@article{ART003364210},
author={Su-Min Jung and Ye-Jin Ko and Jae-Eun Shin},
title={From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2026},
volume={31},
number={7},
pages={65-78}
TY - JOUR
AU - Su-Min Jung
AU - Ye-Jin Ko
AU - Jae-Eun Shin
TI - From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection
JO - Journal of The Korea Society of Computer and Information
PY - 2026
VL - 31
IS - 7
PB - The Korean Society Of Computer And Information
SP - 65
EP - 78
SN - 1598-849X
AB - As AI agents become increasingly integrated into group decision-making, how different intervention styles affect consensus experience remains understudied. We designed a within-subject experiment (N=48) comparing a recommender-type agent (ranked candidate list based on aggregated preferences) and a mediator-type agent (structures disagreements and guides consensus through voting) in a group trip planning task. Consensus experience was assessed across four dimensions: perceived exploration ease, procedural fairness, perceived control, and trust. The mediator condition yielded significantly higher perceived exploration ease and procedural fairness, while the recommender condition was associated with higher perceived control. Qualitative findings revealed that mediator-type intervention was experienced ambivalently — as both helpful facilitation and unwanted intrusion. These findings suggest that AI intervention style is a meaningful design variable in group decision support.
KW - Group decision making;AI intervention style;Human-AI interaction;Consensus experience;Procedural fairness;User agency
DO -
UR -
ER -
Su-Min Jung, Ye-Jin Ko and Jae-Eun Shin. (2026). From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection. Journal of The Korea Society of Computer and Information, 31(7), 65-78.
Su-Min Jung, Ye-Jin Ko and Jae-Eun Shin. 2026, "From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection", Journal of The Korea Society of Computer and Information, vol.31, no.7 pp.65-78.
Su-Min Jung, Ye-Jin Ko, Jae-Eun Shin "From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection" Journal of The Korea Society of Computer and Information 31.7 pp.65-78 (2026) : 65.
Su-Min Jung, Ye-Jin Ko, Jae-Eun Shin. From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection. 2026; 31(7), 65-78.
Su-Min Jung, Ye-Jin Ko and Jae-Eun Shin. "From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection" Journal of The Korea Society of Computer and Information 31, no.7 (2026) : 65-78.
Su-Min Jung; Ye-Jin Ko; Jae-Eun Shin. From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection. Journal of The Korea Society of Computer and Information, 31(7), 65-78.
Su-Min Jung; Ye-Jin Ko; Jae-Eun Shin. From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection. Journal of The Korea Society of Computer and Information. 2026; 31(7) 65-78.
Su-Min Jung, Ye-Jin Ko, Jae-Eun Shin. From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection. 2026; 31(7), 65-78.
Su-Min Jung, Ye-Jin Ko and Jae-Eun Shin. "From Recommendation to Mediation: How AI Intervention Styles Shape Consensus Experience in Chat-Based Destination Selection" Journal of The Korea Society of Computer and Information 31, no.7 (2026) : 65-78.
