Examining the Role of AI Information-Sharing on Trust in Human-AI Teams

Creating reliable human-AI teams with strong team cognition requires a deeper understanding of how humans perceive and react to various information-sharing tactics employed by an AI teammate. The current study details a factorial survey investigating how participants’ trust in their AI and human teammates changes across various forms of AI information sharing. These information-sharing attributes included backup behavior, explainability, team member statuses, intra- and extra-team changes, augmenting team memory, and control. The study found that participants’ trust in their AI teammate benefited most from information about changes inside and outside the team, but all conditions outperformed the control. Further, the back-up behavior information negatively affected the participants’ trust in their human teammate as the AI corrected the human teammates’ actions. These findings demonstrate the utility of a specific form of situation awareness information, while highlighting that corrective back-up behavior information from an AI may harm perceptions between human teammates.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2025-09-01
DOI
https://doi.org/10.1177/10711813251367726
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

Examining the Role of AI Information-Sharing on Trust in Human-AI Teams

Kapil Chalil Madathil, Beau G. Schelble, Christopher Flathmann, Gracyn Filer
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Human-Automation Interaction and Safety
article

Examining the Role of AI Information-Sharing on Trust in Human-AI Teams

Kapil Chalil Madathil, Beau G. Schelble, Christopher Flathmann, Gracyn Filer
article en

Abstract

Creating reliable human-AI teams with strong team cognition requires a deeper understanding of how humans perceive and react to various information-sharing tactics employed by an AI teammate. The current study details a factorial survey investigating how participants’ trust in their AI and human teammates changes across various forms of AI information sharing. These information-sharing attributes included backup behavior, explainability, team member statuses, intra- and extra-team changes, augmenting team memory, and control. The study found that participants’ trust in their AI teammate benefited most from information about changes inside and outside the team, but all conditions outperformed the control. Further, the back-up behavior information negatively affected the participants’ trust in their human teammate as the AI corrected the human teammates’ actions. These findings demonstrate the utility of a specific form of situation awareness information, while highlighting that corrective back-up behavior information from an AI may harm perceptions between human teammates.

Proceedings of the Human Factors and Ergonomics Society Annual MeetingVol. 69(1)
University of Tennessee at Knoxville (US), Clemson University (US)
Openalex Percentile: Top 73%
Human-Automation Interaction and Safety
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