arXiv subjects

Janet G. Johnson

Publications and source records attributed to Janet G. Johnson.

5 recordsLinked to original sources

arXiv2026

ChatMuse: Supporting In-Person Small-Group Conversation Experience with a Proactive Assistive AI Agent in Mixed Reality

In-person small-group conversations occur across nearly every aspect of daily life and play a crucial role in social interaction. However, achieving effective in-person group conversations can be challenging and cognitively demanding. While recent Mixed Reality (MR) headsets show promise as a conversational support system by presenting relevant information through overlays, it remains unclear how such supporting information should be designed and generated for in-person group conversations. We propose ChatMuse, a novel MR-based proactive assistive system for in-person small-group conversation experience. ChatMuse analyzes verbal and non-verbal cues from all conversation participants and proactively provides real-time guidance on the user's verbal and non-verbal behaviors. The behavioral responses of the supported users are then used to improve ChatMuse's support capabilities in subsequent interactions. We conducted a within-subject study to evaluate and demonstrate the feasibility and effectiveness of ChatMuse in assisting users to engage in and contribute to in-person small-group conversations. Our research around ChatMuse represents a design exploration of a new interaction space that investigates the feasibility of supporting in-person small-group conversations through a proactive assistive AI agent in MR.

cs.HC↗

arXiv2026

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

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.

cs.HC↗

arXiv2026

"I Felt Bad After We Ignored Her": Understanding How Interface-Driven Social Prominence Shapes Group Discussions with GenAI

Recent advancements in the conversational and social capabilities of generative AI (GenAI) have sparked interest in its role as an agent capable of actively participating in human-AI group discussions. Despite this momentum, we don't fully understand how GenAI shapes conversational dynamics or how the interface design impacts its influence on the group. In this paper, we introduce interface-driven social prominence as a design lens for collaborative GenAI systems. We then present a GenAI-based conversational agent that can actively engage in spoken dialogue during video calls and design three distinct collaboration modes that vary the social prominence of the agent by manipulating its presence in the shared space and the degree of control users have over its participation. A mixed-methods within-subjects study, in which 18 dyads engaged in realistic discussions with a GenAI agent, offers empirical insights into how communication patterns and the collective negotiation of GenAI's influence shift based on how it is embedded into the collaborative experience. Based on these findings, we outline design implications for supporting the coordination and critical engagement required in human-AI groups.

cs.HC↗

arXiv2025

Exploring Collaborative GenAI Agents in Synchronous Group Settings: Eliciting Team Perceptions and Design Considerations for the Future of Work

While generative artificial intelligence (GenAI) is finding increased adoption in workplaces, current tools are primarily designed for individual use. Prior work established the potential for these tools to enhance personal creativity and productivity towards shared goals; however, we don't know yet how to best take into account the nuances of group work and team dynamics when deploying GenAI in work settings. In this paper, we investigate the potential of collaborative GenAI agents to augment teamwork in synchronous group settings through an exploratory study that engaged 25 professionals across 6 teams in speculative design workshops and individual follow-up interviews. Our workshops included a mixed reality provotype to simulate embodied collaborative GenAI agents capable of actively participating in group discussions. Our findings suggest that, if designed well, collaborative GenAI agents offer valuable opportunities to enhance team problem-solving by challenging groupthink, bridging communication gaps, and reducing social friction. However, teams' willingness to integrate GenAI agents depended on its perceived fit across a number of individual, team, and organizational factors. We outline the key design tensions around agent representation, social prominence, and engagement and highlight the opportunities spatial and immersive technologies could offer to modulate GenAI influence on team outcomes and strike a balance between augmentation and agency.

cs.HC↗

arXiv2021

Understanding Barriers and Design Opportunities to Improve Healthcare and QOL for Older Adults through Voice Assistants

Voice based Intelligent Virtual Assistants (IVAs) promise to improve healthcare management and Quality of Life (QOL) by introducing the paradigm of hands free and eye free interactions. However, there has been little understanding regarding the challenges for designing such systems for older adults, especially when it comes to healthcare related tasks. To tackle this, we consider the processes of care delivery and QOL enhancements for older adults as a collaborative task between patients and providers. By interviewing 16 older adults living independently or semi independently and 5 providers, we identified 12 barriers that older adults might encounter during daily routine and while managing health. We ultimately highlighted key design challenges and opportunities that might be introduced when integrating voice based IVAs into the life of older adults. Our work will benefit practitioners who study and attempt to create full fledged IVA powered smart devices to deliver better care and support an increased QOL for aging populations.

cs.HC↗