As generative AI accelerates into every corner of society — classrooms, hospitals, factories, churches, HOA boardrooms, and cybersecurity operations centers — the debate over who gets to govern it is no longer academic. It has become a proxy battle over power, innovation, and ultimately the future of knowledge itself.
Recently, former President Donald J. Trump and some members of the GOP pushed proposals that would bar U.S. states from passing new regulations on generative AI, with versions of the idea advocating for a 10-year moratorium on state and local AI laws. To many casual observers, this sounds like a bid for regulatory simplicity. But to technologists and civil society alike, it reflects something far more dangerous: policy paralysis based on politics, not science.
A decade-long freeze on state AI rules doesn’t streamline innovation. It strangles evolution. And while framed as a solution for a "patchwork" of 50 states, it would, in practice, centralize AI governance under a single federal and ideological lens, risking inconsistent protections, regulatory capture by large tech firms, and the chilling of community-driven algorithm audits, transparency initiatives, and educational innovation — the heartbeat of early AI progress in America.
The United States did not become a leader in digital innovation by telling local governments to sit on their hands for ten years. Quite the opposite. Federated experimentation is an American superpower. When states craft independent policy responses to emerging technology, they build laboratories in parallel instead of assembly lines in sequence. They fail small, learn fast, and adapt openly.
Think of the major pillars of AI governance already enacted not by Congress, but by state governments:
- Laws requiring AI systems to disclose their safety protocols
- Protection for whistleblowers reporting AI risks
- Rules governing algorithmic fairness in hiring and lending
- Consumer protections against unauthorized AI impersonation
- Guardrails restricting the most harmful uses of deepfakes
- Data and decision transparency mandates
These rules emerged from local necessity, not national political theater. And significantly, they were passed while AI research continued to flourish, proving that regulation — when designed thoughtfully — does not have to impede innovation. It can direct it.
Meanwhile, in Washington, many national conversations about AI legislation oscillate between extremes: total deregulation versus sweeping restriction. What innovators don’t need are one-size-fits-all laws written to satisfy political talking points about “wokeness” or cultural grievances. What research, startups, universities, and nonprofits need is clarity — narrow and functional — so they can build without fear of abrupt federal upheavals or decades of stagnation.
The deeper issue exposed here is this: Who gets to shape the AI rulebook also shapes future learning pathways.
If the federal government establishes AI safety laws purely as minimum standards — a floor protecting the public from the worst harms without restricting open scholarship — this is healthy governance. If the federal government sets a ceiling that overrides states, influencers, civil groups, or academic institutions from building stronger or faster protections — or customizing oversight to their local populations — this becomes knowledge bottlenecking.
And the data makes one thing obvious: Congress is not moving faster than AI risks, and it is certainly not moving faster than state innovation.
A 10-year federal moratorium means:
- No new state safeguards against generative malware misuse
- No new algorithm bias accountability systems
- No consumer alert standards for AI impersonation fraud
- No regulatory evolution reflecting community priorities
- No structured local risk monitoring frameworks shaping the next generation of AI research responsibly
It forces students, ethicists, researchers, and startups to operate inside a vacuum where the only AI regulations permitted are those that "remove impediments to deployment" — not impediments to harm.
Let’s say it plainly: Deregulation for corporations is not the same thing as freedom for learners.
America needs AI governance. But the governance must be positioned correctly.
Three principles must guide AI legislation going forward:
- Federal baseline safety standards must act as guardrails — not gatekeepers
- States must retain the power to strengthen or specialize protections
- AI research must continue un-frozen, un-filtered, and un-politicized
This leads to the policy stance that matters most in 2025 and beyond:
*“AI safety rules should have a federal floor, not a federal ceiling. Let states protect communities without freezing innovation for a decade.”
If we care about advancing AI safely without slowing research, then we must welcome state participation, not silence it. The loudest voices shaping AI policy must be engineers, researchers, educators, and ethicists crafting solutions based on evidence and harm reduction — not politicians using AI legislation as a roundabout way to throttle what future generations can study or build.
The world is watching how America governs AI. If we legislate in a way that protects people but leaves room for ambitious experimentation, we set a global standard for responsible AI leadership. If we legislate in a way that immobilizes states and local innovators, we set a legacy of stagnation, vulnerability, and diminished public trust.
The choice is ours. The time is now. And the priority is clear: protect the public, empower the states, and never freeze the future of research.