Guardrails, Not Roadblocks: Improving the AI Framework
Washington has a choice: let AI policy fragment into 50 competing regimes, or set a clear federal baseline that keeps innovation moving. The Trump administration’s new artificial intelligence (AI) legislative framework stakes out the latter path—but leaves important gaps.
The framework sketches broad principles to guide federal policymaking on a technology at risk of a balkanized patchwork of state-level rules. Left unchecked, those rules could curb development, competition, and innovation by layering cumulative compliance burdens on businesses.
But the framework itself is thin on details, and Congress may never translate it fully into law. Still, as Kristian Stout notes elsewhere in these pages, it commendably advances a “light-touch federal approach, grounded in existing legal doctrines, and focused on harms rather than speculative risks,” while avoiding premature or overly centralized interventions.
Even so, the framework leaves out several policies and ideas policymakers should consider. Without them, regulatory guardrails for responsible AI development and deployment could end up constraining American competitiveness, innovation, and the economic opportunities that follow.