Complacency and Automation Bias in the Use of Imperfect Automation
Abstract
OBJECTIVE: We examine the effects of two different kinds of decision-aiding automation errors on human-automation interaction (HAI), occurring at the first failure following repeated exposure to correctly functioning automation. The two errors are incorrect advice, triggering the automation bias, and missing advice, reflecting complacency. BACKGROUND: Contrasts between analogous automation errors in alerting systems, rather than decision aiding, have revealed that alerting false alarms are more problematic to HAI than alerting misses are. Prior research in decision aiding, although contrasting the two aiding errors (incorrect vs. missing), has confounded error expectancy. METHOD: Participants performed an environmental process control simulation with and without decision aiding. For those with the aid, automation dependence was created through several trials of perfect aiding performance, and an unexpected automation error was then imposed in which automation was either gone (one group) or wrong (a second group). A control group received no automation support. RESULTS: The correct aid supported faster and more accurate diagnosis and lower workload. The aid failure degraded all three variables, but "automation wrong" had a much greater effect on accuracy, reflecting the automation bias, than did "automation gone," reflecting the impact of complacency. Some complacency was manifested for automation gone, by a longer latency and more modest reduction in accuracy. CONCLUSIONS: Automation wrong, creating the automation bias, appears to be a more problematic form of automation error than automation gone, reflecting complacency. IMPLICATIONS: Decision-aiding automation should indicate its lower degree of confidence in uncertain environments to avoid the automation bias.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Automation bias is the tendency to over-rely on algorithmic output, leading clinicians to accept erroneous recommendations without adequate scrutiny, and this risk is amplified by automation bias.
“This risk is amplified by automation bias, the tendency to over-rely on algorithmic output, by leading clinicians to accept erroneous recommendations without adequate scrutiny.17-21”
From Automation Bias in Large Language Model Assisted Diagnostic Reasoning Among AI-Trained Physicians (2025) · cites this paper as [20]
Cites
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
(1988) · Advances in Psychology · doi:10.1016/s0166-4115(08)62386-9 · Cited by 15,003 · see citing works
Toward a Theory of Situation Awareness in Dynamic Systems
Endsley, M. R. (1995) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872095779049543 · Cited by 8,875 · see citing works
A model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · see citing works
Self-citationComplacency and Bias in Human Use of Automation: An Attentional Integration
Parasuraman, R., & Manzey, D. H. (2010) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720810376055 · Cited by 1,710 · cited 3× · see citing works
“These two problems have been integrated by Parasuraman and Manzey (2010) into a common attentionbased framework.”
BackgroundPerformance Consequences of Automation-Induced 'Complacency'
Parasuraman, R., Molloy, R., & Singh, I. L. (1993) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap0301_1 · Cited by 875 · see citing works
Parasuraman, R., Sheridan, T., & Wickens, C. (2008) · Journal of Cognitive Engineering and Decision Making · doi:10.1518/155534308x284417 · Cited by 729 · see citing works
Self-citationHuman Performance Consequences of Stages and Levels of Automation: An Integrated Meta-Analysis
Onnasch, L., Wickens, C. D., Li, H., & Manzey, D. (2014) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720813501549 · Cited by 524 · see citing works
Self-citationAutomation Bias: Decision Making and Performance in High-Tech Cockpits
Mosier, K. L., Skitka, L. J., Heers, S., & Burdick, M. (1998) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap0801_3 · Cited by 353 · see citing works
Dixon, S. R., & Wickens, C. (2006) · Hum. Factors · doi:10.1518/001872006778606822 · Cited by 329 · see citing works
Self-citationAccountability and automation bias
SKITKA, L. J., MOSIER, K., & BURDICK, M. D. (2000) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1999.0349 · Cited by 324 · see citing works
Monitoring an Automated System for a Single Failure: Vigilance and Task Complexity Effects
MOLLOY, R., & Parasuraman, R. (1996) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/001872089606380211 · Cited by 321 · see citing works
Effects of Adaptive Task Allocation on Monitoring of Automated Systems
Parasuraman, R., Mouloua, M., & Molloy, R. (1996) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872096778827279 · Cited by 285 · see citing works
Bahner, J. E., Hüper, A.-D., & Manzey, D. (2008) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2008.06.001 · Cited by 279 · see citing works
Manzey, D., Reichenbach, J., & Onnasch, L. (2012) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411433844 · Cited by 277 · see citing works
Automation failures on tasks easily performed by operators undermine trust in automated aids
Madhavan, P., Wiegmann, D. A., & Lacson, F. C. (2006) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872006777724408 · Cited by 268 · see citing works
On the Independence of Compliance and Reliance: Are Automation False Alarms Worse Than Misses?
Dixon, S. R., Wickens, C. D., & McCarley, J. S. (2007) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872007x215656 · Cited by 265 · see citing works
Self-citationEffects of Warning Validity and Proximity on Responses to Warnings
Meyer, J. (2001) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872001775870395 · Cited by 235 · see citing works
Conceptual Issues in the Study of Dynamic Hazard Warnings
Meyer, J. (2004) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.2.196.37335 · Cited by 216 · see citing works
Lees, M. N., & Lee, J. D. (2007) · Ergonomics · doi:10.1080/00140130701318749 · Cited by 193 · see citing works
Sorkin, R. D., Kantowitz, B. H., & Kantowitz, S. C. (1988) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/001872088803000406 · Cited by 187 · see citing works
Yeh, M., Merlo, J. L., Wickens, C. D., & Brandenburg, D. L. (2003) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.45.3.390.27249 · Cited by 118 · see citing works
Self-citationNew Alternative Methods of Analyzing Human Behavior in Cued Target Acquisition
Maltz, M., & Shinar, D. (2003) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.45.2.281.27239 · Cited by 82 · see citing works
Identifying Black Swans in NextGen: Predicting Human Performance in Off-Nominal Conditions
Wickens, C. D., Hooey, B. L., Gore, B. F., Sebok, A. L., & Koenicke, C. S. (2009) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720809349709 · Cited by 75 · see citing works
Self-citationSupporting Attention Allocation in Multitask Environments
Wiczorek, R., & Manzey, D. (2014) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720814528534 · Cited by 68 · see citing works
Judgment and Decision Making by Individuals and Teams: Issues, Models, and Applications
Mosier, K. L., & Fischer, U. M. (2010) · Reviews of Human Factors and Ergonomics · doi:10.1518/155723410x12849346788822 · Cited by 67 · see citing works
Trust, Reliance, and Compliance
Meyer, J., & Lee, J. D. (2013) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199757183.013.0007 · Cited by 42 · see citing works
Clegg, B. A., Vieane, A. Z., Wickens, C. D., Gutzwiller, R. S., & Sebok, A. L. (2014) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931214581178 · Cited by 7 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Metrics for explainable AI: challenges and prospects
Hoffman, R. R., Mueller, S. T., Klein, G., & Litman, J. (2018) · arXiv · doi:10.48550/arxiv.1812.04608 · Cited by 518 · see citing works
The shaky foundations of large language models and foundation models for electronic health records
Wornow, M., Xu, Y., Thapa, R., Patel, B., Steinberg, E., Fleming, S., Pfeffer, M. A., Fries, J., & Shah, N. H. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00879-8 · Cited by 324 · see citing works
Hoffman, R. R., Mueller, S. T., Klein, G., & Litman, J. (2023) · Frontiers in Computer Science · doi:10.3389/fcomp.2023.1096257 · Cited by 272 · see citing works
Co-Writing with Opinionated Language Models Affects Users’ Views
Jakesch, M., Bhat, A., Buschek, D., Zalmanson, L., & Naaman, M. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581196 · Cited by 265 · see citing works
Experimental evidence of effective human–AI collaboration in medical decision-making
Reverberi, C., Rigon, T., Solari, A., Hassan, C., Cherubini, P., GI Genius CADx Study Group, Antonelli, G., Awadie, H., Bernhofer, S., Carballal, S., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-18751-2 · Cited by 235 · see citing works
Ellahham, S., Ellahham, N., & Simsekler, M. C. E. (2020) · American Journal of Medical Quality · doi:10.1177/1062860619878515 · Cited by 177 · see citing works
Exploring automation bias in human–AI collaboration: a review and implications for explainable AI
Romeo, G., & Conti, D. (2026) · AI & SOCIETY · doi:10.1007/s00146-025-02422-7 · Cited by 209 · see citing works
“Some researchers emphasize differences in their cognitive and situational antecedents (Wickens et al. 2015), while others highlight substantial overlap, viewing both as manifestations of shared underlying attentional and decision-making mechanisms (Parasuraman and Manzey 2010).”
International migration management in the age of artificial intelligence
Beduschi, A. (2021) · Migration Studies · doi:10.1093/migration/mnaa003 · Cited by 141 · see citing works
Chugunova, M., & Sele, D. (2022) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2022.101897 · Cited by 118 · see citing works
AI in the hands of imperfect users
Kostick, K. M., & Gerke, S. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00737-z · Cited by 109 · see citing works
Explanations and trust: What happens to trust when a robot partner does something unexpected?
Lyons, J. B., Hamdan, I. A., & Vo, T. Q. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107473 · Cited by 97 · see citing works
Ethics in human–AI teaming: principles and perspectives
Pflanzer, M., Traylor, Z., Lyons, J. B., Dubljević, V., & Nam, C. S. (2022) · AI and Ethics · doi:10.1007/s43681-022-00214-z · Cited by 106 · see citing works
The effects of explanations on automation bias
Vered, M., Livni, T., Howe, P. D. L., Miller, T., & Sonenberg, L. (2023) · Artificial Intelligence · doi:10.1016/j.artint.2023.103952 · Cited by 71 · see citing works
Mirror, Mirror on the Wall: Algorithmic Assessments, Transparency, and Self-Fulfilling Prophecies
Bauer, K., & Gill, A. (2023) · Information Systems Research · doi:10.1287/isre.2023.1217 · Cited by 66 · see citing works
Time Sharing Between Robotics and Process Control
Wickens, C. D., Gutzwiller, R. S., Vieane, A. Z., Clegg, B. A., Sebok, A. L., & Janes, J. (2016) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815622761 · Cited by 61 · see citing works
Self-citationExploring the differential effects of trust violations in human-human and human-robot interactions
Alarcon, G. M., Gibson, A. M., Jessup, S. A., & Capiola, A. (2021) · Applied Ergonomics · doi:10.1016/j.apergo.2020.103350 · Cited by 60 · see citing works
Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles
(2020) · CRC Press eBooks · doi:10.1201/b21974 · Cited by 60 · see citing works
Check the box! How to deal with automation bias in AI-based personnel selection
Kupfer, C., Prassl, R., Fleiß, J., Malin, C., Thalmann, S., & Kubicek, B. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1118723 · Cited by 59 · see citing works
“More information about the AI-based system’s capacities, including its reliability, might stimulate a more critical investigation of the system’s recommendations, which positively influences decision quality (Bahner et al., 2008; Wickens et al., 2015; Sauer et al., 2016).”
BackgroundThe effect of cognitive load and task complexity on automation bias in electronic prescribing
Lyell, D., Magrabi, F., & Coiera, E. (2018) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720818781224 · Cited by 67 · see citing works
Kinney, M. N., Anastasiadou, M., Naranjo-Zolotov, M., & Santos, V. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e28562 · Cited by 68 · see citing works
Deb, S., Carruth, D. W., & Hudson, C. R. (2020) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2019.2960517 · Cited by 58 · see citing works
Azevedo-Sa, H., Zhao, H., Esterwood, C. T., Yang, X. J., Tilbury, D. M., & Robert, L. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.102973 · Cited by 56 · see citing works
Gutzwiller, R. S., Chiou, E. K., Craig, S. D., Lewis, C. M., Lematta, G. J., & Hsiung, C.-P. (2019) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181319631201 · Cited by 54 · see citing works
Social impacts of algorithmic decision-making: A research agenda for the social sciences
Gerdon, F., Bach, R. L., Kern, C. A., & Kreuter, F. (2022) · Big Data & Society · doi:10.1177/20539517221089305 · Cited by 61 · see citing works
Egbert, S., & Leese, M. (2020) · Routledge eBooks · doi:10.4324/9780429328732 · Cited by 124 · see citing works
The Automation-by-Expertise-by-Training Interaction
Strauch, B. (2016) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816665459 · Cited by 52 · see citing works
Trusting Autonomous Security Robots: The Role of Reliability and Stated Social Intent
Lyons, J. B., Vo, T. Q., Wynne, K. T., Mahoney, S., Nam, C. S., & Gallimore, D. M. (2020) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820901629 · Cited by 49 · see citing works
Adaptive Cognitive Mechanisms to Maintain Calibrated Trust and Reliance in Automation
Lebiere, C. J., Blaha, L. M., Fallon, C. K., & Jefferson, B. A. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.652776 · Cited by 45 · see citing works
Design Guidelines for Reliability Communication in Autonomous Vehicles
Faltaous, S., Baumann, M. R. K., Schneegaß, S., & Chuang, L. L. (2018) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3239060.3239072 · Cited by 39 · see citing works
How Do Analysts Understand and Verify AI-Assisted Data Analyses?
Gu, K., Shang, R., Althoff, T., Wang, C., & Drucker, S. M. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642497 · Cited by 45 · see citing works
Autopilots in the Operating Room: Safe Use of Automated Medical Technology
Ruskin, K. J., Corvin, C., Rice, S. C., & Winter, S. R. (2020) · Anesthesiology · doi:10.1097/aln.0000000000003385 · Cited by 38 · see citing works
Theory-based Models of Attention in Visual Workspaces
Steelman, K. S., McCarley, J. S., & Wickens, C. D. (2016) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2016.1232228 · Cited by 35 · see citing works
Self-citationNever tell me the odds: Investigating pro-hoc explanations in medical decision making
Cabitza, F., Natali, C., Famiglini, L., Campagner, A., Caccavella, V. M., & Gallazzi, E. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102819 · Cited by 39 · see citing works
How users adjust trust in automation
Yang, X. J., Wickens, C. D., & Hölttä-Otto, K. (2016) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601044 · Cited by 37 · see citing works
Self-citationvan der Kleij, R., Hueting, T. F., & Schraagen, J. M. (2018) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2018.02.010 · Cited by 31 · see citing works
Causse, M., Mercier, M., Lefrançois, O., & Matton, N. (2025) · Applied Ergonomics · doi:10.1016/j.apergo.2024.104456 · Cited by 30 · see citing works
Qazi, I. A., Ali, A., Khawaja, A. U., Akhtar, M. J., Sheikh, A. Z., & Alizai, M. H. (2026) · NEJM AI · doi:10.1056/aioa2501001 · Cited by 37 · see citing works
We and It: An Interdisciplinary Review of the Experimental Evidence on Human-Machine InteractionPreprint
Chugunova, M., & Sele, D. (2020) · SSRN Electronic Journal · doi:10.3929/ethz-b-000442053 · Cited by 30 · see citing works
Supporting human supervision in autonomous collision avoidance through agent transparency
van de Merwe, K., Mallam, S., Nazir, S., & Engelhardtsen, Ø. (2023) · Safety Science · doi:10.1016/j.ssci.2023.106329 · Cited by 28 · see citing works
Human-artificial intelligence interaction in gastrointestinal endoscopy
Campion, J. R., O’Connor, D. B., & Lahiff, C. J. (2024) · World Journal of Gastrointestinal Endoscopy · doi:10.4253/wjge.v16.i3.126 · Cited by 27 · see citing works
Benefits of Imperfect Conflict Resolution Advisory Aids for Future Air Traffic Control
Trapsilawati, F., Wickens, C. D., Qu, X., & Chen, C. (2016) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816655941 · Cited by 27 · see citing works
Self-citation“Computer says no”: Algorithmic decision support and organisational responsibility
Adensamer, A., Gsenger, R., & Klausner, L. D. (2021) · Journal of Responsible Technology · doi:10.1016/j.jrt.2021.100014 · Cited by 28 · see citing works
Day, T. G., Matthew, J., Budd, S., Venturini, L., Wright, R., Farruggia, A., Vigneswaran, T. V., Zidere, V., Hajnal, J. V., Razavi, R., et al. (2024) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.27577 · Cited by 27 · see citing works
Sargent, R., Walters, B. A., & Wickens, C. D. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35596-7_16 · Cited by 25 · see citing works
Self-citationEvaluating the Impact of Uncertainty Visualization on Model Reliance
Zhao, J. L., Wang, Y., Mancenido, M. V., Chiou, E. K., & Maciejewski, R. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3251950 · Cited by 26 · see citing works
Reflections on Automation Complacency
Liu, P. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2265240 · Cited by 23 · see citing works
The Effect of Agent Reasoning Transparency on Automation Bias: An Analysis of Response Performance
Wright, J. L., Chen, J. Y. C., Barnes, M. J., & Hancock, P. A. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-39907-2_45 · Cited by 23 · see citing works
Coyne, R., Hanlon, M. L. D., Smeaton, A. F., Corcoran, P., & Walsh, J. C. (2024) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.07.015 · Cited by 22 · see citing works
Automation complacency on the road
Chu, Y., & Liu, P. (2023) · Ergonomics · doi:10.1080/00140139.2023.2210793 · Cited by 22 · see citing works
The Benefits and Costs of Low and High Degree of Automation
Tatasciore, M., Bowden, V. K., Visser, T. A. W., Michailovs, S., & Loft, S. D. (2019) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720819867181 · Cited by 21 · see citing works
Applying the swift trust model to human-robot teaming
Haring, K. S., Phillips, E., Lazzara, E., Ullman, D., Baker, A. L., & Keebler, J. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-819472-0.00017-4 · Cited by 16 · see citing works
Online Multimodal Inference of Mental Workload for Cognitive Human Machine Systems
Planke, L. J., Gardi, A., Sabatini, R., Kistan, T., & Ezer, N. (2021) · Computers · doi:10.3390/computers10060081 · Cited by 20 · see citing works
Human preferences toward algorithmic advice in a word association task
Bogert, E., Lauharatanahirun, N., & Schecter, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-18638-2 · Cited by 23 · see citing works
Lancaster, C., Schulenberg, K., Flathmann, C., McNeese, N. J., & Freeman, G. (2023) · ACM Journal on Responsible Computing · doi:10.1145/3632121 · Cited by 21 · see citing works
Flight Eye Tracking Assistant (FETA): Proof of Concept
Lounis, C., Peysakhovich, V., & Causse, M. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-20503-4_66 · Cited by 20 · see citing works
Avril, E. (2022) · Ergonomics · doi:10.1080/00140139.2022.2069870 · Cited by 17 · see citing works
Rosbach, E., Ammeling, J., Krügel, S., Kießig, A., Fritz, A., Ganz, J., Puget, C., Donovan, T., Klang, A., Köller, M. C., et al. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713319 · Cited by 18 · see citing works
Mori, Y., Kopylov, U., Sinonquel, P., Ebigbo, A., Dekker, E., de Groof, A. J., Ahmad, O. F., Kader, R., Săftoiu, A., Schoon, E. J., et al. (2025) · Endoscopy · doi:10.1055/a-2742-4342 · Cited by 19 · see citing works
A network analysis of decision strategies of human experts in steel manufacturing
Merten, D. C., Hütt, M. ‐., & Uygun, Y. (2022) · Computers & Industrial Engineering · doi:10.1016/j.cie.2022.108120 · Cited by 18 · see citing works
Carragher, D. J., Sturman, D., & Hancock, P. (2024) · Cognitive Research Principles and Implications · doi:10.1186/s41235-024-00564-8 · Cited by 21 · see citing works
Measuring Trust in the XAI ContextPreprint
Hoffman, R. R., Mueller, S. T., Klein, G., & Litman, J. A. (2021) · doi:10.31234/osf.io/e3kv9 · Cited by 26 · see citing works
Wickens, C. D., Onnasch, L., Sebok, A., & Manzey, D. (2020) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820901957 · Cited by 17 · see citing works
Self-citationThe effect of two-stage warning system on human performance along with different takeover strategies
Wang, S., Liu, Y., Li, S., Liu, Z., You, X., & Li, Y. (2023) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2023.103492 · Cited by 16 · see citing works
Bielić, T., Čulin, J., Poljak, I., & Orović, J. (2020) · Journal of Marine Science and Engineering · doi:10.3390/jmse8070517 · Cited by 16 · see citing works
Effect of Imperfect Information and Action Automation on Attentional Allocation
Avril, E., Valéry, B., Navarro, J., Wioland, L., & Cegarra, J. (2021) · International journal of human computer interactions · doi:10.1080/10447318.2020.1870817 · Cited by 16 · see citing works
Tatasciore, M., Bowden, V. K., Visser, T. A. W., & Loft, S. D. (2021) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720821989148 · Cited by 15 · see citing works
Beyond Visual Analytics: Human-Machine Teaming for AI-Driven Data Sensemaking
Wenskovitch, J. E., Fallon, C. K., Miller, K. H., & Dasgupta, A. (2021) · IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX) · doi:10.1109/trex53765.2021.00012 · Cited by 15 · see citing works
11 Artificial Intelligence, Migration and Mobility: Implications for Policy and Practice
Beduschi, A., & McAuliffe, M. (2022) · World Migration Report · doi:10.1002/wom3.32 · Cited by 15 · see citing works
Influence of automation level of human-machine system on operators’ mental load
Huang, Q., Guo, M., Wei, Y., Zhang, J., Xie, F., & Jin, X. (2023) · Journal of Safety and Sustainability · doi:10.1016/j.jsasus.2023.12.001 · Cited by 15 · see citing works
Unreliable Pedestrian Detection and Driver Alerting in Intelligent Vehicles
Cummings, M. L., & Bauchwitz, B. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2024.3354043 · Cited by 15 · see citing works
Valdez, A. S. C., Heine, M., Franke, T., Jochems, N., Jetter, H.-C., & Schrills, T. (2024) · i-com · doi:10.1515/icom-2024-0014 · Cited by 18 · see citing works
Liel, Y., & Zalmanson, L. (2025) · Journal of Management Information Systems · doi:10.1080/07421222.2025.2561390 · Cited by 14 · see citing works
Automation Bias in Large Language Model Assisted Diagnostic Reasoning Among AI-Trained Physicians
Qazi, I. A., Ali, A., Khawaja, A. U., Akhtar, M. J., Sheikh, A. Z., & Alizai, M. H. (2025) · medRxiv · doi:10.1101/2025.08.23.25334280 · Cited by 16 · see citing works
Okine, E. A., Zarei, E., Roggow, B. J., & Dehghan, N. (2025) · Journal of Safety Science and Resilience · doi:10.1016/j.jnlssr.2025.100249 · Cited by 20 · see citing works
Mitcheltree, C. M. (2023) · Journal of Innovation and Entrepreneurship · doi:10.1186/s13731-023-00267-2 · Cited by 13 · see citing works
Wienrich, C., Carolus, A., Roth-Isigkeit, D., & Andreas Hotho, A. (2022) · Multimodal Technologies and Interaction · doi:10.3390/mti6120106 · Cited by 12 · see citing works
Kobayashi, L., Gosbee, J. W., & Merck, D. L. (2016) · HERD Health Environments Research & Design Journal · doi:10.1177/1937586716673829 · Cited by 12 · see citing works
Bridging the civilian-military divide in responsible AI principles and practices
Azafrani, R., & Gupta, A. (2023) · Ethics and Information Technology · doi:10.1007/s10676-023-09693-y · Cited by 11 · see citing works
Predictive Policing in 2025: A Scenario
Macnish, K., Wright, D., & Jiya, T. (2020) · Advanced sciences and technologies for security applications · doi:10.1007/978-3-030-50613-1_9 · Cited by 11 · see citing works
Automated Vehicle Failure: The First Pedestrian Fatality and Public Perception
Tapiro, H., Wyman, A., Borowsky, A., Petzoldt, T., Wang, X., & Hurwitz, D. (2022) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981221083297 · Cited by 11 · see citing works
Sauer, J., & Chavaillaz, A. (2017) · Applied Ergonomics · doi:10.1016/j.apergo.2016.08.007 · Cited by 12 · see citing works
Trust, Automation Bias and Aversion: Algorithmic Decision-Making in the Context of Credit Scoring
Gsenger, R., & Strle, T. (2021) · Interdisciplinary Description of Complex Systems · doi:10.7906/indecs.19.4.7 · Cited by 12 · see citing works
Hanham, J., & Leppink, J. (2018) · Springer eBooks · doi:10.1007/978-981-13-2808-4_6 · Cited by 9 · see citing works
Morey, D. A., Marquisee, J. M., Gifford, R. C., Fitzgerald, M. C., & Rayo, M. F. (2020) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181320641072 · Cited by 9 · see citing works
Is my User Impaired? Designing Adaptive Automation that Monitors the User’s State
Cotter, J. E., Atchley, A., Banz, B., & Tenhundfeld, N. (2021) · Systems and Information Engineering Design Symposium · doi:10.1109/sieds52267.2021.9483731 · Cited by 8 · see citing works
Sonographer interaction with artificial intelligence: collaboration or conflict?
Day, T. G., Matthew, J., Budd, S., Hajnal, J. V., Simpson, J. M., Razavi, R., & Kainz, B. (2023) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.26238 · Cited by 10 · see citing works
Tenhundfeld, N. L., Forsyth, J. B., Sprague, N. R., El-Tawab, S., Cotter, J. E., & Vangsness, L. (2023) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/15553434231206422 · Cited by 8 · see citing works
Enabling Civil Single-Pilot Operations: A State-of-the-Art Review
Puca, N., & Guglieri, G. (2024) · Aerotecnica Missili & Spazio · doi:10.1007/s42496-024-00223-7 · Cited by 7 · see citing works
SE Perspective on LLMs: Biases in Code Generation, Code Interpretability, and Code Security Risks
Krasniqi, R., Xu, D., & Vieira, M. P. A. (2025) · ACM Computing Surveys · doi:10.1145/3774324 · Cited by 7 · see citing works
Casado–Mansilla, D., Garaizar, P., & López–de–Ipiña, D. (2019) · International Conference on the Internet of Things (IoT) · doi:10.1145/3365871.3365894 · Cited by 7 · see citing works
Approaches for loss of vigilance in vehicle automation: a meta-analytical study
Gonçalves, R. C., Quaresma, M., & Rodrigues, C. M. (2017) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601948 · Cited by 7 · see citing works
Automation function and malfunction: effects on human performance in accident handling tasks
Dong, X., & Li, Z. (2024) · Ergonomics · doi:10.1080/00140139.2024.2307964 · Cited by 5 · see citing works
GDPR Impacts and Opportunities for Computer-Aided Diagnosis Guidelines and Legal Perspectives
Pedrosa, M., Costa, C. M. A., & Dorado, J. (2019) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2019.00128 · Cited by 6 · see citing works
Cooman, J. D. (2023) · Journal of European Competition Law & Practice · doi:10.1093/jeclap/lpad017 · Cited by 6 · see citing works
Wang, S., Liu, Y., Wang, X., Liu, Z., You, X., & Li, Y. (2024) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208241311808 · Cited by 6 · see citing works
Huegli, D., Chavaillaz, A., Sauer, J., & Schwaninger, A. (2025) · Ergonomics · doi:10.1080/00140139.2025.2453546 · Cited by 5 · see citing works
Patton, C. E., Wickens, C. D., Smith, C. A. P., Noble, K. M., & Clegg, B. A. (2023) · Cognitive Research Principles and Implications · doi:10.1186/s41235-023-00519-5 · Cited by 5 · see citing works
Self-citationNæsborg-Andersen, A., Hammerslev, O., & Ullits, J. (2023) · Politica · doi:10.7146/politica.v55i3.140267 · Cited by 5 · see citing works
Scalable Interactive Machine Learning for Future Command and Control
Madison, A., Novoseller, E., Goecks, V. G., Files, B. T., Waytowich, N. R., Yu, A., Lawhern, V. J., Thurman, S. M., Kelshaw, C., & McDowell, K. (2024) · International Conference on Military Communications and Information Systems (ICMCIS) · doi:10.1109/icmcis61231.2024.10540933 · Cited by 7 · see citing works
Human Performance in Automated and Autonomous Systems
(2019) · CRC Press eBooks · doi:10.1201/9780429458330 · Cited by 5 · see citing works
- Authors
- Wickens, C. D., Clegg, B. A., Vieane, A. Z., & Sebok, A. L.
- Affiliations
- Alion Science and Technology (United States) (US)
- Colorado State University (US)
- Venue
- Human Factors: The Journal of the Human Factors and Ergonomics Society
- Publisher
- SAGE Publications
- Published
- 2015-04-17
- Volume
- 57
- Issue
- 5
- Pages
- 728-739
- ISSN
- 0018-7208 (ISSN-L)
- 1547-8181
- OpenAlex
- W2010273961
- Cited by
- 176
- References
- 27
- Citations by year
- 2026: 23 · 2025: 17 · 2024: 29 · 2023: 30 · 2022: 17 · 2021: 11 · 2020: 16 · 2019: 9 · 2018: 7 · 2017: 2 · 2016: 11 · 2015: 4
- FWCI
- 13.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Factors The Journal of the Human Factors and Ergonomics Society (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Aeronautics and Space Administration
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Risk and Safety Analysis
- Keywords
- automation bias, complacency, human-automation interaction, diagnostic accuracy, workload, alert system, false alarms
- MeSH terms
- Automation, Decision Making, Decision Support Techniques, Humans, Man-Machine Systems, Mental Processes, Workload
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
