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.
@article{arxiv.2403.14496,
title = {How Human-Centered Explainable AI Interface Are Designed and Evaluated: A Systematic Survey},
author = {Thu Nguyen and Alessandro Canossa and Jichen Zhu},
journal= {arXiv preprint arXiv:2403.14496},
year = {2024}
}