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Trust in automation: Part I. Theoretical issues in the study of trust and human intervention in automated systems
Abstract
Today many systems are highly automated. The human operator's role in these systems is to supervise the automation and intervene to take manual control when necessary. The operator's choice of automatic or manual control has important consequences for system performance, and therefore it is important to understand and optimize this decision process. One important determinant of operators' choice of manual or automatic control may be their degree of trust in the automation. However, there have been no experimental tests of this hypothesis until recently, nor is there a model of human trust in machines to form a theoretical foundation for empirical studies. In this paper a model of human trust in machines is developed, taking models of trust between people as a starting point, and extending them to the human-machine relationship. The resulting model defines human trust in machines and specifies how trust changes with experience on a system, providing a framework for experimental research on trust and human intervention in automated systems.
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“Most of the studies investigated how to maintain appropriate trust calibration by continuously presenting system information to prevent over-trust or under-trust.”
From Adaptive trust calibration for human-AI collaboration (2020) · cites this paper as [2]
In the citing paper
“Successful collaborations between users and agents would require the users to appropriately adjust their level of trust with the actual reliability of the agents.”
From Adaptive trust calibration for human-AI collaboration (2020) · cites this paper as [2]
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Items 501–600 of 875
How Events Affect Trust: A Baseline Information Processing Model with Three Extensions
McKnight, D. H., Liu, P., & Pentland, B. T. (2012) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-29852-3_16 · Cited by 9
Altering user’ acceptance of automation through prior automation exposure
Bekier, M., & Molesworth, B. (2017) · Ergonomics · doi:10.1080/00140139.2016.1216610 · Cited by 10
“According to Muir and colleagues, user acceptance of automation is highly dependent on many factors, one of which is trust that the technology will function as expected (Lee and See 2004; Muir 1987, 1994; Wickens and dixon 2007).”
BackgroundNormative vs. Pragmatic: Two Perspectives on the Design of Explanations in Intelligent Systems.
Eiband, M., Schneider, H., & Buschek, D. (2018) · IUI Workshops · Cited by 9
Albayram, Y., Jensen, T., Khan, M. M. H., Buck, R. W., & Coman, E. (2018) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2018.1491665 · Cited by 9
“Muir (Muir, 1994) was one of the first researchers to consider this as an issue of “ trust ” in an automated system.”
BackgroundEdelmann, A., Stümper, S., & Petzoldt, T. (2019) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2019.8814126 · Cited by 9
“Here, experience and knowledge improve trust in automated systems [8], [9], whereas system faults lead to a decreased level of trust.”
BackgroundA model of trust in automation: Why humans over-trust?
Itoh, M. (2011) · Society of Instrument and Control Engineers of Japan · Cited by 9
Steinke, F., Ingenhoff, A., & Fritsch, T. (2014) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2014.903789 · Cited by 9
“As this type designates a human’s trust with a technology or device (Muir, 1994), the main difference to other types of trust is that the trustee, in this case, is a machine.”
BackgroundBonini, D. (2001) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/634067.634327 · Cited by 9
The Effects of Alarm System Errors on Dependence: Moderated Mediation of Trust With and Without Risk
Chancey, E. T. (2016) · ODU Digital Commons (Old Dominion University) · doi:10.25777/34gr-x929 · Cited by 10
“…an association among system error characteristics, dependence behaviors, and trust, theoretically (Cohen et al., 1998, Hoff & Bashir, 2015, Lee & See, 2004, Madhavan & Wiegmann, 2007, Muir, 1987, 1994) and empirically (Chancey et al., 2015a; Lee & Moray, 1992, 1994; Muir, 1996; Wang et al., 2010).”
BackgroundAvetisyan, L., Abolarin, E., Zakarian, V., Yang, X. J., & Zhou, F. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103642 · Cited by 8
Show Me What You Can Do: Capability Calibration on Reachable Workspace for Human-Robot Collaboration
Gao, X., Yuan, L., Shu, T., Lu, H., & Zhu, S. C. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3144779 · Cited by 9
“As human’s estimation of the robot’s capability plays an important part in their trust in the autonomous robot [10], [11], previous works have also studied how capability inference affects human’s trust and reliance on the robot [12], [13], [14].”
Knocton, S., Hunter, A., Connors, W. A., Dithurbide, L., & Neyedli, H. F. (2021) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211021711 · Cited by 8
“(Bagheri & Jamieson, 2004; Lee & See, 2004; Muir, 1994), should lead to more appropriate levels of trust and reliance.”
BackgroundDavid, M. (2021) · Springer eBooks · doi:10.1007/978-3-030-72116-9_13 · Cited by 8
The Delegation-Level Choice of an Automated Vehicle: An Analysis by Structural Equation Modeling
Bel, M., & Cœugnet, S. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2170368 · Cited by 7
“In the literature on sys-tem use, trust is characterized by a psychological state in response to a relationship with an object (Adams et al., 2003; Lee & Moray, 1994; Muir, 1994) because of beliefs or expectations toward an object (Barber, 1983; Pruitt & Rubin, 1986).”
BackgroundExplainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models
Roy, C., Nourani, M., Arya, S., Shanbhag, M., Rahman, T., Ragan, E. D., Ruozzi, N., & Gogate, V. (2023) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3626961 · Cited by 8
“There have been a number of studies on how trust influences interactions between humans and automated systems, e.g., [ 32 , 54 , 69 , 70 ].”
BackgroundHuman mismatches and preferences for automation
Rani, M. R. A., Sinclair, M., & Case, K. (2000) · International Journal of Production Research · doi:10.1080/00207540050204894 · Cited by 8
“Human characteristics may have in¯ uence through subjective self-evaluative characteristics such as self-con® dence (Bandura 1977) and trust (Muir 1994), and be related to work experience (Davies and Sparrow 1985) or age (Robinson et al. 1984).”
BackgroundInformation Waste on the World Wide Web and Combating the Clutter
Amrit, C., Wijnhoven, F., & Beckers, D. (2015) · University of Twente Research Information · doi:10.18151/7217266 · Cited by 8
Ruf, C., & Stütz, P. (2016) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-41959-6_21 · Cited by 8
Towards Self-Adaptive Cyber Deception for Defense
Landsborough, J., Carpenter, L., Coronado, B., Fugate, S. J., Ferguson-Walter, K. J., & Bruggen, D. V. (2021) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2021.244 · Cited by 8
“To best utilize automation in the cyber security domain, it is important to consider several factors including: which information processing stage automation is applied to [24, 25], the ability to adapt to changes in the environment [25, 26], and the level of trust placed on the automation by human operators [27, 28].”
MethodCrawford, J. R., Goh, Y., & Hubbard, E.-M. (2021) · IEEE Access · doi:10.1109/access.2021.3076681 · Cited by 9
“In human-AS and interpersonal trust literature, trust is recognised to have both affective and cognitive features [18]–[20].”
BackgroundTrust and Leadership: Implications of Digitization
Höddinghaus, M., & Hertel, G. (2021) · Springer eBooks · doi:10.1007/978-3-030-72945-5_9 · Cited by 9
Trust and Automation: A Systematic Review and Bibliometric Analysis
Zhang, Z. J., Duffy, V. G., & Tian, R. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90238-4_32 · Cited by 8
Alarcon, G. M., Capiola, A., Morgan, J., Hamdan, I. A., & Lee, M. A. (2022) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2022.082 · Cited by 8
Training Air Traffic Controller Trust in Automation within a NextGen Environment
Higham, T. M., Vu, K. L., Miles, J., Strybel, T. Z., & Battiste, V. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39215-3_9 · Cited by 8
The Role of Mental Models in Using Adaptive Cruise Control
Stanton, N. A., & Young, M. S. (2000) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120004402019 · Cited by 8
“The dependent measures were collected using the following tools: (0 (ii) (iii) (iv) (“1 (vi) (“0 (vii) A multidimensional trust scale based upon Muir (1994) The Locus of Control inventory (LOCI) from Rotter (1966) Driving Internality-Externality (MDIE) scales from Montag & Comrey (1987) A…”
MethodMultimedia-supported virtual experiment for online user–system trust studies
Semsar, A., & Shirehjini, A. A. N. (2017) · Multimedia Systems · doi:10.1007/s00530-016-0519-4 · Cited by 9
Justification and Transparency Explanations in Dialogue Systems to Maintain Human-Computer Trust
Nothdurft, F., & Minker, W. (2016) · Signals and communication technology · doi:10.1007/978-3-319-21834-2_4 · Cited by 8
“However, if the perceived mental model is incongruent to the actual system, actions or reactions of the system that do not match the user’s perceived mental model may decrease human-computer trust [7].”
BackgroundSystem Wide Trust: A Possible Contagion Effect
Mehta, R., & Rice, S. C. (2016) · Collegiate Aviation Review International · doi:10.22488/okstate.18.100465 · Cited by 8
“Studies have shown that the perception of reliability significantly affects a person’ trust in the automation (Lee & See, 2004; Geels-Blair, Rice, & Schwark, 2013; Wiegmann, Rich & Zhang, 2001; Parasuraman & Riley, 1997; Rice, 2009; Muir, 1994; Rice & Geels, 2010; Muir, & Moray, 1996).”
Designing Trust in Highly Virtual : A Taxonomy of Levels of Autonomy
Galdón, F., Hall, A., & Wang, S. (2021) · Studies in computational intelligence · doi:10.1007/978-3-030-61045-6_14 · Cited by 1
Automatic Intelligent Cruise Control
Stanton, N. A., & Young, M. S. (2006) · Journal of Intelligent Systems · doi:10.1515/jisys.2006.15.1-4.357 · Cited by 8
Exploring Trust of Mobile Applications Based on User Behaviors
Yan, Z., Dong, Y. H., Niemi, V., & Yu, G. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-14597-1_13 · Cited by 8
“Muir found a positive correlation between trust and use [ 15 , 16].”
BackgroundLing, S., Zhang, Y., & Du, N. (2024) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208241234810 · Cited by 9
“Trust in the context of automation, which encompasses predictability, dependability, faith, competence, responsibility, and reliability (Muir, 1994), can be effectively calibrated through the careful construction and timely presentation of transparent information during interaction (Chancey et al.,…”
Eitrheim, M. H. R., Nordfjærn, T., Log, M. M., & Tørset, T. (2024) · Journal of Risk Research · doi:10.1080/13669877.2024.2423202 · Cited by 7
“A third item about dependability (Choi and Ji 2015; Muir 1994) was omitted from the survey, as pre-trial testing of the questionnaire revealed difficulties for respondents in discriminating dependability from reliability in the Norwegian language.”
Industrial exoskeletons for secure human–robot interaction: a review
Cheng, D., Hu, B., Feng, Y., Song, X., Zhang, Z., Song, J., Wang, F., & Tan, J. (2024) · International Journal of Intelligent Robotics and Applications · doi:10.1007/s41315-024-00403-5 · Cited by 7
“(3) Psychological factors improving the control system to lessen human fatigue: Prolonged human–robot contact can exhaust wearers, cause attention issues and pressure, impairing operation and accurate decision-making (Park et al. 2008; Lee and Moray 1992; Muir 1994).”
Towards detecting the level of trust in the skills of a virtual assistant from the user’s speech
Gauder, L., Pepino, L., Riera, P., Brussino, S., Vidal, J., Gravano, A., & Ferrer, L. (2023) · Computer Speech & Language · doi:10.1016/j.csl.2023.101487 · Cited by 7
Driving Behavior Analysis: A Human Factors Perspective on Automated Driving Styles
Peintner, J. B., Himmels, C., Rock, T., Manger, C., Jung, O., & Riener, A. (2024) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv55156.2024.10588527 · Cited by 7
“The process of addressing this problem, which aims towards an appropriate level of trust, is called ”calibration of trust” [9].”
BackgroundBuilding Decision Support Systems for Acceptance
Riedel, R., Fransoo, J. C., Wiers, V. C. S., Fischer, K., Cegarra, J., & Jentsch, D. (2010) · Springer eBooks · doi:10.1007/978-3-642-13382-4_11 · Cited by 8
Kaptein, F., Broekens, J., Hindriks, K. V., & Neerincx, M. A. (2019) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2019.8925526 · Cited by 7
“Lack of trust in a behaviour change system causes users to not rely on the given advice [20], and can cause them to misuse or even abandon the system [21].”
BackgroundHuman-Machine Trust and Calibration Based on Human-in-the-Loop Experiment
Wang, Y., Guo, J., Zeng, S., Mao, Q., Lu, Z., & Wang, Z. (2022) · International Conference on System Reliability and Safety Engineering (SRSE) · doi:10.1109/srse56746.2022.10067635 · Cited by 7
“Muir established a human-machine trust model, and extended it to human-machine relations [7].”
BackgroundVerifiably Safe and Trusted Human-AI Systems: A Socio-technical Perspective
Akintunde, M. E., Young, V., Yazdanpanah, V., Fathabadi, A. S., Leonard, P., Butler, M. J., & Moreau, L. (2023) · International Symposium on Trustworthy Autonomous Systems (TAS) · doi:10.1145/3597512.3599719 · Cited by 7
“[81] •Muir & Moray [60] •Metcalfe [57] •Muir [59] •Hoff & Bashir [37] • Parasuraman & Riley [68] • Lee & See [52] •Hou [39] • Parasuraman [69] • Lee & Moray [50, 51] •Kaber & Endsley [45] •Onnasch et al.”
Shall I Trust a Recommendation? Towards an Evaluation of the Trustworthiness of Recommender Sites
Lenzini, G., van Houten, Y., Huijsen, W., & Melenhorst, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12082-4_16 · Cited by 7
“In other words, trust is the intervening variable that directly affects the use of a certain technology [ 17 ].”
BackgroundUncertainty Visualization for Mobile and Wearable Devices Based Activity Recognition Systems
Dong, M., Chen, L., Wang, L., Jiang, X., & Chen, G. (2016) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2016.1224527 · Cited by 7
Hitting the Road: Exploring Human-Robot Trust for Self-Driving Vehicles
Razin, Y. S., & Feigh, K. M. (2020) · IEEE International Conference on Human-Machine Systems (ICHMS) · doi:10.1109/ichms49158.2020.9209525 · Cited by 7
An experimental investigation of human mismatches in machining
Case, K., Sinclair, M., & Rani, M. R. A. (1999) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1243/0954405991517362 · Cited by 7
Affect and Trust in Technology in Teams
Xu, J., & Montague, E. N. H. (2015) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931215591042 · Cited by 7
“In addition, an individual’s trust in technology may also influence his/her trust in other elements of the system, such as interpersonal trust and institutional trust (Muir, 1994).”
BackgroundEXPLORING THE IMPACT OF A CONTEXT-AWARE APPLICATION FOR IN-CAR USE
Olsson, C. M. (2004) · Journal of the Association for Information Systems · Cited by 7
Evaluation Methods and Techniques for ELearning Software for School Students in Primary Stages
Odeh, S., & Qaraeen, O. (2007) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 7
Modeling and Adding Intelligibility to Human Activity
Dey, A. K. (2008) · International Symposium on Ubiquitous Virtual Reality · doi:10.1109/isuvr.2008.25 · Cited by 7
“One of the biggest challenges to the usability of context-aware applications is the difficulty of understanding why they do what they do. The lack of intelligibility of an application can be a serious issue that may lead to application failure or abandonment due to lack of trust [ 10 ] in the system.”
BackgroundTrust-Aware Planning: Modeling Trust Evolution in Longitudinal Human-Robot Interaction.Preprint
Zahedi, Z., Verma, M., Sreedharan, S., & Subbarao Kambhampati, B. (2021) · arXiv (Cornell University) · Cited by 7
Help me make a dinner! Challenges when assisting humans in action planning
Behnke, G., Leichtmann, B., Bercher, P., Holler, D., Nitsch, V., Baumann, M., & Biundo, S. (2017) · 2017 International Conference on Companion Technology (ICCT) · doi:10.1109/icct42709.2017.9151907 · Cited by 7
“[38] B.”
BackgroundCui, Z.-X., Zhuang, X.-L., Lee, S. C., Lee, J., Li, X.-T., & Itoh, M. (2025) · Applied Ergonomics · doi:10.1016/j.apergo.2025.104477 · Cited by 7
A Conceptual Framework for User Trust in AI Biosensors: Integrating Cognition, Context, and Contrast
Prahl, A. (2025) · Sensors · doi:10.3390/s25154766 · Cited by 6
“Historically, trust research distinguished between interpersonal trust among humans and trust in automation or machine aids [20,25,26].”
Decoding trust in large language models for healthcare in Saudi Arabia
Alelyani, T. (2025) · Scientific Reports · doi:10.1038/s41598-025-18404-0 · Cited by 11
“Studies show that patients are more likely to adhere to AI-driven treatment plans if they trust the system’s recommendations 6,7 .”
Tan, H., & Hao, Y. (2023) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.21001 · Cited by 5
“Predictability is usually perceived through the consistency and desirability of the machine's repeated behaviors (Muir, 1994), which is regarded as the dominant predictor of trust (Muir & Moray, 1996).”
BackgroundInfluentialInteracting with Adaptive Systems
Evers, V., Cramer, H. S. M., van Someren, M., & Wielinga, B. J. (2010) · Studies in computational intelligence · doi:10.1007/978-3-642-11688-9_11 · Cited by 6
“Users have to calibrate their level of trust and their level of reliance on the system to its capabilities [42][ 52 ][53].”
BackgroundInfluentialAre households ready to engage with smart home technology?
Mulcahy, R. F., Letheren, K., McAndrew, R., Glavas, C., & Russell‐Bennett, R. (2022) · Routledge eBooks · doi:10.4324/9781003307105-2 · Cited by 6
Calibration of Trust in Autonomous Vehicle
Lee, S. C., & Ji, Y. G. (2022) · Automation, collaboration, and e-services · doi:10.1007/978-3-031-10784-9_16 · Cited by 6
I’m Only Human: The Effects of Trust Dampening by Anthropomorphic Agents
Jensen, T., & Khan, M. M. H. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-21707-4_21 · Cited by 6
Embodying a Virtual Agent in a Self-Driving Car
Lawson-Guidigbe, C., Louveton, N., Amokrane, K., Blanc, B. L., & André, J. (2023) · International Journal of Mobile Human Computer Interaction · doi:10.4018/ijmhci.330542 · Cited by 6
“It has also been defined as a part of an individual personality that drives one to believe another party is reliable (Muir, 1994).”
Performance-Aware Trust Modeling within a Human–Multi-Robot Collaboration Setting
Rabby, M. K. M., Khan, M. A., Jiang, S. X., & Karimoddini, A. (2024) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3660648 · Cited by 6
“Inspired by the need for a quantitative explanation of developed trust over time, this research focuses on mathematical models for human trust in robot operation.”
BackgroundMethodInfluentialBusch, P. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100490 · Cited by 11
Experimental Investigation of Calibration and Resolution in Human-Automation System Interaction
Maehigashi, A., Miwa, K., Terai, H., Kojima, K., & Morita, J. (2013) · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · doi:10.1587/transfun.e96.a.1625 · Cited by 6
Theoretical Issues in the Study of Trust in Human-Computer Interaction
Yan, Z., Kantola, R., & Zhang, P. (2011) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom.2011.114 · Cited by 6
Generation of human computational models with knowledge engineering
Campuzano, F., García-Valverde, T., Serrano, E., & Botía, J. A. (2014) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2014.06.027 · Cited by 6
Does The First Officer Concur? Shared Control with Smart Vehicle Systems
Miller, D., & Ju, W. G. (2014) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/2667239.2667286 · Cited by 6
Measurement of Human Trust in a Hybrid Inspection for Varying Error Patterns
Madhani, K., Khasawneh, M. T., Kaewkuekool, S., Gramopadhye, A. K., & Melloy, B. J. (2002) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120204600343 · Cited by 6
“…tried to construct a comprehensive framework to describe, explain, and predict human behavior in an automated task, with research showing that a key factor in defining human behavior may be the operator's trust in automation (Muir, 1987; Muir, 1994; Sheridan and Hennessy, 1984; Muir et al., 1996).”
BackgroundInfluentialInvestigating users’ mental representation of likelihood alarm systems with different thresholds
Wiczorek, R. (2016) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2016.1207209 · Cited by 6
“Common trust theories differ with regard to several assumptions but almost every concept incorporates the relevance of reliability (e.g. Lee and Moray 1992; Muir 1994; Madsen and Gregor 2000; Bisantz and Seong 2001; Madhavan and Wiegman 2004).”
BackgroundEdwards, T. E., & Lee, P. U. (2017) · AIAA Aviation Technology, Integration, and Operations Conference (ATIO) · doi:10.2514/6.2017-4487 · Cited by 6
Damen, N. B., & Toh, C. A. (2017) · ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE) · doi:10.1115/detc2017-68349 · Cited by 7
Building Trust in Social Robotics: A Pilot Survey
Campanozzi, L. L., Guglielmelli, E., Cella, E., Ghilardi, G., Michilli, M., Molina, A., Ciccozzi, M., & Tambone, V. (2019) · IEEE Technology and Society Magazine · doi:10.1109/mts.2019.2948440 · Cited by 6
Effects of Reliance Support on Team Performance by Advising and Adaptive Autonomy
van Maanen, P.-P., Wisse, F., van Diggelen, J., & Beun, R. J. (2011) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat.2011.117 · Cited by 6
“1) Team Performance: Due to the fact that there is a positive relation between appropriate trust and reliance for the performance of humans supported by decision aids, and that appropriate trust is something often not trivial in hybrid team collaborative tasks [2], [3], [4], [5], [6], it is expected that both the grap…”
BackgroundAnalyses of the Concept of Trust in Information Fusion and Situation Assessment
Atoyan, H., & Shahbazian, E. (2009) · NATO science for peace and security series. C, Environmental security · doi:10.1007/978-1-4020-8883-4_21 · Cited by 6
Bustamante, E. A. (2005) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120504901702 · Cited by 6
A systematic review and meta-analysis of age-related differences in trustPreprint
Bailey, P. E., & Leon, T. (2019) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/we7vh · Cited by 10
Confiance interpersonnelle et communications de travail
Karsenty, L. (2011) · Le travail humain · doi:10.3917/th.742.0131 · Cited by 45
Hollander, C., Hartwich, F., & Krems, J. F. (2022) · Open Psychology · doi:10.1515/psych-2022-0124 · Cited by 5
Gibbard, K., Gill, H., Powell, D. M., & Hausdorf, P. A. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2506664 · Cited by 7
“Trust is crucial for employees to adopt and use AI in the workplace (Hasija and Esper 2019), and users’ trust can decrease if they do not understand a system’s actions (Muir 1994).”
Need for Trust Calibration in Takeover request Performance in Level 3 Automated vehicles
Jui, J. J., Hettiarachchi, I. T., & Mohajer, N. (2025) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3744333.3747816 · Cited by 6
“The dispositional dimension explains why some users inherently resist automation while others readily adopt it, with meta-analyses showing significant correlations with demographic factors [57].”
Arnestad, M. N., Bigman, Y., Solberg, E. A., & Gray, K. J. (2025) · International Journal of Selection and Assessment · doi:10.1111/ijsa.70028 · Cited by 10
Kaufmann, E., & Chacon, A. (2026) · Cognitive Systems Research · doi:10.1016/j.cogsys.2026.101462 · Cited by 3
Sato, T., Inman, J., Politowicz, M. S., Chancey, E. T., & Yamani, Y. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231194326 · Cited by 5
“Building on earlier works on interpersonal trust (Barber, 1983; Rempel et al., 1985) and human-automation trust (Muir, 1994; Muir & Moray, 1996), trust is often conceptualized as an attitude that evolves based on information on the automation’s behavior (i.e., performance), the automation’s…”
BackgroundQian, X., Wang, T., Xu, X., Jonker, T. R., & Todi, K. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642158 · Cited by 5
“When such automation policies behave unexpectedly, users can lose trust and abandon these systems [64].”
BackgroundThe Impact of Confidence Ratings on User Trust in Large Language Models
Wang, L., Friedman, N., Zhu, C., Zhu, Z., & Mountford, S. J. (2025) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3708319.3734178 · Cited by 5
“Seminal work done by Muir [11] found a positive correlation be-tween the level of user trust and the user’s delegated level of control to the system.”
A qualitative evaluation criterion for human-robot interaction system in achieving collective tasks
Saleh, J. A., Karray, F. O., & Morckos, M. (2012) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzz-ieee.2012.6251313 · Cited by 5
Determinants of Trust in Acceptance of Medical Assistive Technologies
Wilkowska, W., & Ziefle, M. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-15736-4_3 · Cited by 5
The uncertain advisor: trust, accuracy, and self-correction in an automated decision support system
Lochner, M., & Smilek, D. (2022) · Cognitive Processing · doi:10.1007/s10339-022-01113-1 · Cited by 4
“The available studies (see French et al. 2018) have tackled a wide range of issues, including the relevance of interpersonal trust (Muir 1994), fault management (Lee and Moray 1992), the role of decision aids (Cohen et al. 1997), automation in a military context (Adams et al. 2003), and automation…”
BackgroundThe Interaction Gap: A Step Toward Understanding Trust in Autonomous Vehicles Between Encounters
Hunter, J. G., Konishi, M., Jain, N., Akash, K., Wu, X., Misu, T., & Reid, T. (2022) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181322661311 · Cited by 5
“Trust in automation or autonomous vehicles is not a new topic; however, despite three decades of research on this topic (Muir, 1994; Lee and See, 2004; Hoff and Bashir, 2015), few studies have investigated changes in human trust due to multiple distinct interactions with an automated system.”
BackgroundGroup Polarization of Trust in Technology
Xu, J., & Montague, E. N. H. (2013) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213571075 · Cited by 5
“An individual's trust in technology also may influence his/her trust in other elements of the system, such as the organization or collaborators (Montague & Lee, 2012; Muir, 1994).”
BackgroundVega, L. C., Montague, E. N. H., & DeHart, T. (2010) · International Health Informatics Symposium · doi:10.1145/1882992.1883100 · Cited by 5
Dolgov, I., & Kaltenbach, E. K. (2017) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601799 · Cited by 8
Automated Systems and Trust: Mineworkers' Trust in Proximity Detection Systems for Mobile Machines
Swanson, L. R., Bellanca, J. L., & Helton, J. (2019) · Safety and Health at Work · doi:10.1016/j.shaw.2019.09.003 · Cited by 5
Human-automation teamwork : Current practices and future directions in air traffic control
Svensson, Å. (2020) · Linköping studies in science and technology. Dissertations · doi:10.3384/diss.diva-164303 · Cited by 5
“The research around automation has also focused on trust (Muir, 1994; Bonini, Jackson, & McDonald, 2001; Eurocontrol, 2003; de Visser et al., 2016), conformance (C. Westin, Borst, & Hilburn, 2016), complacency (Parasuraman, Molloy, & Singh, 1993; Parasuraman & Manzey, 2010), and transparency…”
Pedestrians-Automated Vehicles Interaction: Toward a Specific Trust Model?
Bonneviot, F., Cœugnet, S., & Brangier, É. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-74608-7_69 · Cited by 5
Dynamics of Trust in Automation and Interactive Decision Making during Driving Simulation Tasks
Rodriguez, L. R., Bustamante-Orellana, C., Landfair, J. T., Magaldino, C., Demir, M., Amazeen, P. G., Metcalfe, J. S., Huang, L., & Kang, Y. (2021) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181321651288 · Cited by 5
“An extremely high level of trust will result in a complacent operator who fails to take control even when the automation is unable to perform a given task successfully, such as avoiding a pedestrian (Sheridan & Hennessy, 1984; Muir, 1994).”
BackgroundResultInfluentialKraus, M., Riekenbrauck, R., & Minker, W. (2023) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3563359.3597403 · Cited by 5
“Previous research on trust has identified various user-, system-, and context-related factors that influence the trust relationship [7, 20, 27, 28].”
BackgroundChromik, M., Fincke, F., & Butz, A. M. (2020) · ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS) · doi:10.1145/3393672.3398491 · Cited by 5
Liu, C.-L., & Su, K.-W. (2006) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.20056 · Cited by 5
“Besides discussion on SA, some researchers have reported that trust is a key point (Lee & Moray, 1994; Muir, 1987, 1994, 1996).”
BackgroundEffect of Error Severity on Human Trust in Hybrid Systems
Khasawneh, M. T., Bowling, S. R., Jiang, X., Gramopadhye, A. K., & Melloy, B. J. (2004) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120404800335 · Cited by 5
Behavioural Adaptation to In-Vehicle Safety Measures
Brown, C. M., & Noy, Y. I. (2004) · Elsevier eBooks · doi:10.1016/b978-008043925-9/50003-7 · Cited by 5
Agents and Decision Support Systems
Tolk, A., Madhavan, P., Tweedale, J. W., & Jain, L. C. (2009) · Wiley eBooks · doi:10.1002/9783527627783.ch14 · Cited by 5
Metadata
- Authors
- MUIR, B. M.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- MUIR, BONNIE M.
- Venue
- Ergonomics
- Publisher
- Informa UK Limited
- Published
- 1994-11
- Volume
- 37
- Issue
- 11
- Pages
- 1905-1922
- ISSN
- 0014-0139 (ISSN-L)
- 1366-5847
- OpenAlex
- W2032426551
- Cited by
- 873
- References
- 49
- Citations by year
- 2026: 33 · 2025: 52 · 2024: 46 · 2023: 41 · 2022: 51 · 2021: 72 · 2020: 60 · 2019: 44 · 2018: 50 · 2017: 36 · 2016: 46 · 2015: 17 · 2014: 29 · 2013: 26 · 2012: 27
- FWCI
- 2.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ergonomics (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- trust in automation, human-machine trust, human intervention, manual control, automated systems, operator decision-making, trust model, human oversight
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