Documenting use cases in the affective computing domain using Unified Modeling Language
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Abstract (arXiv)
The study of the ethical impact of AI and the design of trustworthy systems needs the analysis of the scenarios where AI systems are used, which is related to the software engineering concept of "use case" and the "intended purpose" legal term. However, there is no standard methodology for use case documentation covering the context of use, scope, functional requirements and risks of an AI system. In this work, we propose a novel documentation methodology for AI use cases, with a special focus on the affective computing domain. Our approach builds upon an assessment of use case information needs documented in the research literature and the recently proposed European regulatory framework for AI. From this assessment, we adopt and adapt the Unified Modeling Language (UML), which has been used in the last two decades mostly by software engineers. Each use case is then represented by an UML diagram and a structured table, and we provide a set of examples illustrating its application to several affective computing scenarios.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 39 references that are in the map. First posted on arXiv 19 Sep 2022.
Builds on
9 of 39 references.
References · 9
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- 2019Affective Computing for Large-Scale Heterogeneous Multimedia Data: A Surveycited by 17
- 2021AffectiveSpotlight: Facilitating the Communication of Affective Responses from Audience Members during Online Presentationscited by 7
- 2021An Ethical Framework for Guiding the Development of Affectively-Aware Artificial Intelligencecited by 4
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