Friend, Foe, or Bot? Exploring Intergroup Dynamics in Hybrid Human-Bot Teams

要旨

Existing research has examined how artificial teammates influence collaboration within teams, but far less is known about their role in shaping interactions between teams. In particular, it remains unclear how transparent integration of AI teammates influences intergroup biases in competitive contexts. To investigate this, we designed StarHarvest, an online game where two hybrid teams (each consisting of one human and one bot, either concealed or revealed) competed for resources while bots elicited prosocial or antisocial behaviors. Drawing on data from 240 participants, we analyzed behavioral choices, evaluations, and resource allocations toward ingroup and outgroup members. Our findings show that hidden bots fostered stronger within-team coordination but also allowed asymmetric retribution toward weaker opponents. By contrast, revealed bots were treated as secondary teammates, reducing cohesion and shifting responsibility onto human partners. We conclude with design implications for socially responsible integration of artificial teammates, highlighting tensions between group-level and agent-level identities.

受賞
Best Paper
著者
Assem Zhunis
HKUST, Hong Kong, Hong Kong
Ziqi Pan
The Hong Kong University of Science and Technology, Hong Kong, China
Yuanhao Zhang
Hong Kong University of Science and Technology, Hong Kong, China
Xiaojuan Ma
Hong Kong University of Science and Technology, Hong Kong, Hong Kong

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Synergistic with AI

P1 - Room 125
6 件の発表
2026-04-15 20:15:00
2026-04-15 21:45:00