信任的藍圖：AI系統卡片實現端到端透明度與治理

摘要

本文介紹了危險感知系統卡片（Hazard-Aware System Card, HASC），這是一個旨在提升人工智慧系統開發與部署透明度和問責性的新穎框架。HASC 基於現有的模型卡片和系統卡片概念，整合了人工智慧系統安全性和安全態勢的全面動態記錄。該框架提出了一套標準化的識別符系統，包括新穎的人工智慧安全危險（AI Safety Hazard, ASH）ID，以補充現有的安全識別符（如 CVEs），從而實現對已修復缺陷的清晰且一致的溝通。通過提供一個單一且易於訪問的真相來源，HASC 使開發者和利益相關者能夠在人工智慧系統的整個生命週期中做出更明智的安全決策。最後，我們還將我們提出的人工智慧系統卡片與 ISO/IEC 42001:2023 標準進行了比較，並討論了它們如何相互補充，為人工智慧系統提供更大的透明度和問責性。

English

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.

信任的藍圖：AI系統卡片實現端到端透明度與治理

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

摘要

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