New Paper on Leaders' Trust in HAT Presented at CHI 2026
April 13, 2026
Artificially intelligent agents are increasingly moving beyond decision-support roles to become teammates,
creating novel team configurations beyond traditional human-AI dyads. One such configuration is a hierarchical team,
where a human leader directs both human and agent subordinates. This raises key questions about managing mixed-identity
subordinates and about how agent traits (ability/integrity) shape trust. We present a lab study with teams of four
(one human leader, with one human and two agent subordinates) performing a collaborative block-moving task. Leaders
interacted with three types of agents that varied in ability and integrity: High-Integrity-High-Ability (HI-HA),
High-Integrity-Low-Ability (HI-LA), and Low-Integrity-High-Ability (LI-HA). Leaders generally preferred and maintained stable trust in humans,
whereas trust in agents declined significantly under both low-ability and low-integrity conditions, with stronger sensitivity to integrity.
Thematic analysis revealed distinct expectations tied to identity: leaders granted humans an inherent baseline of trust due to humans’
adaptability, while evaluating agents primarily on task efficiency and obedience.
Please check out this paper!
Citation: Chung, H., & Yang, X. J. (2026, April). "Should I Rely on You or the AI?" Leaders' Trust and Perceptions in Mixed Human-AI Teams.
In Proceedings of the 2026 chi conference on human factors in computing systems (pp. 1-16).