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Attribution Biases and Trust Development in Physical Human-Machine Coordination: Blaming Yourself, Your Partner or an Unexpected Event

Abstract Reading partners’ actions correctly is essential for successful coordination, but interpretation does not always reflect reality. Attribution biases, such as self-serving and correspondence biases, lead people to misinterpret their partners’ actions and falsely assign blame after an unexpected event. These biases thus further influence people’s trust in their partners, including machine partners. The increasing capabilities and complexity of machines allow them to work physically with humans. However, their improvements may interfere with the accuracy for people to calibrate trust in machines and their capabilities, which requires an understanding of attribution biases’ effect on human-machine coordination. Specifically, the current thesis ... (more)
Created Date 2019
Contributor Hsiung, Chi-Ping (Author) / Chiou, Erin (Advisor) / Cooke, Nancy (Advisor) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Subject Psychology / attribution bias / blame / physical human-machine coordination / trust / trust in machines / unexpected event
Type Masters Thesis
Extent 76 pages
Language English
Note Masters Thesis Human Systems Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis