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Haccp for AI: An Auditable Self-Control Standard for Artificial Intelligence

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#ai governance#risk management#standards#haccp
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The paper proposes adapting the Hazard Analysis and Critical Control Points (HACCP) framework to provide a process‑control layer for AI governance. Version 4.0 shifts the unit of governance to the organization’s own plan, introduces a three‑tier structure and distinguishes critical, operational, and indicator limits. It supplies a twelve‑step codex, hazard taxonomy, control‑point catalogue, and mappings to ISO/IEC 42001, the EU AI Act, and the NIST framework while noting a metrological gap in capability evaluation.

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Original publisherZenodo
Canonical URLhttps://zenodo.org/records/21710254
Publication timeFri, 31 Jul 2026 10:17:12 +0000
Retrieval time2026-07-31T10:22:38.414Z
Last seen2026-07-31T10:22:38.414Z
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Published July 30, 2026 | Version 4.0 Working paper Open HACCP for AI: An Auditable Self-Control Standard for Artificial Intelligence Authors/Creators Paciaroni, Simone1 Show affiliations 1. AXIX® / HACCP.ai Description Almost every serious instrument in AI governance now requires an organisation to run a risk process. None of them tells the organisation where in its own lifecycle the control points sit, what measurable limit applies at each one, what happens automatically when a limit is breached, or who is competent to verify the measurement. That layer — process control — is missing, and it is the layer on which everything else depends. A management system without control points produces documentation; it does not produce safety.

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