{"title":"视觉搜索任务中的人机计划冲突和冲突解决","authors":"Yunxian Pan , Jie Xu","doi":"10.1016/j.ijhcs.2024.103377","DOIUrl":null,"url":null,"abstract":"<div><div>With rapid technological development, humans are more likely to cooperatively work with intelligence systems in everyday life and work. Similar to interpersonal teamwork, the effectiveness of human-machine teams is affected by conflicts. Some human-machine conflict scenarios occur when neither the human nor the system was at fault, for example, when the human and the system formulated different but equally effective plans to achieve the same goal. In this study, we conducted two experiments to explore the effects of human-machine plan conflict and the different conflict resolution approaches (human adapting to the system, system adapting to the human, and transparency design) in a computer-aided visual search task. The results of the first experiment showed that when conflicts occurred, the participants reported higher mental load during the task, performed worse, and provided lower subjective evaluations towards the aid. The second experiment showed that all three conflict resolution approaches were effective in maintaining task performance, however, only the transparency design and the human adapting to the system approaches were effective in reducing mental load and improving subjective evaluations. The results highlighted the need to design appropriate human-machine conflict resolution strategies to optimize system performance and user experience.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Human-machine plan conflict and conflict resolution in a visual search task\",\"authors\":\"Yunxian Pan , Jie Xu\",\"doi\":\"10.1016/j.ijhcs.2024.103377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With rapid technological development, humans are more likely to cooperatively work with intelligence systems in everyday life and work. Similar to interpersonal teamwork, the effectiveness of human-machine teams is affected by conflicts. Some human-machine conflict scenarios occur when neither the human nor the system was at fault, for example, when the human and the system formulated different but equally effective plans to achieve the same goal. In this study, we conducted two experiments to explore the effects of human-machine plan conflict and the different conflict resolution approaches (human adapting to the system, system adapting to the human, and transparency design) in a computer-aided visual search task. The results of the first experiment showed that when conflicts occurred, the participants reported higher mental load during the task, performed worse, and provided lower subjective evaluations towards the aid. The second experiment showed that all three conflict resolution approaches were effective in maintaining task performance, however, only the transparency design and the human adapting to the system approaches were effective in reducing mental load and improving subjective evaluations. The results highlighted the need to design appropriate human-machine conflict resolution strategies to optimize system performance and user experience.</div></div>\",\"PeriodicalId\":54955,\"journal\":{\"name\":\"International Journal of Human-Computer Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Human-Computer Studies\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1071581924001605\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human-Computer Studies","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071581924001605","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Human-machine plan conflict and conflict resolution in a visual search task
With rapid technological development, humans are more likely to cooperatively work with intelligence systems in everyday life and work. Similar to interpersonal teamwork, the effectiveness of human-machine teams is affected by conflicts. Some human-machine conflict scenarios occur when neither the human nor the system was at fault, for example, when the human and the system formulated different but equally effective plans to achieve the same goal. In this study, we conducted two experiments to explore the effects of human-machine plan conflict and the different conflict resolution approaches (human adapting to the system, system adapting to the human, and transparency design) in a computer-aided visual search task. The results of the first experiment showed that when conflicts occurred, the participants reported higher mental load during the task, performed worse, and provided lower subjective evaluations towards the aid. The second experiment showed that all three conflict resolution approaches were effective in maintaining task performance, however, only the transparency design and the human adapting to the system approaches were effective in reducing mental load and improving subjective evaluations. The results highlighted the need to design appropriate human-machine conflict resolution strategies to optimize system performance and user experience.
期刊介绍:
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
• Innovative interaction techniques
• Multimodal interaction
• Speech interaction
• Graphic interaction
• Natural language interaction
• Interaction in mobile and embedded systems
• Interface design and evaluation methodologies
• Design and evaluation of innovative interactive systems
• User interface prototyping and management systems
• Ubiquitous computing
• Wearable computers
• Pervasive computing
• Affective computing
• Empirical studies of user behaviour
• Empirical studies of programming and software engineering
• Computer supported cooperative work
• Computer mediated communication
• Virtual reality
• Mixed and augmented Reality
• Intelligent user interfaces
• Presence
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