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The Effects of Proactive AI Agent Intervention Methods on User Experience in Social Conversation Contexts

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2026, 31(2), pp.1~16
  • DOI : 10.9708/jksci.2026.31.02.001
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : December 23, 2025
  • Accepted : January 20, 2026
  • Published : February 27, 2026

Seong-Yeon Kim 1 Ju-Hye Ha 1 Chang-Hoon Oh 1

1연세대학교

Accredited

ABSTRACT

This study examines how proactive intervention methods by conversational AI agents affect user experience in dyadic home conversations. AI Agent interventions in social contexts create a "proactivity dilemma" by influencing conversational dynamics and relational norms. A 3 × 2 within-subject experiment (N=30) measured social appropriateness, agency, and pleasantness across conversation types and intervention methods. Consent-based interventions significantly outperformed direct interventions, particularly for agency in opinion conflicts. Mediation analysis validated the pathway: intervention method → social appropriateness → agency → pleasantness. Qualitatively, consent-based interventions represented "knocking" versus direct interventions as "intrusion." This research establishes a proactive AI Agent acceptance model for social contexts with consent-based design as default.

Citation status

* References for papers published after 2024 are currently being built.

This paper was written with support from the National Research Foundation of Korea.