{"title":"个体人工智能熟练程度对人类智能体协作的影响:对于人工智能熟练程度较高的用户,识别智能体理解能力的敏感度更高","authors":"Ruifeng Yu, Xinran Xu, Shuo Peng","doi":"10.1016/j.ergon.2025.103745","DOIUrl":null,"url":null,"abstract":"<div><div>This study explored the impact of individual artificial intelligence (AI) proficiency on task scores, human perceptions of the agent's intelligence and anthropomorphism, trust, and mental workload from the perspective of human–agent collaboration. A 2 (Individual AI Proficiency, between-subjects) <span><math><mrow><mo>×</mo></mrow></math></span> 2 (Intelligent Agent's Comprehension Ability for Human Intentions, within-subjects) mixed experimental design was implemented in a task in which the participants and intelligent agents collaborated to navigate an unknown map. Forty participants participated in this study. The results revealed significant interaction effects between human AI proficiency and the agents' comprehension abilities on human trust, perceived intelligence, and perceived anthropomorphism. Users with higher AI proficiency demonstrated greater trust, perceived intelligence, and anthropomorphism when interacting with intelligent agents that interpreted human intention based on both immediate and previous feedback, compared to intelligent agents based solely on immediate feedback, displaying a higher sensitivity to the change in agents' ability. Additionally, intelligent agents that interpret human intentions based on both immediate and previous feedback significantly reduce users' mental workload compared with those that rely solely on immediate feedback.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103745"},"PeriodicalIF":3.0000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of individual AI proficiency on human–agent collaboration: Higher sensitivity to discern the comprehension ability of intelligent agents for users with higher AI proficiency levels\",\"authors\":\"Ruifeng Yu, Xinran Xu, Shuo Peng\",\"doi\":\"10.1016/j.ergon.2025.103745\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study explored the impact of individual artificial intelligence (AI) proficiency on task scores, human perceptions of the agent's intelligence and anthropomorphism, trust, and mental workload from the perspective of human–agent collaboration. A 2 (Individual AI Proficiency, between-subjects) <span><math><mrow><mo>×</mo></mrow></math></span> 2 (Intelligent Agent's Comprehension Ability for Human Intentions, within-subjects) mixed experimental design was implemented in a task in which the participants and intelligent agents collaborated to navigate an unknown map. Forty participants participated in this study. The results revealed significant interaction effects between human AI proficiency and the agents' comprehension abilities on human trust, perceived intelligence, and perceived anthropomorphism. Users with higher AI proficiency demonstrated greater trust, perceived intelligence, and anthropomorphism when interacting with intelligent agents that interpreted human intention based on both immediate and previous feedback, compared to intelligent agents based solely on immediate feedback, displaying a higher sensitivity to the change in agents' ability. Additionally, intelligent agents that interpret human intentions based on both immediate and previous feedback significantly reduce users' mental workload compared with those that rely solely on immediate feedback.</div></div>\",\"PeriodicalId\":50317,\"journal\":{\"name\":\"International Journal of Industrial Ergonomics\",\"volume\":\"107 \",\"pages\":\"Article 103745\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Industrial Ergonomics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0169814125000514\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Industrial Ergonomics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169814125000514","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
The impact of individual AI proficiency on human–agent collaboration: Higher sensitivity to discern the comprehension ability of intelligent agents for users with higher AI proficiency levels
This study explored the impact of individual artificial intelligence (AI) proficiency on task scores, human perceptions of the agent's intelligence and anthropomorphism, trust, and mental workload from the perspective of human–agent collaboration. A 2 (Individual AI Proficiency, between-subjects) 2 (Intelligent Agent's Comprehension Ability for Human Intentions, within-subjects) mixed experimental design was implemented in a task in which the participants and intelligent agents collaborated to navigate an unknown map. Forty participants participated in this study. The results revealed significant interaction effects between human AI proficiency and the agents' comprehension abilities on human trust, perceived intelligence, and perceived anthropomorphism. Users with higher AI proficiency demonstrated greater trust, perceived intelligence, and anthropomorphism when interacting with intelligent agents that interpreted human intention based on both immediate and previous feedback, compared to intelligent agents based solely on immediate feedback, displaying a higher sensitivity to the change in agents' ability. Additionally, intelligent agents that interpret human intentions based on both immediate and previous feedback significantly reduce users' mental workload compared with those that rely solely on immediate feedback.
期刊介绍:
The journal publishes original contributions that add to our understanding of the role of humans in today systems and the interactions thereof with various system components. The journal typically covers the following areas: industrial and occupational ergonomics, design of systems, tools and equipment, human performance measurement and modeling, human productivity, humans in technologically complex systems, and safety. The focus of the articles includes basic theoretical advances, applications, case studies, new methodologies and procedures; and empirical studies.