K. J. Klingshirn, C. Garth, and A. Ebert. XAI Beyond Reality: Identifying Key Research Gaps and Future Directions. In Engineering Interactive Computer Systems. EICS 2025 International Workshops, Cham, 2026, pp. 167–184.
10.1007/978-3-032-26051-2_13
@inproceedings{10.1007/978-3-032-26051-2_13,
author = {Klingshirn, Kai Jonas and Garth, Christoph and Ebert, Achim},
editor = {Fayollas, Camille and Van Gorp, Pieter and Baghdadi, Mahmoud and Ebert, Achim and Hu, Jun and Humayoun, Shah Rukh and Jaidka, Sapna and Luyten, Kris and Mentler, Tilo and Palanque, Philippe and Parvin, Parvaneh and Spano, Lucio Davide and Stumpf, Simone and van der Veer, Gerrit and Zaina, Luciana and Ziegler, J{\"u}rgen},
title = {XAI Beyond Reality: Identifying Key Research Gaps and Future Directions},
booktitle = {Engineering Interactive Computer Systems. EICS 2025 International Workshops},
year = {2026},
publisher = {Springer Nature Switzerland},
address = {Cham},
pages = {167--184},
isbn = {978-3-032-26051-2},
doi = {10.1007/978-3-032-26051-2_13}
}
Abstract: Artificial Intelligence (AI) is increasingly being integrated into a wide array of Extended Reality (XR) applications, including sophisticated navigation systems, immersive training simulations for educational use-cases and data analysis in medicine, e.g. for MRI scans. Consequently, ensuring the transparency and interpretability of these AI-driven applications has become a major challenge. This paper examines the growing importance of Explainable AI (XAI) in Extended Reality environments and identifies key challenges in developing effective explanation systems. We analyze how these AI-powered XR applications particularly benefit from transparent explanations that build trust, enhance user understanding and improve overall adoption. After summarizing the general challenges in the field of XAI, we investigate how these challenges manifest in the specific context of XR. By synthesizing current research and identifying critical open questions, this work aims to guide future XAI development towards more transparent, trustworthy systems that prioritize human needs across XR applications and beyond.