Understanding the impact and design of AI teammate etiquette

IF 4.5 2区 工程技术 Q1 COMPUTER SCIENCE, CYBERNETICS Human-Computer Interaction Pub Date : 2023-03-24 DOI:10.1080/07370024.2023.2189595
Christopher Flathmann, Nathan J. Mcneese, Beau G. Schelble, Bart P. Knijnenburg, Guo Freeman
{"title":"Understanding the impact and design of AI teammate etiquette","authors":"Christopher Flathmann, Nathan J. Mcneese, Beau G. Schelble, Bart P. Knijnenburg, Guo Freeman","doi":"10.1080/07370024.2023.2189595","DOIUrl":null,"url":null,"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","PeriodicalId":56306,"journal":{"name":"Human-Computer Interaction","volume":"58 1","pages":""},"PeriodicalIF":4.5000,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human-Computer Interaction","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/07370024.2023.2189595","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
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
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
理解AI队友礼仪的影响和设计
人工智能(AI)的技术和实践进步导致人工智能团队与人类一起在一个被称为人类管理团队的领域工作。虽然过去的重要研究已经表明,在人工智能工具和机器人队友中结合互动规则和结构(即礼仪)对信任有好处,但研究尚未明确研究数字人工智能队友的礼仪。鉴于信任在人类代理团队中的历史重要性,确定礼仪在团队中的影响应该是至关重要的。因此,本研究通过混合方法研究,对遵守或忽视机器系统传统礼仪标准的AI队友进行比较,实证评估AI队友礼仪的影响。定量结果表明,传统礼仪的遵守导致了更大的信任,人工智能的感知绩效,以及整个团队的感知绩效。然而,定性结果表明,由于个体差异的存在,并不是所有的传统礼仪行为都具有普遍的吸引力。本研究首次对人类智能体团队中的礼仪进行了实证和明确的探索,本研究的结果应进一步用于为AI团队设计具体的礼仪行为。文章历史收到2022年7月6日修订2023年2月23日接受2023年3月2日
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Human-Computer Interaction
Human-Computer Interaction 工程技术-计算机:控制论
CiteScore
12.20
自引率
3.80%
发文量
15
审稿时长
>12 weeks
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.
期刊最新文献
File hyper-searching explained Social fidelity in cooperative virtual reality maritime training The future of PIM: pragmatics and potential Clarifying and differentiating discoverability Design and evaluation of a versatile text input device for virtual and immersive workspaces
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1