DOI: 10.1177/00187208261464006 ISSN: 0018-7208

System-Wide Trust (SWT) Versus Component-Specific Trust (CST) in Multi-Agent Human–Agent Teams: Individual Variability in Trust Bias

Hyesun Chung, X. Jessie Yang

Background

Prior work on trust in multi-component systems has proposed two competing perspectives: system-wide trust (SWT) versus component-specific trust (CST). SWT argues that individuals view multiple agent teammates as interconnected parts of a single “system,” and thus trust in one agent spills over to others; CST, in contrast, argues that trust is evaluated on a component-by-component basis. However, existing studies have largely overlooked individual differences in these trust evaluation patterns.

Method

We conducted a lab study with 30 two-human-two-agent teams performing collaborative block-moving tasks. Teams completed 10 trials each under three agent reliability pairing conditions: perfect (both agents reliable), mixed (one reliable and one unreliable), and imperfect (both unreliable). After each trial, participants rated trust in each teammate and the team, while communication logs and task completion times were recorded. We first evaluated individual variability and classified participants based on how trust in one agent changed as a function of paired-agent reliability. Subsequently, we examined how these influenced communication behaviors and performance.

Results

We identified three distinct trust bias patterns: assimilation (trust becomes more similar across agents, consistent with SWT), no bias (trust remains independent across agents, consistent with CST), and contrast (trust becomes more differentiated between agents). These were associated with different communication strategies and reliance behaviors, which in turn affected team performance.

Conclusion

Trust in multi-agent HATs cannot be fully explained by SWT or CST alone but instead varies with how individuals comparatively evaluate autonomous agents.

Application

The findings provide a foundation for developing personalized trust bias mitigation.

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