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Engram Provenance: Substrate-Rooted Provenance for Safety-Critical AI Systems
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This paper introduces Engram Provenance, a substrate-rooted provenance model for AI systems. Building on the Engram Layer and the Engram Signature, provenance is defined as continuity of execution-realized identity across time, perturbation, and substrate variation. Engram Provenance formalizes lineage as a sequence of stable Engram Signatures and provides minimal conditions for auditability, chain-of-custody, and substrate-rooted trust in safety-critical domains.
Title: Engram Provenance: Substrate-Rooted Provenance for Safety-Critical AI Systems
Description:
This paper introduces Engram Provenance, a substrate-rooted provenance model for AI systems.
Building on the Engram Layer and the Engram Signature, provenance is defined as continuity of execution-realized identity across time, perturbation, and substrate variation.
Engram Provenance formalizes lineage as a sequence of stable Engram Signatures and provides minimal conditions for auditability, chain-of-custody, and substrate-rooted trust in safety-critical domains.
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