Christopher Flathmann, Nathan J. Mcneese, Beau G. Schelble, Bart P. Knijnenburg, Guo Freeman
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引用次数: 4
Abstract
Technical and practical advancements in Artificial Intelligence (AI) have led to AI teammates working alongside humans in an area known as humanagent teaming. While critical past research has shown the benefit to trust driven by the incorporation of interaction rules and structures (i.e. etiquette) in both AI tools and robotic teammates, research has yet to explicitly examine etiquette for digital AI teammates. Given the historic importance of trust within human-agent teams, the identification of etiquette’s impact within said teams should be paramount. Thus, this study empirically evaluates the impact of AI teammate etiquette through a mixedmethods study that compares AI teammates that either adhere to or ignore traditional etiquette standards for machine systems. The quantitative results show that traditional etiquette adherence leads to greater trust, perceived performance of the AI, and perceived performance of the team as a whole. However, qualitative results reveal that not all traditional etiquette behaviors have universal appeal due to the presence of individual differences. This research provides the first empirical and explicit exploration of etiquette within human-agent teams, and the results of this study should be used further design specific etiquette behaviors for AI teammates. ARTICLE HISTORY Received 6 July 2022 Revised 23 February 2023 Accepted 2 March 2023
期刊介绍:
Human-Computer Interaction (HCI) is a multidisciplinary journal defining and reporting
on fundamental research in human-computer interaction. The goal of HCI is to be a journal
of the highest quality that combines the best research and design work to extend our
understanding of human-computer interaction. The target audience is the research
community with an interest in both the scientific implications and practical relevance of
how interactive computer systems should be designed and how they are actually used. HCI is
concerned with the theoretical, empirical, and methodological issues of interaction science
and system design as it affects the user.