This report documents safety assurance argument templates to support the deployment and operation of autonomous systems that include machine learning (ML) components. The document presents example safety argument templates covering: the development of safety requirements, hazard analysis, a safety monitor architecture for an autonomous system including at least one ML element, a component with ML and the adaptation and change of the system over time. The report also presents generic templates for argument defeaters and evidence confidence that can be used to strengthen, review, and adapt the templates as necessary. This report is made available to get feedback on the approach and on the templates. This work was sponsored by the UK Dstl under the R-cloud framework.

翻译：本报告载有安全保障论证模板,用以支持包括机器学习(ML)组成部分在内的自主系统的部署和运行;本文件以安全论证模板为例,涵盖:制定安全要求、危害分析、一个包含至少一个 ML 元素的自主系统安全监测架构、一个包含 ML 元素的组件,以及系统随时间变化和调整;本报告还提供了可用于论证失败者的通用模板和证据信心,以便在必要时加强、审查和调整模板;本报告供查阅,以获得对方法和模板的反馈;这项工作由英国Dstl公司在R-Cloud框架下赞助。