Blueprints of Trust: AI System Cards for End to End Transparency and Governance

Fuente: arXiv
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Main Authors: Sidhpurwala, Huzaifa, Fox, Emily, Mollett, Garth, Gabarda, Florencio Cano, Zhukov, Roman
Format: Preprint
Published: 2025
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author Sidhpurwala, Huzaifa
Fox, Emily
Mollett, Garth
Gabarda, Florencio Cano
Zhukov, Roman
author_facet Sidhpurwala, Huzaifa
Fox, Emily
Mollett, Garth
Gabarda, Florencio Cano
Zhukov, Roman
contents This paper introduces the Hazard-Aware System Card (HASC), a novel framework designed to enhance transparency and accountability in the development and deployment of AI systems. The HASC builds upon existing model card and system card concepts by integrating a comprehensive, dynamic record of an AI system's security and safety posture. The framework proposes a standardized system of identifiers, including a novel AI Safety Hazard (ASH) ID, to complement existing security identifiers like CVEs, allowing for clear and consistent communication of fixed flaws. By providing a single, accessible source of truth, the HASC empowers developers and stakeholders to make more informed decisions about AI system safety throughout its lifecycle. Ultimately, we also compare our proposed AI system cards with the ISO/IEC 42001:2023 standard and discuss how they can be used to complement each other, providing greater transparency and accountability for AI systems.
format Preprint
id arxiv_https___arxiv_org_abs_2509_20394
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Blueprints of Trust: AI System Cards for End to End Transparency and Governance
Sidhpurwala, Huzaifa
Fox, Emily
Mollett, Garth
Gabarda, Florencio Cano
Zhukov, Roman
Computers and Society
Artificial Intelligence
Computation and Language
Cryptography and Security
This paper introduces the Hazard-Aware System Card (HASC), a novel framework designed to enhance transparency and accountability in the development and deployment of AI systems. The HASC builds upon existing model card and system card concepts by integrating a comprehensive, dynamic record of an AI system's security and safety posture. The framework proposes a standardized system of identifiers, including a novel AI Safety Hazard (ASH) ID, to complement existing security identifiers like CVEs, allowing for clear and consistent communication of fixed flaws. By providing a single, accessible source of truth, the HASC empowers developers and stakeholders to make more informed decisions about AI system safety throughout its lifecycle. Ultimately, we also compare our proposed AI system cards with the ISO/IEC 42001:2023 standard and discuss how they can be used to complement each other, providing greater transparency and accountability for AI systems.
title Blueprints of Trust: AI System Cards for End to End Transparency and Governance
topic Computers and Society
Artificial Intelligence
Computation and Language
Cryptography and Security
url https://arxiv.org/abs/2509.20394