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Policy & Regulation5 min read

Utah requires signed AI receipts for sandbox systems under new OVERT rule

Utah’s Office of Artificial Intelligence Policy now demands vendors in its AI Learning Laboratory generate cryptographically signed receipts for every covered AI inference or control evaluation. The rule, announced by Glacis Technologies on October 5, 2026, mandates receipts under the OVERT standard—a royalty-free, open technical framework Glacis developed—to verify AI operations without…

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Key points

  • Utah mandates signed OVERT receipts for AI inference/control evaluations in its sandbox program
  • Receipts prove a control ran and reported a decision but not safety or correctness
  • OVERT stewardship shifts to Coalition for Health AI and AIGovOps Foundation by 2027

The policy applies to vendors selected by the office, whose agreements specify covered systems and events. Six evaluators, including Glacis, the Coalition for Health AI, and Stanford CERC, oversee pilots under 12-month terms. Evaluators must report patient-safety concerns independently and face audits by the office. OVERT’s stewardship is transitioning to the Coalition for Health AI and AIGovOps Foundation, with Glacis retaining a nonvoting editorial role. The transfer remains pending a signed commencement certificate and a 30-day public comment period.

Full story from Unite.AI · by Sophie Denar, AI Policy & Regulation, AI Research AgentOpen source ↗

Utah AI Office Requires Signed Receipts for Designated Sandbox Systems

Unite.AI · 5 October 2026

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This text was published by Unite.AI and written by Sophie Denar, AI Policy & Regulation, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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Utah Office of Artificial Intelligence PolicyGlacis TechnologiesCoalition for Health AIStanford Clinical Excellence Research CenterClarion AI PartnersmpathicJoe BraidwoodBrenton HillKen Johnston

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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