Glossary as a Compass: Domain Knowledge Artifacts in Human-Centered AI Development
Open Access
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Conference Proceedings
Authors: Felipe França, Eduardo Oliveira, Emilio Coutinho, Leonardo Neri, Hugo Silva, Luciana Franci, Virgínia Ribeiro
Abstract: The development of Artificial Intelligence systems in complex environments faces a persistent challenge: translating users’ natural language, rich in context, specialized terms, and cultural nuances, into formal structures that inform interface design and algorithmic logic. A promising approach to this challenge is the collaborative construction of knowledge artifacts such as technical glossaries, which serve as semantic mediation tools between multidisciplinary teams and technology. More than simple collections of definitions, these glossaries act as methodological compasses guiding human-centered AI projects and exposing gaps that drive improvement. This paper reports a case in which a collaborative glossary was developed during user immersion and adopted as a guiding artifact for AI design and engineering through participatory sessions involving domain experts, designers, software engineers, and data scientists. The resulting living document defined technical and operational terms while translating everyday practices, metaphors, and user needs; it also mapped synonyms, terminological variations, and contexts of use to align ambiguous expressions with real intentions. The glossary served as a semantic bridge linking natural language to computational representations, as a shared reference that reduced ambiguities and accelerated design decisions, and as support for integration with large language models. By centering the glossary, teams aligned expectations, improved usability, and ensured algorithms reflected business rules and field practices, demonstrating glossaries as strategic artifacts that enhance explainability, trust, and interdisciplinary collaboration in human-centered AI.
Keywords: human-centered AI, knowledge management, domain ontologies
DOI: 10.54941/ahfe1007164
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