深入探讨
The AI RMF 1.0 organizes risk-management activities into Govern, Map, Measure and Manage. Govern is cross-cutting; Map establishes context and identifies risks; Measure analyzes risks; Manage prioritizes and responds to them. NIST describes the framework as voluntary. NIST’s AI RMF Playbook provides suggested actions, and the 2024 Generative AI Profile applies the framework to generative-AI risks such as confabulation. These resources are guidance, not legal requirements or certifications.
现实世界的实施
An organization can use Govern to assign responsibilities and policies for AI risk management.
A project team can use Map to document its context, intended use and affected stakeholders.
A team can use Measure to evaluate identified risks with appropriate qualitative and quantitative methods.
A team can use Manage to prioritize responses and monitor residual risks.
NIST 人工智能风险管理框架的未来
Organizations may choose to use the AI RMF as one input to their own governance and risk-management processes. NIST may publish additional profiles, but adoption and crosswalks depend on the organization and applicable requirements. Check current NIST publications rather than assuming the framework is becoming a universal procurement or compliance baseline.
付诸实践
为什么这很重要
- 风险与安全. 灾难性和日常的人工智能危害都取决于谁了解风险以及谁能够采取行动。
- 更清晰的判决. 公众和专业素养决定强有力的安全政策在政治上是否可行。
- 打破炒作. 清晰的解释可以减少炒作、实验室公关和模糊道德剧场的影响。
留意
- 将存在风险视为科幻小说，同时能力复合。
- 混淆了表面产品安全与高度自治下的对准。
- 只给非英语和非专业观众留下低质量的资源。
后续步骤
- 单独的产品危害、误用和失控/失调风险。
- 询问哪些证据会改变您对时间表和严重性的看法。
- 比起营销主张，更喜欢主要来源和具体评估。
- 确定一条行动路径：职业、政策、资金或技能——而不仅仅是意识。
不断探索
常见问题
What is NIST AI Risk Management Framework?
NIST’s AI Risk Management Framework (AI RMF 1.0) is a voluntary, cross-sector framework for managing risks to individuals, organizations and society across AI design, development, deployment and use.
NIST AI RMF 的四大核心功能是什么？
该框架围绕治理、地图、测量和管理构建，其中治理作为横切功能，为其他功能提供支持。
法律是否要求遵守 NIST AI RMF？
AI RMF 是明确自愿的且与部门无关，提供指导而不是可执行的命令。
哪个功能被描述为交叉并融入其他三个功能？
治理建立支撑规划、衡量和管理的文化、政策和问责结构。
为什么 RMF 将可信度视为一组权衡？
一项特征（如准确性）的收益可能会以牺牲另一种特征（如隐私或公平性）为代价，因此必须平衡它们。
NIST 在 2024 年向框架添加了哪些内容来解决大型语言模型问题？
2024 年生成式人工智能配置文件解决了法学硕士特有的风险，例如虚构、数据泄露和有害内容。