Forging the next generation of resilient, trustful, and explainable XR assistance.
Submit a Position PaperExtended Reality (XR) combined with Artificial Intelligence (AI) has the potential to revolutionize how professionals operate in Challenging Environments (CEs), ranging from emergency response and firefighting to advanced industrial manufacturing. These are contexts defined by a confluence of complexity, risk, and unpredictability that pushes human decision-making to its limits.
However, current research often fails to address the unique demands of embodied, mission-critical work. When stakes are high, systems cannot just be "seamless"—they must be resilient. We argue for three crucial shifts in perspective to bridge this gap:
Moving beyond static trust to dynamic models that help professionals appropriately gauge reliance in real-time under duress.
Rejecting brittle perfection in favor of systems that fail gracefully, ensuring the human remains the ultimate authority during breakdowns.
Replacing complex text explanations with glanceable, embodied cues integrated directly into the physical workspace.
We invite researchers, practitioners, and domain experts to join us in building a cross-disciplinary community. Our goal is to identify key problems and co-create a shared research agenda for the next generation of mission-critical XR. This long-format, in-person workshop will focus on bridging the gap between foundational principles and domain-specific issues in embodied, mission-critical work.
We welcome submissions that address the three proposed shifts (Trust, Resilience, Explainability) or other relevant themes, including but not limited to:
We solicit 2–4 page position papers (excluding references). Submissions may present novel concepts, empirical findings, design provocations, or case studies.
Format: ACM Master Article Submission Template (Single Column).
Review Process: All submissions will be peer-reviewed by the organizers based on quality, relevance, and their potential to stimulate discussion.
Publication: With author consent, accepted papers will be published as open-access proceedings on platforms such as arXiv or CEUR-WS.
Note: At least one author of each accepted submission must register for and attend the workshop in person to present their work.