Christopher Katins was part of the organizing team of the International Workshop on Reality Mediation at UbiComp/ISWC 2026 in Shanghai.

Jacques-Maurice Walther joins the team as Researcher and PhD candidate. His research focuses on human-AI interaction and the development of agent-based interfaces.

Barbarella Petz joins the team as Researcher and PhD candidate. Her research focuses on human–AI collaboration and the development of user-friendly AI systems, with an emphasis on applying large language models to detect and debunk disinformation.

As Augmented Reality (AR) applications and their respective virtual components approach photorealism, users are challenged to distinguish physical objects from virtually rendered ones, which can undermine trust in the environment and lead to interaction errors. We address this challenge by introducing three indicators that mark virtual content to support reliable physical-virtual discrimination. Since photorealistic virtual content is still hard to achieve in real-time AR, we induce ambiguity instead by applying a matched Sobel edge-detection stylization to both the passthrough view and the virtual objects. We evaluated the indicators in a user study (N=20) where participants classified objects in an AR environment as either physical or virtual. Our results show that a salient hovering cue significantly improved confidence-weighted classification accuracy over the baseline and the transparency indicator, while it did not differ significantly from an outline. However, misclassifications still occurred for all indicators, suggesting that current designs are not fail-safe. These results give first indications on how users of AR applications could be informed about the physicality and virtuality of components once indistinguishable by the human eye alone.

Recent advances in AI, XR, multimodal sensing, wearable interfaces, and cyber-physical infrastructures are expanding the role of Ubiquitous Computing from supporting everyday activities to shaping how people perceive, interpret, and discuss about the world around them. These systems can enable accessibility, learning, mobility, collaboration, and public-space interaction at unprecendented personalization levels, but they may also fragment shared understanding, create asymmetries, and raise concerns around manipulation, privacy, safety, accountability, and trust. This workshop introduces reality mediation as a unifying lens for these emerging challenges. It brings together researchers from across UbiComp’s contributing disciplines, including but not limited to HCI, XR, AI, urban computing, mobility, cyber-physical systems, and trustworthy computing, to discuss how personalized and mediated experiences can remain intelligible, shareable, and societally grounded. The workshop aims to develop concepts, design principles, evaluation methods, and research questions for future ubiquitous computing systems that are not only adaptive and intelligent, but also supportive of shared understanding, towards ubiquitous technology that increases societal cohesion rather than undermining it.

Debugging is an important activity in software development, yet providing actionable and comprehensible explanations for program failures remains challenging. Automated tools such as ALHAZEN and AVICENNA address this by using distinct strategies: ALHAZEN employs binary decision trees to show failure-inducing conditions, while AVICENNA uses a specification language to model complex input dependencies. To assess their impact on usability and user efficiency, we conducted a controlled within-between-subjects user study with 18 participants tasked with resolving four software bugs using either tool or no support. Quantitative results showed that both tools improved debugging efficiency compared to manual methods, with AVICENNA offering more precise diagnostics but requiring higher cognitive effort. Qualitative feedback revealed a preference for AVICENNA’s expressiveness despite its complexity. Our findings show that effective debugging tools have tradeoffs between accuracy and interpretability to support developers’ decision-making in increasingly complex software environments.