Poet-Weaver: Reflecting on Communication Failure in Personal Relationships With Stylized AI-Generated Conversation Digests
Seraphina Yong, Chi-Lan Yang, Atsushi Hashimoto, Hideaki Kuzuoka, Shigeo Yoshida
Abstract
Interpersonal communication often involves navigating social challenges like managing expectations and conveying intentions. In practical contexts like productivity and navigation of social boundaries, agent-and AI-mediated communication (AIMC) has served as an effective social intermediary. Communication within personal relationships, especially between intercultural friends from different backgrounds, can also face significant challenges, such as miscommunication and expressive suppression. However, AIMC remains underutilized in the context of established personal relationships due to ethical concerns about agency and authenticity. We propose designing openly-interpretable AIMC output as an augmented context cue to reduce its active social involvement, balancing AI support with preservation of relational agency. We developed and evaluated Poet-Weaver, a Discord text chat plugin that presents AI-generated insights on user conversations in a stylized, openly-interpretable way to encourage reflection on communication challenges. We conducted a mixed-methods study with 30 intercultural friend pairs to assess Poet-Weaver's impact. Findings showed Poet-Weaver effectively helped participants address communication failures, although AIMC still influenced users' behavior even with openly-interpretable output. We recommend future uses of AIMC that support transformative, positive relationship changes while preserving individual responsibility and identity within relationships.
CCS Concepts: • Human-centered computing → Empirical studies in collaborative and social computing; Collaborative and social computing systems and tools.
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