KNIT-C: Exploring Conversational AI Facilitation of Group Convergence Through Computational Boundary Objects
TL;DR
KNIT-C is introduced, a conversational system that operationalises computational boundary objects within synchronous multi-user dialogue, eliciting individual viewpoints, synthesising group perspectives, and guiding discussion toward negotiated outcomes, finding that conversational engagement deepened individual reflection but created pacing and coordination challenges in group interaction.
Abstract
Conversational AI is widely explored for supporting brainstorming and creative collaboration, yet its potential to guide groups through convergence, where differing perspectives must be reconciled into a shared direction, remains largely unexamined. We introduce KNIT-C, a conversational system that operationalises computational boundary objects within synchronous multi-user dialogue, eliciting individual viewpoints, synthesising group perspectives, and guiding discussion toward negotiated outcomes. Across four public workshop sessions (14 non-expert participants), we find that conversational engagement deepened individual reflection but created pacing and coordination challenges in group interaction. AI-generated summaries anchored discussion, though their similarity demanded careful comparison rather than simplifying choices. Participants frequently reported feeling heard without fully endorsing outcomes, pointing to productive disagreement as a form of convergence that preserves visible tension rather than resolving it. We discuss implications for adaptive pacing, context-sensitive stance-shifting, and evaluation frameworks that assess whether differences were genuinely engaged rather than suppressed.