Teaching Requirements Engineering for Human-Centered AI: A Classroom Experience with the RE4HCAI Framework - Santos, Bruna; Lima, Márcia; Ribeiro, Márcio; Conte, Tayana (Anais do Simpósio Brasileiro de Qualidade de Software (SBQS); 2025: Anais do XXIV Simpósio Brasileiro de Qualidade de Software, 2025)
Requirements Engineering for AI-based systems (RE4AI) demands approaches that integrate technical, social, and human-centered dimensions. For instance, when eliciting requirements for AI systems, one must account for data biases and imbalances that may lead to decisions reinforcing stereotypes and excluding certain user profiles without making such effects visible. Despite the topic’s relevance, teaching RE4AI remains nascent and lacks suitable pedagogical methods. To address this gap, this study examines the use of the RE4HCAI framework as a pedagogical aid for teaching requirements elicitation in AI systems, attending to technical, human, and social dimensions. We conducted a classroom activity with 86 students, applying the framework and collecting perceptions of its usefulness. Among participants, 66% reported that using the RE4HCAI framework fostered reflection on themes such as responsibility, bias, and explainability. Despite its formative potential, students noted challenges related to linguistic complexity, the need for prior knowledge, and the clarity of instructions. This work offers preliminary empirical indications and provides structured materials that can support instructors in teaching RE4AI.