Exploring Needs and Design Opportunities for Proactive Information Support in In-Person Small-Group Conversations

2026-01-24

AI Summary

In face-to-face small-group conversations, participants often struggle to simultaneously manage attention allocation, interpret nonverbal cues, and engage effectively due to a lack of real-time informational support. This study systematically investigates the design requirements and opportunities for proactive information support through focus groups and two mixed-reality technology probes, employing participatory design and qualitative methods. It presents the first set of design principles specifically tailored for proactive information support in small-group dialogues and identifies key design opportunities that maximize its benefits. The findings offer a novel paradigm for developing proactive AI agents in augmented reality and lay the groundwork for enriched, augmented face-to-face conversational experiences.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Multiagent Systems: Agent Communication
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

In-person small-group conversations play a crucial role in everyday life; however, facilitating effective group interaction can be challenging, as the real-time nature demands full attention, offers no opportunity for revision, and requires interpreting non-verbal cues. Using Mixed Reality to provide proactive information support shows promise in helping individuals engage in and contribute to group conversations. We present a preliminary participatory design and qualitative study (N = 10) using focus groups and two technology probes to explore the opportunities of designing proactive information support in in-person small-group conversations. We reveal key design opportunities concerning how to maximize the benefits of proactive information support and how to effectively design such supporting information. Our study is crucial for paving the way toward designing future proactive AI agents to enable the paradigm of augmented in-person small-group conversation experience.

Problem

• small-group conversations
• proactive information support
• in-person interaction
• Mixed Reality
• AI agents

Innovation

• proactive information support
• mixed reality
• small-group conversation
• participatory design
• AI agents