133404 20260217205510.0 doi 10.1007/s10676-024-09757-7 sideral 138079 ART-2024-138079 eng Hupont, Isabelle Use case cards: a use case reporting framework inspired by the European AI Act 2024 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/DGA/T60-23R info:eu-repo/grantAgreement/ES/MICINN/PID2022-136779OB-C31 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 4.0 2024 ETHICS 6 / 77 = 0.078 2024 Q1 T1 INFORMATION SCIENCE & LIBRARY SCIENCE 28 / 166 = 0.169 2024 Q1 T1 1.107 2024 Library and Information Sciences 2024 Q1 Computer Science Applications 2024 Q1 9.9 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Fernández-Llorca, David Baldassarri, Sandra Universidad de Zaragoza (orcid)0000-0002-9315-6391 Gómez, Emilia 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 26, 19 (2024), [23 pp.] ETHICS AND INFORMATION TECHNOLOGY ETHICS AND INFORMATION TECHNOLOGY 1388-1957 10106527 http://zaguan.unizar.es/record/133404/files/texto_completo.pdf Versión publicada 2259526 http://zaguan.unizar.es/record/133404/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:133404 articulos driver 2026-02-17-20:24:55 ARTICLE