White House AI Order Gets Security Right, but Review Process Needs Guardrails, ICLE Scholar Says
WASHINGTON (June 2, 2026) — The White House’s new executive order on “Promoting Advanced Artificial Intelligence Innovation and Security” takes a more sensible approach to AI security by rejecting mandatory licensing, keeping pre-release engagement voluntary, and emphasizing defensive deployment, International Center for Law & Economics Director of Innovation Policy Kristian Stout said.
But Stout warned that its voluntary review process—built around classified benchmarks and federal determinations—could still become a de facto gatekeeping regime that favors incumbents, slows innovation, or gives future administrations too much leverage over model developers.
“The order gets important things right,” Stout said. “It treats AI as a national-security issue without pretending every model should need a federal permission slip. That is a meaningful improvement over proposals that would turn frontier AI into a licensed industry.”
The order creates a voluntary process for developers of “covered frontier models”—the most capable AI systems at the technological edge—to work with agencies including the National Security Agency, Cybersecurity and Infrastructure Security Agency, National Institute of Standards and Technology, and Treasury Department for up to 30 days before release.
It also directs faster AI adoption across federal systems and critical infrastructure, creates a Treasury-led clearinghouse to help identify and patch cybersecurity vulnerabilities, expressly disclaims any “mandatory governmental licensing, preclearance, or permitting requirement” for new AI models, and directs the attorney general to prioritize AI-enabled cybercrime prosecutions under existing law.
Stout said the order is stronger than approaches that treat “AI” as one undifferentiated policy problem or chips as the only meaningful policy lever.
“Good AI policy focuses on where misuse actually happens: capabilities, access, and deployment at the frontier,” Stout said. “Security will depend on spreading useful capability across firms, infrastructure, and end users—not concentrating it in a few government-blessed intermediaries.”
But Stout cautioned that voluntary systems can harden over time, especially when the standards are classified, technical, or opaque.
“A pre-release review process backed by classified benchmarks and final federal determinations is exactly the sort of thing that can grow teeth later,” Stout said. “A framework designed today to screen for adversary access could tomorrow be used to pressure developers on lawful content, pull them into surveillance beyond statutory limits, or slow the release of defensive tools Americans will need.”
Stout also questioned whether each new frontier-model release creates the kind of sudden cyber-risk leap that would justify case-by-case federal review.
“Frontier models appear to improve incrementally—not in sudden jumps—at finding software vulnerabilities,” Stout said. “If the added cyber-risk from any single release is smaller than the order implies, then the obvious concern is that the review framework creates a bottleneck only the best-capitalized incumbents can navigate.”
Stout pointed to the 1990s Clipper Chip proposal and crypto export-control regime as a cautionary precedent: a security-framed regime can become an incumbent moat and an innovation brake long before anyone admits that is what happened.
For more, see ICLE’s recent work, including Stout’s “A Sensible Federal Framework for AI (If Congress Can Stick to It),” “AI Risk and the Very Large Hammer,” “Stack Wars: The Garage Myth Meets the Five-Layer Cake,” and “Regulating the Tool or the Trouble? A Survey of State AI Bills.”
To request an interview with Kristian, contact Jim Fellinger at [email protected].
About ICLE
The International Center for Law & Economics is a nonprofit, nonpartisan research center working with a roster of more than one hundred academic affiliates and research centers from around the globe. ICLE scholars promote the use of law and economics methodologies to inform public policy debates.