为通用人工智能模型提供风险管控标准，防范潜在重大危害。
AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models
- 基于NIST和ISO框架，针对通用大模型设计专用风险管控流程。
- 聚焦模型开发中的高风险场景，提出可操作的风险识别与缓解策略。
- 适合大模型开发者及依赖其应用的下游团队参考使用。
日益多用途的人工智能模型，如前沿大型语言模型或其他‘通用人工智能’（GPAI）模型、基础模型、生成式AI模型及‘前沿模型’（本文统称为GPAI/基础模型，必要时区分），虽具广泛有益能力，但也可能引发后果严重的不良事件。本文提供GPAI/基础模型的风险管理实践或控制措施，用于识别、分析和缓解相关风险。主要面向大规模、最先进GPAI/基础模型的开发者；也可为基于此类模型构建终端应用的下游开发者提供参考。本文件旨在促进符合或采用领先的AI风险管理标准，基于NIST AI风险管理框架和ISO/IEC 23894的通用自愿指南，重点应对GPAI/基础模型开发者面临的独特挑战。
原文摘要 · Abstract (English)
Increasingly multi-purpose AI models, such as cutting-edge large language models or other 'general-purpose AI' (GPAI) models, 'foundation models,' generative AI models, and 'frontier models' (typically all referred to hereafter with the umbrella term 'GPAI/foundation models' except where greater specificity is needed), can provide many beneficial capabilities but also risks of adverse events with profound consequences. This document provides risk-management practices or controls for identifying, analyzing, and mitigating risks of GPAI/foundation models. We intend this document primarily for developers of large-scale, state-of-the-art GPAI/foundation models; others that can benefit from this guidance include downstream developers of end-use applications that build on a GPAI/foundation model. This document facilitates conformity with or use of leading AI risk management-related standards, adapting and building on the generic voluntary guidance in the NIST AI Risk Management Framework and ISO/IEC 23894, with a focus on the unique issues faced by developers of GPAI/foundation models.
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