IHM '26 - Explainable AI for End Users

IHM '26 — Explainable AI for End Users, held in Lille, France, is a focused workshop at the intersection of human-computer interaction and explainable artificial intelligence, organized in conjunction with the French-speaking IHM (Interaction Homme-Machine) conference. The workshop examines how AI explanations can be designed, evaluated, and communicated to non-expert end users — the people who interact daily with AI-driven products without specialist knowledge of machine learning. As regulations such as the EU AI Act mandate transparency and explainability in high-risk AI systems, understanding how end users perceive, trust, and act on AI explanations becomes critical. The workshop fosters dialogue between XAI researchers and HCI specialists to develop user-centered explanation design guidelines.

IHM '26 - Explainable AI for End Users invites submissions on the design, evaluation, and user experience of AI explanation systems. Topics of interest include: user-centered design of AI explanations; cognitive models of explanation comprehension; trust and reliance calibration through explanations; explanation interfaces for conversational AI and recommendation systems; evaluation methodologies for explainability (user studies, crowdsourcing); domain-specific explainability in healthcare, finance, and justice; regulatory compliance and explainability requirements; contrastive and counterfactual explanations for lay users; accessibility of AI explanations; and cross-cultural perspectives on AI transparency. Papers in French or English are welcome.