners to navigate AI tools. Protecting children, workers, consumers, and ratepayers transcends partisan divides, as both parties are actively advancing legislation on these matters.

Perhaps the most bewildering critiques describe the framework as granting “immunity” to AI companies, comparing its preemption to Section 230. This interpretation is fundamentally misguided. Section 230 was a form of tort reform intended to limit indirect liability because courts were overwhelmed with cases that threatened to stifle the early internet.

The preemption in this framework addresses a different concern: the potential for state legislatures to create new legal claims and regulatory burdens that target AI developers for harms caused by third parties. The framework does not advocate for shielding AI companies from general tort law; rather, it explicitly preserves the enforcement of applicable laws. The real risk lies in a patchwork of novel state laws that could deflect enforcement towards financially capable entities rather than wrongdoers, complicating the ability for any company—whether large or small—to develop AI products compliant with fifty distinct legal frameworks.

The rationale behind preemption is not about granting immunity but ensuring consistency. AI model development is inherently interstate; a model trained in one state ultimately impacts all others. If states like California, Colorado, and North Carolina impose varying obligations on developers, the most restrictive state’s regulations could unintentionally become the de facto national standard. This presents a form of regulatory overreach from a minority of state legislatures without a democratic mandate from the broader population.

A coalition of over thirty organizations—encompassing consumer advocacy groups, small-business supporters, taxpayer organizations, and technology policy centers—recently sent a letter to Congress endorsing the framework. Their clear message was that without a uniform national standard, the U.S. risks losing its position as a leader in AI to global competitors, leaving the majority of Americans on the periphery of the AI economy.

Critics who wish for this initiative to fail should consider the alternative: increased fragmentation state by state, heightened regulatory uncertainty, and greater advantages handed to China, all while many Americans miss out on the tools that millions are utilizing to address health and insurance questions, learn more efficiently, and make significant scientific discoveries.

Congress has undertaken extensive preparation for AI policy, and the White House has now presented a structured plan for translating that groundwork into federal law. While these four pages alone won’t create legislation, they could significantly influence the direction of AI policy for decades—should Congress choose to heed the President’s lead.