为AI系统使用安全提供风险识别与应对建议的治理助手
Usage Governance Advisor: From Intent to AI Governance
- 构建半结构化治理信息，整合多源数据评估安全风险
- 根据使用场景优先级识别风险，推荐适配的评估基准
- 不仅预警还给出具体缓解策略，适合企业部署AI时参考
评估AI系统的安全性是组织部署其应用时的紧迫问题。除了系统缺乏公平性带来的社会损害外，部署方还担忧法律后果和声誉损失。安全性涵盖模型的行为（如能否从训练数据中泄露个人信息）以及模型构建过程（如是否仅使用授权数据集）。评估安全性需整合来自多种异构来源的信息，包括安全基准和模型技术文档。此外，通过引导用户采取缓解措施，促进负责任的使用。本文提出Usage Governance Advisor，可生成半结构化治理信息，根据预期使用场景识别并优先排序风险，推荐合适的基准测试与风险评估，并关键性地提出缓解策略与行动建议。
原文摘要 · Abstract (English)
Evaluating the safety of AI Systems is a pressing concern for organizations deploying them. In addition to the societal damage done by the lack of fairness of those systems, deployers are concerned about the legal repercussions and the reputational damage incurred by the use of models that are unsafe. Safety covers both what a model does; e.g., can it be used to reveal personal information from its training set, and how a model was built; e.g., was it only trained on licensed data sets. Determining the safety of an AI system requires gathering information from a wide set of heterogeneous sources including safety benchmarks and technical documentation for the set of models used in that system. In addition, responsible use is encouraged through mechanisms that advise and help the user to take mitigating actions where safety risks are detected. We present Usage Governance Advisor which creates semi-structured governance information, identifies and prioritizes risks according to the intended use case, recommends appropriate benchmarks and risk assessments and importantly proposes mitigation strategies and actions.
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