Human-Centered AI Support for Immersive Data Sensemaking

Immersive analytics and extended reality (XR) environments are changing how people explore complex data, reason spatially, and collaborate around emerging patterns. At the same time, rapid advances in generative AI, adaptive interfaces, and multimodal sensing are creating new possibilities for AI systems to summarize, recommend, explain, annotate, simulate, and support decision-making during data sensemaking.

Despite this potential, the integration of human-centered AI into immersive data sensemaking remains fragmented. Many systems demonstrate impressive technical capabilities, but less is known about how AI support should be designed so that it strengthens human judgment, preserves agency, communicates uncertainty, and supports trustworthy collaboration in complex analytical contexts.

This workshop brings together researchers and practitioners from HCI, AI, visualization, immersive analytics, XR, and cognitive science to examine how AI can act as a meaningful collaborator in immersive data work. Rather than treating AI as an autonomous replacement for human reasoning, the workshop focuses on how people and AI systems can jointly interpret data, negotiate uncertainty, and build insight in interactive immersive environments.

Motivation and Goals

The workshop aims to establish a shared research space for human-centered AI support in immersive data sensemaking. Our goals are to:

• Clarify the design space for AI-supported immersive sensemaking, including when AI should guide, explain, adapt, challenge, or step back.
• Connect communities across HCI, AI, visualization, XR, cognitive science, and applied domains where complex data interpretation matters.
• Identify human-centered principles for systems that remain interpretable, accountable, adaptive, and respectful of user agency.
• Discuss evaluation approaches for trust, collaboration quality, cognitive load, insight generation, and user control in immersive human-AI workflows.
• Develop a shared research agenda that outlines open challenges, promising methods, and opportunities for future collaboration.

Focus Areas

The workshop will focus on conceptual, design, technical, and evaluation challenges in HCAI-supported immersive data sensemaking, including:

• Human-AI collaboration in immersive sensemaking: roles, initiative, agency, and interaction patterns between users, groups, and AI systems.
• AI-supported visual analytics: explanation, recommendation, summarization, annotation, and uncertainty communication in immersive data environments.
• Multimodal and adaptive interaction: use of speech, gesture, gaze, physiological signals, and interaction traces to support context-aware AI assistance.
• Trust, ethics, and user control: responsible approaches to transparency, privacy, calibration, accessibility, and human oversight.
• Methods and applications: evaluation frameworks, design guidelines, prototypes, and domain cases where immersive human-AI sensemaking can create value.

The workshop will combine short participant presentations, theme-based group discussions, and synthesis activities. Outcomes will include a shared overview of key challenges and research directions, with the aim of supporting future collaborations and a follow-up synthesis article.