Despite recent efforts by the Artificial Intelligence (AI) community to move towards standardised procedures for documenting models, methods, systems or datasets, there is currently no methodology focused on use cases aligned with the risk-based approach of the European AI Act (AI Act). In this paper, we propose a new framework for the documentation of use cases, that we call "use case cards", based on the use case modelling included in the Unified Markup Language (UML) standard. Unlike other documentation methodologies, we focus on the intended purpose and operational use of an AI system. It consists of two main parts. Firstly, a UML-based template, tailored to allow implicitly assessing the risk level of the AI system and defining relevant requirements. Secondly, a supporting UML diagram designed to provide information about the system-user interactions and relationships. The proposed framework is the result of a co-design process involving a relevant team of EU policy experts and scientists. We have validated our proposal with 11 experts with different backgrounds and a reasonable knowledge of the AI Act as a prerequisite. We provide the 5 "use case cards" used in the co-design and validation process. "Use case cards" allows framing and contextualising use cases in an effective way, and we hope this methodology can be a useful tool for policy makers and providers for documenting use cases, assessing the risk level, adapting the different requirements and building a catalogue of existing usages of AI.

翻译：尽管人工智能（AI）领域近期致力于推动模型、方法、系统或数据集的标准化文档流程，但目前仍缺乏一种与《欧洲人工智能法案》（AI Act）基于风险的方针相一致的用例方法论。本文提出了一种新的用例文档框架，即"用例卡片"，该框架基于统一建模语言（UML）标准中的用例建模。与其他文档方法论不同，我们聚焦于AI系统的预期目的和操作用途。该框架包含两个主要部分：首先，一个基于UML的模板，用于隐式评估AI系统的风险等级并定义相关要求；其次，一个辅助性UML图，用于提供系统与用户交互及关系的相关信息。该框架是由欧盟政策专家和科学家团队共同设计的成果。我们已通过11位具有不同背景且对《AI法案》有合理了解的专家对提案进行了验证。同时提供了在共同设计和验证过程中使用的5份"用例卡片"。"用例卡片"能够有效界定和情境化用例，我们希望该方法论能成为政策制定者和提供者记录用例、评估风险等级、适配不同要求以及构建现有AI应用目录的有用工具。