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Bidirectional transparency in human-agent communications: effects of direction and level of transparency
Xinran Xu1, Ruifeng Yu1, Minhui Yuan1
1Department of Industrial Engineering, Tsinghua University, Beijing, China.
Abstract:
This study investigated whether bidirectional transparency, compared to agent-to-human transparency, improved human-agent collaboration. Additionally, we examined the optimal transparency levels for both humans and agents. We assessed the impact of transparency direction and level on various metrics of a human-agent team, including performance, trust, satisfaction, perceived agent's teaming skills, and mental workload. A total of 30 participants engaged in a human-agent collaborative game in a within-subject experiment with five conditions: a 2 (transparency directions: agent-to-human transparency vs. bidirectional transparency) × 2 (transparency levels: reasoning transparency vs. reasoning + projection transparency) factorial design, plus an additional action transparency condition as a control condition. The findings indicated that bidirectional transparency improved task performance without increasing the mental workload. This study recommends a bidirectional transparency mechanism, in which the agent provides transparency to humans regarding its reasoning and predictions, whereas humans offer transparency to the agent regarding their reasoning. Practitioner Summary: This study highlights the importance of bidirectional transparency in human-agent collaboration, demonstrating its effectiveness in enhancing task performance without increasing mental workload. It recommends implementing a mechanism where both humans and agents share transparency information, optimising collaboration outcomes.
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