How Human-Centered Explainable AI Interface Are Designed and Evaluated: A Systematic Survey
March 21, 2024 Β· Declared Dead Β· π arXiv.org
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Authors
Thu Nguyen, Alessandro Canossa, Jichen Zhu
arXiv ID
2403.14496
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
11
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Despite its technological breakthroughs, eXplainable Artificial Intelligence (XAI) research has limited success in producing the {\em effective explanations} needed by users. In order to improve XAI systems' usability, practical interpretability, and efficacy for real users, the emerging area of {\em Explainable Interfaces} (EIs) focuses on the user interface and user experience design aspects of XAI. This paper presents a systematic survey of 53 publications to identify current trends in human-XAI interaction and promising directions for EI design and development. This is among the first systematic survey of EI research.
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