Can AR Embedded Visualizations Foster Appropriate Reliance on AI in Spatial Decision-Making? A Comparative Study of AR X-Ray vs. 2D Minimap
arXiv:2507.14316 · doi:10.1145/3772318.3790710
The paper reports a user study comparing an AR-embedded X‑ray visualization with a traditional 2D minimap for AI‑assisted spatial target selection, finding that the AR view can increase over‑reliance on AI despite improving spatial mapping.
Abstract
Artificial Intelligence (AI) and indoor sensing increasingly support decision-making in spatial environments. However, traditional visualization methods impose a substantial mental workload when viewers translate this digital information into real-world spaces, leading to inappropriate reliance on AI. Embedded visualizations in Augmented Reality (AR), by integrating information into physical environments, may reduce this workload and foster more appropriate reliance on AI. To assess this, we conducted an empirical study (N = 32) comparing an AR embedded visualization (X-ray) and 2D Minimap in AI-assisted, time-critical spatial target selection tasks. Surprisingly, evidence shows that the embedded visualization led to greater inappropriate reliance on AI, primarily as over-reliance, due to factors like perceptual challenges, visual proximity illusions, and highly realistic visual representations. Nonetheless, the embedded visualization demonstrated benefits in spatial mapping. We conclude by discussing empirical insights, design implications, and directions for future research on human-AI collaborative decision in AR.
15 pages, 10 figures, Accepted for publication in CHI'26, Barcelona, Spain, April 13 - 17, 2026; CHI '26: ACM CHI Conference on Human Factors in Computing Systems