AIREP: A Protocol for Per-Decision Evidence in AI Runtime Governance
arXiv:2608.21363v1 Announce Type: new Abstract: A protocol is presented for recording the governance decisions of automated AI runtimes. When a runtime releases, blocks, defers, redacts, or escalates an individual output, AIREP records that decision as a single signed object that any party can check offline, independent of the runtime that produced it. A record carries the decision as one of a closed set of verbs under a stated policy basis, references its input, output, and evidence by hash rather than by value, and declares both what its evidence covers and what it does not. Records form a SHA-256 hash chain that binds each record to its position, so that tampering and gaps are detectable by recomputation. Vendor-, model-, and domain-specific content is confined to a single optional namespace, and a mechanical neutrality test keeps the shared format free of it. A reference implementation and a two-language conformance kit are described. Some implementation issues are considered, and problems such as alignment of the canonical form across implementations, freshness witnesses, and multi-runtime chains are exposed. The format is offered for adoption by any AI runtime that records governance decisions.
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[Submitted on 31 May 2026]
Title:AIREP: A Protocol for Per-Decision Evidence in AI Runtime Governance
View a PDF of the paper titled AIREP: A Protocol for Per-Decision Evidence in AI Runtime Governance, by Ali Toygar Abak
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Abstract:A protocol is presented for recording the governance decisions of automated AI runtimes. When a runtime releases, blocks, defers, redacts, or escalates an individual output, AIREP records that decision as a single signed object that any party can check offline, independent of the runtime that produced it. A record carries the decision as one of a closed set of verbs under a stated policy basis, references its input, output, and evidence by hash rather than by value, and declares both what its evidence covers and what it does not. Records form a SHA-256 hash chain that binds each record to its position, so that tampering and gaps are detectable by recomputation. Vendor-, model-, and domain-specific content is confined to a single optional namespace, and a mechanical neutrality test keeps the shared format free of it. A reference implementation and a two-language conformance kit are described. Some implementation issues are considered, and problems such as alignment of the canonical form across implementations, freshness witnesses, and multi-runtime chains are exposed. The format is offered for adoption by any AI runtime that records governance decisions.
Comments: 8 pages. Reference implementation and two-verifier conformance kit: this https URL
Subjects:
Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
Cite as: arXiv:2608.21363 [cs.AI]
(or arXiv:2608.21363v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2608.21363
arXiv-issued DOI via DataCite
Submission history
From: Ali Toygar Abak [view email] [v1] Sun, 31 May 2026 18:24:59 UTC (16 KB)
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