Use case cards: a use case reporting framework inspired by the European AI Act

• Published in: Ethics and information technology Vol. 26; no. 2; p. 19
• Main Authors: Hupont, Isabelle, Fernández-Llorca, David, Baldassarri, Sandra, Gómez, Emilia
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2024; Springer Nature B.V
• Subjects: Artificial intelligence; Cards; Co-design; Computer Science; Documentation; Ethics; Innovation/Technology Management; Library Science; Management of Computing and Information Systems; Original Paper; Risk assessment; Risk levels; User Interfaces and Human Computer Interaction; AI policies; Transparency; Use case modelling; Trustworthy AI; Risk assessment; Documentation
• ISSN: 1388-1957; 1572-8439
• DOI: 10.1007/s10676-024-09757-7

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, and 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.