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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]
Citations
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“In comparison to the static trust models in [14], [28], [29], the proposed model is able to capture the trust in a dynamic way.”
BackgroundResultSchmidt, T., Philipsen, R., & Ziefle, M. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-20376-8_51 · Cited by 18
Khastgir, S., Birrell, S. A., Dhadyalla, G., & Jennings, P. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-93885-1_37 · Cited by 15
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Jacobs, G., & Rodgers, C. (1999) · CALICO Journal · doi:10.1558/cj.v16i4.509-529 · Cited by 15
“Muir (1994) has proven that the level of trust in a computer is directly related to the extent to which it has consistently demonstrated superior performance.”
BackgroundAdaptive Automation: Building Flexibility into Human-Machine Systems☆
Dzindolet, M. T., Beck, H. P., & PIERCE, L. (2005) · Advances in human performance and cognitive engineering research · doi:10.1016/s1479-3601(05)06007-8 · Cited by 15
Theoretical issues in the design of visual inspection systems
Jiang, X., Gramopadhye, A. K., & Melloy, B. J. (2004) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922021000050005 · Cited by 15
“For example, if an operator trusts the automation too much, he/she may become complacent and fail to override the automation when it is faulty (Muir 1994).”
BackgroundMethodWhy Trust Is Hard – Challenges in e-Mediated Services
Rindebäck, C., & Gustavsson, R. (2005) · Lecture notes in computer science · doi:10.1007/11532095_11 · Cited by 15
“An implicit trust condition is that an artifact or tool is not behaving in an unexpected or undesired way by its design [ 3 ].”
MethodTwenty Software Requirement Patterns to Specify Recommender Systems that Users Will TrustPreprint
Hoffmann, A., Söllner, M., & Hoffmann, H. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2484462 · Cited by 15
“We supplemented the list by the antecedents collected by Lee and See (2004) and antecedents suggested by Muir (Muir, 1994) to have a good groundwork for the software requirements pattern.”
How Do Visual Explanations Foster End Users' Appropriate Trust in Machine Learning?Preprint
Yang, F. (2021) · doi:10.31219/osf.io/s9q8t · Cited by 18
Meeßen, S. M., Thielsch, M. T., Riehle, D. M., & Hertel, G. (2020) · Ergonomics · doi:10.1080/00140139.2020.1758797 · Cited by 16
“Indeed, uncritical trust (or overtrust) in technology can be dangerous in time-and safety-critical contexts because it can support misuse (Muir 1987, 1994; Lee and See 2004; Parasuraman and Riley 1997; Parasuraman and Wickens 2008).”
BackgroundMethodResultInfluentialDisentangling Trust and Anthropomorphism Toward the Design of Human-Centered AI Systems
Jensen, T. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77772-2_3 · Cited by 16
Faulhaber, A. K., Ni, I., & Schmidt, L. (2021) · Mensch und Computer (MuC) · doi:10.1145/3473856.3473886 · Cited by 16
“Particularly trust in automation has been a topic of interest in the past decades [e.g., 17, 18, 27, 37, 38, 48].”
BackgroundMultimodal Warnings Design for In-Vehicle Robots under Driving Safety Scenarios
Wang, J., Wang, C., Liu, Y., Yue, T., Wang, Y., & You, F. (2022) · Sensors · doi:10.3390/s23010156 · Cited by 14
“Muir [55] proposed a trust-based model for vehicle automation that includes three trust dimensions: predictability, dependability, and loyalty.”
BackgroundZahedi, Z., Verma, M., Sreedharan, S., & Subbarao Kambhampati, B. (2023) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3568162.3578628 · Cited by 14
“At the end of each round, a four-item trust scale of Muir questionnaire [22] is given to them, which measures their”
MethodSato, T., Inman, J., Politowicz, M. S., Chancey, E. T., & Yamani, Y. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231194333 · Cited by 15
“The literature indicates evidence for trust as a critical factor driving human-automation interaction (Chancey et al., 2017; Hoff & Bashir, 2015; Karpinsky et al., 2018; Lee & See, 2004; Muir, 1994; Muir & Moray, 1996; Sato et al., 2020, 2022; Yamani et al., 2020).”
BackgroundLawson-Guidigbe, C., Amokrane, K., Louveton, N., Blanc, B. L., Rousseaux, V., & André, J. (2023) · Machines · doi:10.3390/machines11121087 · Cited by 16
Weber, R. O., Johs, A. J., Goel, P., & Marques-Silva, J. P. (2024) · AI Magazine · doi:10.1002/aaai.12184 · Cited by 23
Wang, S., & Jiao, J. R. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-14890-0 · Cited by 14
“Moreover, human trust can be a dynamic value influenced by the discrepancy between what operators observe and what they expect from the automation agent [51] making it necessary to formulate trust as a dynamic process [25, 40].”
A novel digital twins-driven mutual trust framework for human–robot collaborations
Li, J., Zhu, E., Lin, W., Yang, S. X., & Yang, S. L. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.04.009 · Cited by 17
Towards a Personalized Trust Model for Highly Automated Driving
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Challenges in Partially Automated Driving : A Human Factors Perspective
Marcos, I. S. (2018) · Linköping studies in behavioural science · doi:10.3384/diss.diva-147764 · Cited by 14
Investigating Trust in Interaction with Inconsistent Embodied Virtual Agents
Moradinezhad, R., & Solovey, E. (2021) · International Journal of Social Robotics · doi:10.1007/s12369-021-00747-z · Cited by 14
Hall, S., & McQuay, W. (2010) · Proceedings of the IEEE 2010 National Aerospace & Electronics Conference · doi:10.1109/naecon.2010.5712918 · Cited by 14
“Another definition in the automation literature is given by [8] and it states that trust is constructed as an ‘intervening’ variable, residing in the mind, which mediates responses to environmental stimuli.”
BackgroundEkman, F., Johansson, M., & Sochor, J. (2016) · Nordic Conference on Human-Computer Interaction · doi:10.1145/2971485.2971551 · Cited by 15
Trust of Simulated Robotic Peacekeepers among Resident and Expatriate Americans
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Biros, D. P., Fields, G. S., & Gunsch, G. H. (2003) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2003.1173894 · Cited by 14
Driver Confidence and Level of Automation Influencing Trust in Automated Driving Features
Miele, D., Ferraro, J. C., & Mouloua, M. (2021) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181321651300 · Cited by 14
“Therefore, evaluating trust levels when interacting with a new type of automation can be beneficial, as all automation behaves in different manners, and trust should not be generalized (Muir, 1994).”
BackgroundInteraction strategies with advanced driver assistance systems
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FortClash: Predicting and Mediating Unintended Behavior in Home Automation
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“This can be frustrating [9, 47] and cause users to lose trust [5, 58].”
BackgroundBonneviot, F., Cœugnet, S., & Brangier, É. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1129341 · Cited by 16
“These behaviors observed in human–computer interaction are considered comparable to the trusting behaviors observed in human–human relationships (Muir, 1994).”
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Formalizing Trust Based on Usage Behaviours for Mobile Applications
Yan, Z., & Rong, Y. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02704-8_15 · Cited by 13
“She verifies the hypothesis that the supervisor’s intervention behavior is based upon his/her trust in automation [ 4 , 17].”
BackgroundTutul, A. A., Nirjhar, E. H., & Chaspari, T. (2021) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3462244.3479926 · Cited by 15
“Individuals and stake-holders need to calibrate their trust on the algorithms that power the decision making process in such human-centered applications, which tend to be subjective and involve high stakes [14, 20].”
BackgroundThe Relationship of Self-Efficacy and Complacency in Pilot-Automation Interaction
Prinzel, L. J. (2002) · NASA STI Repository (National Aeronautics and Space Administration) · Cited by 13
Rajaonah, B. (2017) · Ingénierie des systèmes d information · doi:10.3166/isi.22.1.109-133 · Cited by 13
“Once interactions between trustors and trustees are established, good reasons-based trust is built from facts, relying on trustors’ trial and error experience, understanding of the trustees’ characteristics, predictability and limits, etc. (e.g., Lewicki and Bunker, 1996; Muir, 1994; Numan, 1998).”
BackgroundMethodTrust View from the Human-Machine Cooperation Framework
Itoh, M., & Pacaux‐Lemoine, M. (2018) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2018.00544 · Cited by 13
“The built up trust is close to the notion of “dependability, predictability” again proposed by Muir [3].”
BackgroundA roadmap for developing team trust metrics for human-autonomy teams
Schaefer, K. E., Perelman, B. S., Gremillion, G. M., Marathe, A., & Metcalfe, J. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-819472-0.00012-5 · Cited by 13
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Explainable activity recognition in videos: Lessons learned
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“…as influenced by system reliability, is a major factor in user attitudes toward automation use (Wickens & Hollands, 2000; Parasuraman, et al, 2000; Parasuraman & Riley, 1997; Moray, et al, 2000; Muir, 1994; Muir & Moray, 1996; Skitka, Mosier, & Burdick, 1999; Lee & Moray, 1992; Lee & Moray, 1994).”
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“Trust is generally defined as the belief or expectation that a person or a system will perform as intended, reliably and accurately, and in the best interest of the operator (Muir, 1994).”
Dong, X., Cappuccio, M. L., Alnajjar, F., Ali, L., Jassmi, H. A., Debie, E., Ghasrikhouzani, M., Lanteri, A., McGregor, T., Molloy, О., et al. (2025) · Journal of Field Robotics · doi:10.1002/rob.70108 · Cited by 30
A conceptual model of HRIS‐Trust: an understanding of suppliers'/customers' relationship
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Design of Proactive Interaction for In-Vehicle Robots Based on Transparency
Wang, J., Yue, T., Liu, Y., Wang, Y., Wang, C., Yan, F., & You, F. (2022) · Sensors · doi:10.3390/s22103875 · Cited by 12
“The trust scores in the study were based on the model of trust in vehicle automation proposed by Muir [35], using a post-task trust scale with a comprehensive analysis of three trust dimensions: predictability, dependability, and faith.”
MethodGEEDI - Guards for Emotional and Explanatory DIalogues
Nothdurft, F., Bertrand, G., Heinroth, T., & Minker, W. (2010) · International Conference on Intelligent Environments (IE) · doi:10.1109/ie.2010.24 · Cited by 12
Modelling of robot attention demand in human-robot interaction using finite fuzzy state automata
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“Trust in automation has been extensively discussed in the literature by many researchers, especially in the fields of human-machine interaction [9], [10], [2], [4].”
BackgroundDriver's Trust in Automted Driving when Passing Other Traffic Objects
Abe, G., Sato, K., & Itoh, M. (2015) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2015.165 · Cited by 12
Human Trust in Robot Capabilities across Tasks
Shu, P., Chen, M., Bodala, I. P., Nikolaidis, S., Hsu, D., & Soh, H. (2018) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3173386.3177034 · Cited by 12
“, the human’s technical expertise and the complexity of the automation [4].”
BackgroundMosier, K. L., Fischer, U. M., Burian, B. K., & Kochan, J. A. (2017) · NASA STI Repository (National Aeronautics and Space Administration) · doi:10.13140/rg.2.2.25859.60966 · Cited by 14
Understanding Trust in Automated Vehicles
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Vance, A., Lowry, P. B., & Wilson, D. W. (2015) · Security Journal · doi:10.1057/sj.2015.22 · Cited by 12
“…characteristics such as agency (Friedman and Millett, 1997); personality; friendliness and helpfulness (Reeves and Nass, 1996); morality and responsibility (Muir, 1987, 1994; Muir and Moray, 1996); and, it is argued, benevolence and credibility (Cassell and Bickmore, 2000; Wang and Benbasat, 2005).”
Pushparaj, K., Ky, G. A., Ayeni, A. J., Alam, S., & Dương, V. (2021) · Journal of Air Transport Management · doi:10.1016/j.jairtraman.2021.102143 · Cited by 14
Long, S. K., Lee, J., Yamani, Y., Unverricht, J. R., & Itoh, M. (2022) · Applied Ergonomics · doi:10.1016/j.apergo.2021.103674 · Cited by 11
Human-agent interaction in a target identification task
Lenox, T. L., Roberts, L., & Lewis, M. (2002) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.1997.635346 · Cited by 12
Madhavan, P., & Wiegmann, D. A. (2005) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120504900358 · Cited by 12
“This concept of automation trust, in general, has been the focus of a vast body of research over the last decade (e.g. Muir, 1994; Lee & Moray, 1992; Lerch, Prietula & Kulik, 1997; Lee & See, 2004).”
Chang, W.-C., Ryan, S. M., Hasanzadeh, S., & Esmaeili, B. (2023) · Computing in construction · doi:10.35490/ec3.2023.205 · Cited by 13
Multilevel Confirmatory Factor Analysis Reveals Two Distinct Human–Automation Trust Constructs
Yamani, Y., Long, S. K., Sato, T., Braitman, A. L., Politowicz, M. S., & Chancey, E. T. (2024) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208241263774 · Cited by 11
“…growing, and maintaining successful human-automation interactions (Chen & Barnes, 2014; Lee et al., 2021; Lee & Moray, 1992, 1994; Long et al., 2020, 2022; Lyons & Stokes, 2012; Moray et al., 2000; Muir, 1994; Muir & Moray, 1996; Parasuraman & Riley, 1997; Riley, 1994; Yamani et al., 2020).”
Effects of Demographic Characteristics on Trust in Driving Automation
Lee, J., Abe, G., Sato, K., & Itoh, M. (2020) · Journal of Robotics and Mechatronics · doi:10.20965/jrm.2020.p0605 · Cited by 11
More Than Accuracy: Towards Trustworthy Machine Learning Interfaces for Object Recognition
Heuer, H., & Breiter, A. (2020) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3340631.3394873 · Cited by 11
“evaluate their visualizations in user tests and does not compare their visualizations to basic visualizations [29, 32]. In this paper, we focus on trust in intelligent systems [17, 42] and automation [21, 27, 28] in the context of object recognition. arXiv:2008.01980v1 [cs.HC] 5 Aug 2020 Heuer and Breiter Convolutiona…”
BackgroundTrust Miscalibration Is Sometimes Necessary: An Empirical Study and a Computational Model
Collins, M. G., & Juvina, I. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.690089 · Cited by 12
“Miscalibrated (i.e., over-or under-) trust has been thought to only have negative consequences, e.g., over-reliance and under-utilization (Muir, 1994; Parasuraman and Riley, 1997; Lee and See, 2004; Robinette et al., 2016; Okamura and Yamada, 2020).”
BackgroundSato, T., Islam, S., Still, J. D., Scerbo, M. W., & Yamani, Y. (2022) · Cognition Technology & Work · doi:10.1007/s10111-022-00717-z · Cited by 11
“Trust is a critical factor for successful human–automation interaction (Hoff and Bashir 2015; Lee and Moray 1992; Lee et al. 2021; Long et al. 2022; Lyons and Stokes 2012; Muir 1994; Muir and Moray 1996; Schaefer et al. 2016; Paras-uraman and Riley 1997; Yamani et al. 2020).”
BackgroundHuman and automation: a matter of cooperation.
Hoc, J. (2007) · HAL · Cited by 11
Calibrating trust to integrate intelligent agents into human teams
Sycara, K. P., Lewis, M., Lenox, T. L., & Roberts, L. (2002) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.1998.653107 · Cited by 11
Integrating Trust in Automation into Driver State Monitoring Systems
Perello-March, J. R., Burns, C. G., Elliott, M. T., & Birrell, S. A. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-25629-6_53 · Cited by 11
Improving trust in data and algorithms in the medium of AI
Srinivasan, A. V., & de Boer, M. (2020) · Maandblad Voor Accountancy en Bedrijfseconomie · doi:10.5117/mab.94.49425 · Cited by 13
“Muir (1994) initially developed a trust model in automation, and it was primarily based on the work done on trust in interpersonal relationships by Rempel et al. (1985), as the model closely ties with the theoretical basis of trust foundation.”
MethodAdaptive Explanation Architecture for Maintaining Human-Computer Trust
Nothdurft, F., Bertrand, G., Lang, H., & Minker, W. (2012) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac.2012.28 · Cited by 11
Evaluating the Effects of Situation Awareness and Trust With Robust Design in Automation
Liu, C.-L., & Hwang, S. (2000) · International Journal of Cognitive Ergonomics · doi:10.1207/s15327566ijce0402_3 · Cited by 11
Should We Trust (X)AI? Design Dimensions for Structured Experimental EvaluationsPreprint
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“She collected multiple definitions of trust in humans, showcasing the different aspects of trust and suggesting that “trust is a multidimensional construct” [52] and that calibration and re-calibration of trust are necessary over time.”
Nordhoff, S., & Hagenzieker, M. (2024) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.09.021 · Cited by 10
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The Authority Issue in Organizational Automation
Boy, G. A., & Grote, G. (2017) · CRC Press eBooks · doi:10.1201/9781315557380-7 · Cited by 10
“In the system design literature, however, trust is often understood as a desirable user attitude based on familiarity with the system and confidence stemming from high transparency, predictability, and reliability of systems, thereby actually providing essential prerequisites for control (Lee & See, 2004; McGuirl & Sa…”
BackgroundDynamic high-level requirements in self-adaptive systems
Rossi, D., Poggi, F., & Ciancarini, P. (2018) · ACM Symposium on Applied Computing · doi:10.1145/3167132.3167143 · Cited by 10
Kim, H. (2019) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2019.07.014 · Cited by 11
Trust in Clinical AI: Expanding the Unit of Analysis
Browne, J., Bakker, S., Yu, B., Lloyd, P. A., & Allouch, S. B. (2022) · Frontiers in artificial intelligence and applications · doi:10.3233/faia220192 · Cited by 10
Explainable Activity Recognition in Videos.
Roy, C., Shanbhag, M., Nourani, M., Rahman, T., Kabir, S., Gogate, V., Ruozzi, N., & Ragan, E. D. (2019) · IUI Workshops · Cited by 10
Clustering Human Trust Dynamics for Customized Real-Time Prediction
Liu, J.-D., Kumar, A., Misu, T., & Wu, X. (2021) · International Conference on Intelligent Transportation Systems · doi:10.1109/itsc48978.2021.9565016 · Cited by 19
“As an alternative, recent works have developed dynamic models to capture human trust and estimate it in real-time [13], [14], [15], [9].”
BackgroundAlarcon, G. M., & Willis, S. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.134 · Cited by 10
Lippert, S. K. (2007) · International Journal of Information Technology and Management · doi:10.1504/ijitm.2008.015888 · Cited by 10
Driver's trust in automated driving when sharing of spatial awareness
Sonoda, K., & Wada, T. (2016) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2016.7844618 · Cited by 10
“These estimations or feelings would determine automation usage [20], [21], [22].”
BackgroundDeciding when to trust automation in a policy-based city management game
Oduor, K. F., & Campbell, C. S. (2007) · Computer Human Interaction for Management of Information Technology · doi:10.1145/1234772.1234775 · Cited by 10
3. Operators' automation usage decisions and the sources of misuse and disuse
Beck, H. P., Dzindolet, M. T., & PIERCE, L. (2002) · Advances in human performance and cognitive engineering research · doi:10.1016/s1479-3601(02)02005-2 · Cited by 10
The Effect of Road Transport Telematics
Nilsson, L., Harms, L., & Peters, B. (2001) · Springer eBooks · doi:10.1007/978-1-4757-6867-1_14 · Cited by 10
Building Trust in Assistive Robotics: Insights From a Real-World Mobile Navigation Experiment
Lingg, N., & Demiris, Y. (2023) · International Symposium on Trustworthy Autonomous Systems (TAS) · doi:10.1145/3597512.3597519 · Cited by 9
“Another very commonly used definition of trust, particularly in automation, is provided by [11].”
BackgroundChang, W.-C., Borowiak, A., & Hasanzadeh, S. (2024) · ASCE International Conference on Computing in Civil Engineering (i3CE) · doi:10.1061/9780784485224.099 · Cited by 9
Zhang, X., Sun, Y., Yan, C., & Mao, H. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2323276 · Cited by 8
“The original theory of trust in automation was proposed by Muir and subsequently validated through experimental studies (Muir, 1987; Muir, 1994; Muir & Moray, 1996).”
They Prefer Humans! Experimental Measurement of Student Trust in ChatGPT
Walker, F., Favetta, M., Hasker, L., & Walker, R. D. (2024) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3613905.3650955 · Cited by 11
“To account for the multitude of pairwise comparisons in our study (18) and to reduce the risk of Type I errors, we applied the Bon-ferroni correction method.”
BackgroundMethodThe Effects of In-vehicle Automation and Reliability on Driver Situation Awareness and Trust
Ma, R. (2005) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 9
Automation in Air Traffic Control: Trust, Teamwork, Resilience, Safety
Timotić, D., & Netjasov, F. (2022) · Transportation Research Procedia · doi:10.1016/j.trpro.2022.11.003 · Cited by 8
Technology Traps Who Is Responsible?
Crabb, P. B., & Stern, S. E. (2010) · International Journal of Technoethics · doi:10.4018/jte.2010040103 · Cited by 9
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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