The Council of AI has published an IETF experimental draft defining 'measurement capsules,' a JSON-based format for recording discrepancies between declared and observed data in SCITT-based supply chains. This protocol facilitates independent, authority-free verification of claims within streaming and software supply chain ecosystems.
The introduction of independent measurement capsules addresses a critical gap in streaming supply chain transparency by separating third-party observations from actor-issued receipts. By providing a standardized way to record when a platform's live protocol exchange differs from its public registry, the Council of AI offers a mechanism for verifying technical compliance without centralized authority. This shift toward deterministic, append-only logs could reduce reliance on self-reported vendor data for critical infrastructure components. Industry observers should watch for the first successful registration of a capsule batch with an external SCITT Transparency Service to validate cross-party interoperability.
The Council of AI has published an IETF experimental draft for the SCITT measurement capsule, a JSON-based format for recording discrepancies between declared and observed data. This protocol allows for independent verification of supply chain claims without requiring subject participation, potentially reducing reliance on self-reported vendor data for critical infrastructure.
It is a JSON-based format defined by the Council of AI that records discrepancies between declared and observed data, allowing for independent verification of claims within supply chain ecosystems.
Measurement capsules are identified by SHA-256 digests and are batched under RFC 9162 Merkle Tree Hashes to ensure membership integrity.
No, the protocol includes a strict denylist that forbids 22 specific terms, such as 'approve' or 'permit,' to prevent the capsules from functioning as automated gates or authorization tools.
The 'UNCHECKABLE' outcome is a first-class state defined within the deterministic JSON record to handle specific measurement scenarios.
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