mlsanityData to 7 Oct 2026

Operational Identity: A Finite Audit of Declared and Implemented Rules of Sameness

arXiv 2607.20729 ↗First posted 22 Jul 2026cs.LO cs.AIcited by 0

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Abstract (arXiv)

A record system declares when two records refer to the same entity, occurrence, scope, or rule. Its disclosed implementation mechanisms induce a corresponding operational identity relation. The declared and implemented relations may diverge systematically without producing a provenance gap or detectable contradiction. A system can apply, consistently and with every record individually correct, a rule of sameness that no artifact declares. This paper formalizes that implemented relation. A declared identity regime partitions a finite record domain into co-reference classes; a disclosed mechanism, through its typed identity-relevant outcomes, induces an operational identity partition of the same domain. The audit compares these partitions in the refinement lattice. A mechanism is faithful when the declared partition refines the operational partition, so no declared class is split. A divergence witness is a pair the declaration merges and the mechanism separates; such witnesses are decidable by pair enumeration. When an imported sibling basis also splits a declared class, local comparison with its partition yields sibling-aligned, sub-sibling, super-sibling, or sibling-incomparable divergence. This result reports only the relationship; it does not identify the basis carried by the mechanism. Global equality of the operational and sibling partitions is defined separately as regime substitution and does not follow from sibling alignment. A version field incremented on every textual edit inhabits the sub-sibling case by splitting declared classes more finely than either imported basis. The audit is three-valued and relative to the disclosed artifacts, evaluated surfaces, and identified uses; each boundary has a finite refuting witness. A passing verdict is non-monotone because extending the transformation history can merge declared classes and create a witness among records already examined.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 38 references that are in the map. First posted on arXiv 22 Jul 2026.

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References · 13

  1. 2025PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflowscited by 29
  2. 2026The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systemscited by 27
  3. 2026Auditable Agentscited by 14
  4. 2026Audit Trails for Accountability in Large Language Modelscited by 10
  5. 2025A Trustworthiness-based Metaphysics of Artificial Intelligence Systemscited by 6
  6. 2026AI Identity: Standards, Gaps, and Research Directions for AI Agentscited by 5
  7. 2026High-Risk AI Systems and the Problem of Identity in the European AI Actcited by 4
  8. 2026Responsible Agentic AI Requires Explicit Provenancecited by 3
  9. 2026A Category Theory Account of AI Identitycited by 2
  10. 2026Neutral Substrates: A Design Constraint for Shared Records Under Persistent Interpretive Disagreementcited by 1
  11. 2026Referential Regimes: Transformation-Invariant Identity for Neutral Substratescited by 1
  12. 2026Superintelligence and Lawcited by 1
1 more
  1. 2026ECO/CPO-DAG: A Contradiction-Based Accountability Layer for Adversarial Supply Chainscited by 1

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