朱孟潇,陆文灏,柳林

• 1:中国科学技术大学科技传播系
• 2:中国科学技术大学管理科学系

摘要(Abstract)：

人机信任指人类对机器系统可靠性、能力及伦理属性所持有的积极心理预期。自20世纪以来，学界逐步建立了关于人机信任的理论框架，并尝试定义其内涵、解释其作用机制。然而，随着大语言模型(LLM)的兴起，传统人机信任理论框架的局限性日益显现。本研究通过系统梳理相关理论与实证研究，从技术特异、用户差异与交互模式三个维度分析LLM语境下人机信任的特点，构建了涵盖信任建立、维持、破坏与修复的整合框架，为相关研究提供理论参考。

关键词(KeyWords)： 人机信任;大语言模型;整合框架

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 朱孟潇,陆文灏,柳林

参考文献(References)：

• 陈素白(2025):传播互动失败情境下用户对AI客服的持续信任研究：基于归因理论视角，《现代传播》,第47卷第3期，150-158。
• 董青岭(2024):人工智能时代的算法黑箱与信任重建，《人民论坛·学术前沿》,第16期，76-82。
• 葛畅、郭凯毅、朱雨菁、余隋怀(2025):智能化设备人机交互界面的信任校准综述，《机械设计》,第42卷第2期，159-165。
• 胡泳、王昱昊(2025):技术过程论视角下AI幻觉生成的价值负荷与伦理问题探析，《南京社会科学》,第3期，84-94。
• 黄心语、李晔(2024):人机信任校准的双途径：信任抑制与信任提升，《心理科学进展》,第32卷第3期，527-542。
• 解煜彬、周荣刚(2025):新型人机关系下的人机双向信任，《心理科学进展》,第33卷第6期，916-932。
• 李琎、谭田甜、刘双喜(2025):人际信任与人机信任的差异，《浙江大学学报(理学版)》,第52卷第5期，549-560,566页。
• 牟怡(2024):《传播的跃迁：人工智能如何革新人类的交流》,北京：清华大学出版社。
• 齐玥、陈俊廷、秦邵天、杜峰(2024):通用人工智能时代的人与AI信任，《心理科学进展》,第32卷第12期，2124-2136。
• 王袁欣、朱孟潇、陈思潞(2023):理解人机对话——对角色定位、信任关系及人际交往影响的分析，《全球传媒学刊》,第10卷第5期，106-126。
• 向安玲(2024):无以信，何以立：人机交互中的可持续信任机制，《未来传播》,第31卷第2期，29-41,129。
• 杨志勇、翟少铃(2022):服务消费中人工智能信息透明与顾客契合的关系研究——基于顾客信任和拟人化的分析，《价格理论与实践》,第4期，193-196。
• 衣俊霖(2025):论人机协同审判的信任构建，《中国法学》,第2期，148-167。
• 于雪(2022):基于机器能动性的人机交互信任建构，《自然辩证法研究》,第38卷第10期，43-49。
• Baker,A.L.,Phillips,E.K.,Ullman,D.& Keebler,J.R.(2018).Toward an understanding of trust repair in human-robot interaction:Current research and future directions.ACM Transactions on Interactive Intelligent Systems (TiiS),8(4),30.doi:10.1145/3181671.
• Banovic,N.,Yang,Z.R.,Ramesh,A.& Liu,A.(2023).Being trustworthy is not enough:How untrustworthy artificial intelligence (AI) can deceive the end-users and gain their trust.Proceedings of the ACM on Human-Computer Interaction,7(CSCW1),27.doi:10.1145/3579460.
• Bigman,Y.E.& Gray,K.(2018).People are averse to machines making moral decisions.Cognition,181,21-34.doi:10.1016/j.cognition.2018.08.003.
• Cheong,B.C.(2024).Transparency and accountability in AI systems:Safeguarding wellbeing in the age of algorithmic decision-making.Frontiers in Human Dynamics,6,1421273.doi:10.3389/fhumd.2024.1421273.
• Cohn,M.,Pushkarna,M.,Olanubi,G.O.,Moran,J.M.,Padgett,D.,Mengesha,Z.& Heldreth,C.(2024).Believing anthropomorphism:Examining the role of anthropomorphic cues on trust in large language models.In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp.54).Honolulu:Association for Computing Machinery.doi:10.1145/3613905.3650818.
• De Visser,E.J.,Krueger,F.,McKnight,P.,Scheid,S.,Smith,M.,Chalk,S.& Parasuraman,R.(2012).The world is not enough:Trust in cognitive agents.Proceedings of the Human Factors and Ergonomics Society Annual Meeting,56(1),263-267.doi:10.1177/1071181312561062.
• DiSalvo,C.F.,Gemperle,F.,Forlizzi,J.& Kiesler,S.(2002).All robots are not created equal:The design and perception of humanoid robot heads.In Proceedings of the 4th Conference on Designing Interactive Systems:Processes,Practices,Methods,and Techniques (321-326).London:Association for Computing Machinery.doi:10.1145/778712.778756.
• Dong,Y.,Xu,W.,Huang,J.Y.& Yann,K.(2025).Validating and refining a multi-dimensional scale for measuring AI literacy in education using the Rasch model.Humanities and Social Sciences Communications,12(1),1317.doi:10.1057/s41599-025-05670-6.
• Duan,H.D.,Wei,J.Q.,Wang,C.H.,Liu,H.W.,Fang,Y.X.,Zhang,S.Y.,Lin,D.H.,Chen,K.(2024).BotChat:Evaluating LLMs' capabilities of having multi-turn dialogues.In Findings of the Association for Computational Linguistics:NAACL 2024 (3184-3200).Mexico City:Association for Computational Linguistics.doi:10.18653/v1/2024.findings-naacl.201.
• Esterwood,C.& Robert,L.P.(2023a).The theory of mind and human-robot trust repair.Scientific Reports,13(1),9877.doi:10.1038/s41598-023-37032-0.
• Esterwood,C.& Robert,L.P.Jr.(2023b).Three strikes and you are out!:The impacts of multiple human-robot trust violations and repairs on robot trustworthiness.Computers in Human Behavior,142,107658.doi:10.1016/j.chb.2023.107658.
• Federiakin,D.,Molerov,D.,Zlatkin-Troitschanskaia,O.& Maur,A.(2024).Prompt engineering as a new 21st century skill.Frontiers in Education,9,1366434.doi:10.3389/feduc.2024.1366434.
• Foehr,J.& Germelmann,C.C.(2020).Alexa,can I trust you?Exploring consumer paths to trust in smart voice-interaction technologies.Journal of the Association for Consumer Research,5(2),181-205.doi:10.1086/707731.
• French,B.,Duenser,A.,& Heathcote,A.(2018).Trust in automation—A literature review (No.EP184082).CSIRO,Australia.
• Gillespie,N.,Lockey,S.,Ward,T.,Macdade,A.& Hassed,G.(2025).Trust,attitudes and use of artificial intelligence:A global study 2025.The University of Melbourne and KPMG.doi:10.26188/28822919.
• Glikson,E.& Woolley,A.W.(2020).Human trust in artificial intelligence:Review of empirical research.Academy of Management Annals,14(2),627-660.doi:10.5465/annals.2018.0057.
• Hancock,P.A.(2020).Imposing limits on autonomous systems.In Stanton,N.A.,Salmon,P.M.& Walker,G.(Eds.),New Paradigms in Ergonomics (pp.134-141).London:Routledge.
• Hancock,P.A.,Billings,D.R.,Schaefer,K.E.,Chen,J.Y.C.,De Visser,E.J.& Parasuraman,R.(2011).A meta-analysis of factors affecting trust in human-robot interaction.Human Factors:The Journal of the Human Factors and Ergonomics Society,53(5),517-527.doi:10.1177/0018720811417254.
• Hoff,K.A.& Bashir,M.(2015).Trust in automation:Integrating empirical evidence on factors that influence trust.Human Factors,57(3),407-434.doi:10.1177/0018720814547570.
• Hu,M.,Zhang,G.L.,Chong,L.,Cagan,J.& Goucher-Lambert,K.(2025).How being outvoted by AI teammates impacts human-AI collaboration.International Journal of Human-Computer Interaction,41(7),4049-4066.doi:10.1080/10447318.2024.2345980.
• Huang,L.,Yu,W.J.,Ma,W.T.,Zhong,W.H.,Feng,Z.Y.,Wang,H.T.,Chen,Q.L.,Peng,W.H.,Feng,X.C.,Qin,B.& Liu,T.(2025).A survey on hallucination in large language models:Principles,taxonomy,challenges,and open questions.ACM Transactions on Information Systems,43(2),42.doi:10.1145/3703155.
• Jin,Y.Q.,Martinez-Maldonado,R.,Ga??evi■,L.X.(2025).GLAT:The generative AI literacy assessment test.Computers and Education:Artificial Intelligence,9,100436.doi:10.1016/j.caeai.2025.100436.
• Kim,P.H.,Ferrin,D.L.,Cooper,C.D.& Dirks,K.T.(2004).Removing the shadow of suspicion:The effects of apology versus denial for repairing competence-versus integrity-based trust violations.Journal of Applied Psychology,89(1),104-118.doi:10.1037/0021-9010.89.1.104.
• Kim,P.H.,Dirks,K.T.,Cooper,C.D.& Ferrin,D.L.(2006).When more blame is better than less:The implications of internal vs.external attributions for the repair of trust after a competence-vs.integrity-based trust violation.Organizational Behavior and Human Decision Processes,99(1),49-65.doi:10.1016/j.obhdp.2005.07.002.
• Klingbeil,A.,Gruetzner,C.& Schreck,P.(2024).Trust and reliance on AI — an experimental study on the extent and costs of overreliance on AI.Computers in Human Behavior,160,108352.doi:10.1016/j.chb.2024.108352.
• Kox,E.S.,Kerstholt,J.H.,Hueting,T.F.& De Vries,P.W.(2021).Trust repair in human-agent teams:The effectiveness of explanations and expressing regret.Autonomous Agents and Multi-Agent Systems,35(2),30.doi:10.1007/s10458-021-09515-9.
• Lai,W.N.,Xie,H.R.,Xu,G.D.,Li,Q.& Qin,S.J.(2025,June 2).When LLMs team up:The emergence of collaborative affective computing.arXiv:2506.01698,2025.doi:10.48550/arXiv.2506.01698.
• Langer,M.,K??nig,C.J.,Back,C.& Hemsing,V.(2023).Trust in artificial intelligence:Comparing trust processes between human and automated trustees in light of unfair bias.Journal of Business and Psychology,38(3),493-508.doi:10.1007/s10869-022-09829-9.
• Lee,J.D.& See,K.A.(2004).Trust in automation:Designing for appropriate reliance.Human Factors:The Journal of the Human Factors and Ergonomics Society,46(1),50-80.doi:10.1518/hfes.46.1.50_30392.
• Liu,B.J.(2021).In AI we trust?Effects of agency locus and transparency on uncertainty reduction in human-AI interaction.Journal of Computer-Mediated Communication,26(6),384-402.doi:10.1093/jcmc/zmab013.
• Love,J.,Gronau,Q.F.,Palmer,G.,Eidels,A.& Brown,S.D.(2024).In human-machine trust,humans rely on a simple averaging strategy.Cognitive Research:Principles and Implications,9(1),58.doi:10.1186/s41235-024-00583-5.
• Luhmann,N.(1979).Trust and power.New York:John Wiley and Sons.
• Massenon,R.,Gambo,I.,Khan,J.A.,Agbonkhese,C.& Alwadain,A.(2025).“My AI is lying to Me”:User-reported LLM hallucinations in AI mobile apps reviews.Scientific Reports,15(1),30397.doi:10.1038/s41598-025-15416-8.
• Mayer,R.C.,Davis,J.H.& Schoorman,F.D.(1995).An integrative model of organizational trust.Academy of Management Review,20(3),709-734.doi:10.5465/amr.1995.9508080335.
• Merritt,S.M.& Ilgen,D.R.(2008).Not all trust is created equal:Dispositional and history-based trust in human-automation interactions.Human Factors:The Journal of the Human Factors and Ergonomics Society,50(2),194-210.doi:10.1518/001872008X288574.
• Muir,B.M.& Moray,N.(1996).Trust in automation:II.Experimental studies of trust and human intervention in a process control simulation.Ergonomics,39(3),429-460.doi:10.1080/00140139608964474.
• Park,K.& Young Yoon,H.(2025).AI algorithm transparency,pipelines for trust not prisms:Mitigating general negative attitudes and enhancing trust toward AI.Humanities and Social Sciences Communications,12(1),1160.doi:10.1057/s41599-025-05116-z.
• Peter,S.,Riemer,K.& West,J.D.(2025).The benefits and dangers of anthropomorphic conversational agents.Proceedings of the National Academy of Sciences of the United States of America,122(22),e2415898122.doi:10.1073/pnas.2415898122.
• Roesler,E.,Vollmann,M.,Manzey,D.& Onnasch,L.(2024).The dynamics of human-robot trust attitude and behavior—exploring the effects of anthropomorphism and type of failure.Computers in Human Behavior,150,108008.doi:10.1016/j.chb.2023.108008.
• Romeo,G.& Conti,D.(2026).Exploring automation bias in human-AI collaboration:A review and implications for explainable AI.AI & Society,41(1),259-278.doi:10.1007/s00146-025-02422-7.
• Schaeffer,R.,Miranda,B.& Koyejo,S.(2023).Are emergent abilities of large language models a mirage?.In Proceedings of the 37th International Conference on Neural Information Processing Systems (pp.2425).New Orleans:Curran Associates Inc.
• Steyvers,M.,Tejeda,H.,Kumar,A.,Belem,C.,Karny,S.,Hu,X.Y.,Mayer,L.W.& Smyth,P.(2025).What large language models know and what people think they know.Nature Machine Intelligence,7(2),221-231.doi:10.1038/s42256-024-00976-7.
• Thielsch,M.T.,Mee??en,S.M.& Hertel,G.(2018).Trust and distrust in information systems at the workplace.PeerJ,6,e5483.doi:10.7717/peerj.5483.
• Vaswani,A.,Shazeer,N.,Parmar,N.,Uszkoreit,J.,Jones,L.,Gomez,A.N.,Kaiser,??.& Polosukhin,I.(2017).Attention is all you need.In Proceedings of the 31st International Conference on Neural Information Processing Systems (pp.6000-6010).Long Beach:Curran Associates Inc.
• Wang,L.,Ma,C.,Feng,X.Y.,Zhang,Z.Y.,Yang,H.,Zhang,J.S.,Chen,Z.Y.,Tang,J.K.,Chen,X.,Lin,Y.K.,Zhao,W.X.,Wei,Z.W.& Wen,J.R.(2024).A survey on large language model based autonomous agents.Frontiers of Computer Science,18(6),186345.doi:10.1007/s11704-024-40231-1.
• Wang,W.G.,Gao,G.D.& Agarwal,R.(2023).Friend or foe?Teaming between artificial intelligence and workers with variation in experience.Management Science,70(9),5753-5775.doi:10.1287/mnsc.2021.00588.
• Xu,Y.,Bradford,N.& Garg,R.(2023).Transparency enhances positive perceptions of social artificial intelligence.Human Behavior and Emerging Technologies,2023,550418.doi:10.1155/2023/5550418.
• Yan,Z.,Dong,Y.,Niemi,V.& Yu,G.L.(2013).Exploring trust of mobile applications based on user behaviors:An empirical study.Journal of Applied Social Psychology,43(3),638-659.doi:10.1111/j.1559-1816.2013.01044.x.
• Yankouskaya,A.,Liebherr,M.& Ali,R.(2025).Can ChatGPT be addictive?A call to examine the shift from support to dependence in AI conversational large language models.Human-Centric Intelligent Systems,5(1),77-89.doi:10.1007/s44230-025-00090-w.
• Zerilli,J.,Bhatt,U.& Weller,A.(2022).How transparency modulates trust in artificial intelligence.Patterns,3(4),100455.doi:10.1016/j.patter.2022.100455.
• Zhang,X.Y.,Lee,S.K.,Kim,W.& Hahn,S.(2023).“Sorry,it was my fault”:Repairing trust in human-robot interactions.International Journal of Human-Computer Studies,175,103031.doi:10.1016/j.ijhcs.2023.103031.