On August 3 the White House announced that it had met the deadline set by the June 2 executive order Promoting Advanced Artificial Intelligence Innovation and Security, which required a framework for reviewing the most capable AI models before release. It had been discussed with Meta, Nvidia, Microsoft, OpenAI, Anthropic and smaller developers. Officials declined to say what it contains, who has seen it, or when companies will begin using it.
The day before, the European Union’s AI Act took effect, giving the European Commission authority to demand review of advanced models before release, with penalties reaching seven percent of worldwide annual revenue. Two answers to the same problem arrived within twenty-four hours. One is binding and published. The other is voluntary and undisclosed.
Pre-deployment review is a genuine advance, and the American framework has a defensible reason for confidentiality: its concern is national security, and capability thresholds tied to cyber risk cannot be published without telling adversaries where the lines fall. But a reason for withholding is not an answer to the question the withholding creates. When the criteria are classified, the reviewers internal, and the results unpublished, no citizen can distinguish a rigorous process from a nominal one — and neither can a legislator, an allied government, or a company wondering whether its competitors were held to the same standard. Nor is a legislative remedy near: the bipartisan framework that would have required independent audits of frontier developers remains stalled over state preemption.
The government has not done something wrong. It simply cannot, by itself, produce what this situation most needs — a standard the public can check. That is the institutional problem examined in Beacon Papers No. 4 — Who May Verify?
An Independent Layer of Trust Verification
BGF–AIWS proposes that the AIWS Trust Order Board, working with AI pioneers, scientists and legal scholars, develop an independent mechanism to sit alongside government-led review. This is not a challenge to public authority but a complement to it: the mechanism should not replace the legitimate authority of the United States Government, nor seek information that must remain classified. Its value lies precisely in what the government, for legitimate reasons, cannot supply — verification that is itself open to inspection.
Supported by the AIWS Trust Infrastructure, the Board could verify selected trust and safety claims, assess systems against published AIWS Trust Standards, examine Human-in-Command safeguards including override and emergency intervention, and issue public attestations that provide real accountability without disclosing sensitive information.
Government determines whether a deployment satisfies public authority. Independent trust institutions determine whether the safeguards surrounding it deserve public confidence. Neither substitutes for the other.
A Frontier AI Trust Review Pilot
BGF–AIWS proposes exploring a Frontier AI Trust Review Pilot with U.S. institutions, frontier AI laboratories and universities. It would not duplicate the government’s evaluation, but begin with questions an outside party can answer. Does a frontier system have effective Human-in-Command mechanisms? Are critical safety claims supported by examinable evidence? Are serious incidents reported? Are deployment decisions traceable to accountable human authorities?
Such a pilot would demonstrate the principle AIWS Trust Infrastructure exists to advance: trust must be demonstrated, not merely declared.
As governments build mechanisms to review increasingly powerful AI, the next institutional question arrives with them: who verifies the verifiers? The answer cannot be that society should simply trust them. In the AI Age, those who verify powerful AI must themselves be verifiable.
