Designing for Effective Human-XAI Interaction: User Experience Research Plays and Cards
Authors: Naiseh, M., Dogan, H., Giff, S., Malhi, A., Jiang, N.
Journal: Lecture Notes in Computer Science
Volume: 15936 LNCS
eISSN: 1611-3349
ISSN: 0302-9743
DOI: 10.1007/978-3-032-01399-6_13
Abstract:Explainable Artificial Intelligence (XAI) has emerged as a critical field for fostering trust, transparency, and comprehension in human-AI interactions. However, existing XAI systems often fall short of addressing real-world usability challenges, resulting in suboptimal adoption and engagement. This paper applies the User Experience Research Point of View (UXR PoV) playbook to Human-XAI interactions as a case study, i.e., a structured framework designed to guide multidisciplinary teams in creating effective human-centered XAI systems. The playbook consists of actionable play cards, organised into three dimensions: Usability Enhancement, Human-Like Enhancement, and Learning Enhancement. Our proposed Human-XAI plays and cards aim to improve the usability and long-term impact of XAI systems by leveraging iterative design principles, interdisciplinary collaboration, and evidence-based practices.
https://eprints.bournemouth.ac.uk/41103/
Source: Scopus
Designing for Effective Human-XAI Inter-action: User Experience Research Plays and Cards
Authors: Naiseh, M., Dogan, H., Giff, S., Malhi, A., Jiang, N.
Conference: Explainable, Trustworthy, and Responsible AI and Multi-Agent Systems (EXTRAAMAS 2025)
Dates: 19/05/2025
https://eprints.bournemouth.ac.uk/41103/
Source: Manual