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The benefits of imperfect diagnostic automation: a synthesis of the literature
Abstract
This review of the literature examines, in a quantitative fashion, how the level of imperfection or unreliability of diagnostic automation affects the performance of the human operator who is jointly consulting that automation and the raw data itself. The data from 20 different studies were used to generate 35 different data points that compared performance with varying levels of unreliability, with that of a non-automated baseline condition. A regression analysis of benefits/costs relative to baseline was carried out, and revealed a strong linear function of benefits with reliability. The analysis revealed that a reliability of 0.70 was the ‘crossover point’ below which unreliable automation was worse than no automation at all. The analysis also revealed that performance was more strongly affected by reliability in high workload conditions, implicating the role of workload-imposed automation dependence in producing this relationship, and suggesting that humans tend to protect performance of concurrent tasks from imperfection of diagnostic automation.
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“This observation supports prior research suggesting that both over-reliance and under-reliance are closely linked to perceived AI competence and actual system performance (Lee & See, 2004;Wickens & Dixon, 2007).”
From Investigating appropriate reliance on AI-Based decision support systems: the role of expertise, trust, and self-confidence (2025) · cites this paper as Wickens & Dixon, 2007
In the citing paper
“Previous research has revealed consistently a positive relationship between automation reliability and the (snapshot) trust in automation measured at the end of an experiment”
From Toward Quantifying Trust Dynamics: How People Adjust Their Trust After Moment-to-Moment Interaction With Automation (2023) · cites this paper as Wickens & Dixon, 2007
In the citing paper
“70% is the threshold above which using automation improves task performance and below which such use may harm performance”
From Toward Quantifying Trust Dynamics: How People Adjust Their Trust After Moment-to-Moment Interaction With Automation (2023) · cites this paper as Wickens & Dixon, 2007
In the citing paper
“On the contrary, we find that automation reliability significantly predicts the (snapshot) trust in automation measured at the end of an experiment, which is in line with previous research (de Visser & Parasuraman, 2011; Du et al., 2020; Wickens & Dixon, 2007).”
From Toward Quantifying Trust Dynamics: How People Adjust Their Trust After Moment-to-Moment Interaction With Automation (2023) · cites this paper as Wickens & Dixon, 2007
Citations
Cites
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1956) · Psychological Review · doi:10.1037/h0043158 · Cited by 17,812
Trust in Automation: Designing for Appropriate Reliance
Lee, J. D., & See, K. A. (2004) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.1.50_30392 · Cited by 6,605 · cited 3×
“Numerous contextual factors such as human operator knowledge and payoffs may well moderate this value considerably (Lee and See 2004).”
BackgroundResultInfluentialA 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 · cited 2×
“( 2000 ), diagnostic aiding refers both to stage 1 automation (e.”
BackgroundSelf-citationPerformance 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 · cited 2×
“In both of these cases, the automation benefits are likely to increase, to the extent that the single task to be automated is more difficult (Maltz and Shinar 2003, Dixon and Wickens 2006), and/or that concurrent task load is imposed (Parasuraman et al. 1993).”
BackgroundDoes automation bias decision-making?
SKITKA, L. J., MOSIER, K. L., & BURDICK, M. (1999) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1999.0252 · Cited by 694
Yeh, M., & Wickens, C. D. (2001) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872001775898269 · Cited by 175
Self-citation
Research works printed but not linked: 29
- 10.1016/j.apergo.2003.07.003 · DOI
- Davison HJ, 2001, Proceedings of the 11th International Symposium on Aviation Psychology
- 10.1518/001872097778543930 · DOI
- 10.1518/001872005774860005 · DOI
- 10.1518/001872006778606822 · DOI
- Dzindolet MT, 2001, Proceedings of the 45th Annual Meeting of the Human Factors and Ergonomics Society, 532
- Galster SM, 2001, Proceedings of the 45th Annual Meeting of the Human Factor Society, 321
- 10.1037/1076-898X.1.1.19 · DOI
- Lee JD, 2004, Human Factors, 46, 50, 10.1518/hfes.46.1.50.30392 · DOI · Paper page
- 10.1016/S0925-7535(00)00043-6 · DOI
- 10.1518/001872006777724408 · DOI · Paper page
- 10.1518/001872001775900931 · DOI
- 10.1518/hfes.45.2.281.27239 · DOI
- 10.1518/hfes.46.2.357.37348 · DOI
- 10.1518/0018720053653802 · DOI
- 10.1518/001872001775870395 · DOI
- 10.1518/001872096779048093 · DOI
- Sheridan T, 2002, Humans and Automation: System Design and Research Issues
- Sheridan, T and Parasurman, R. 2006. Human automation interaction. Proceedings of the Human Factors and Ergonomics Society 46th Annual Meeting. 2006. Edited by: Nickerson, R. Santa Monica, CA: Human Factors and Ergonomics Society.
- 10.1207/s15327051hci0101_2 · DOI
- John M, 2002, Proceedings of the Human Factors and Ergonomics Society 46th Annual Meeting
- Swets JA, 1982, The Evaluation of Diagnostic Systems
- Thomas LC, 2003, Proceedings of the 47th Annual Human Factors Ergonomics Society Conference
- Wickens CD, 2006, Human Factors of Remotely Operated Vehicles
- 10.1207/STHF0202_01 · DOI
- Wiegmann DA, 2003, Human Factors
- Xu X, Ergonomics
- 10.1518/0018720024497925 · DOI
- 10.1518/hfes.45.3.390.27249 · DOI
Cited by
Sorted by citations
Complacency 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
“Wickens and Dixon (2007) proposed that this cutoff value is approximately 70% (with a standard error of ± 14%), on the basis of studies examining the beneficial effects of automation support.”
BackgroundFrom Here to Autonomy: Lessons Learned From Human–Automation Research
Endsley, M. R. (2017) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816681350 · Cited by 898
“The presence of competing tasks has also been found to increase trust in automation in a metaanalysis of studies (Wickens & Dixon, 2007), thus shifting operator attention away from the automation and decreasing SA of the functions being automated (Carsten, Lai, Barnard, Jamson, & Merat, 2012; Kaber…”
BackgroundParasuraman, R., Sheridan, T., & Wickens, C. (2008) · Journal of Cognitive Engineering and Decision Making · doi:10.1518/155534308x284417 · Cited by 729
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
“It is also in line with other authors who also departed from the classic approach for similar reasons (e.g., Hutchins, Wickens, Carolan, & Cumming, 2013; Wickens & Dixon, 2007; Wickens et al., 2013; Wickens, Hooey, Gore, Sebok, & Koe-nicke, 2009).”
ResultSelf-citationAutomation bias and verification complexity: a systematic review
Lyell, D., & Coiera, E. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw105 · Cited by 451
Intelligent agent transparency in human–agent teaming for multi-UxV management
Mercado, J. E., Rupp, M. A., Chen, J. Y. C., Barnes, M. J., Barber, D., & Procci, K. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815621206 · Cited by 403
Humans: Still Vital After All These Years of Automation
Parasuraman, R., & Wickens, C. D. (2008) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872008x312198 · Cited by 401
“These findings have been replicated ( Scerbo, 2007) and modeled computationally (Farrell & Lewandowsky, 2000; Wickens & Dixon, 2007).”
Self-citationDixon, S. R., & Wickens, C. (2006) · Hum. Factors · doi:10.1518/001872006778606822 · Cited by 329
“Such resource scarcity may result either when the task itself is difficult (Maltz & Shinar, 2003) or when the automated task is carried out in a multitask context (C. D. Wickens & Dixon, 2005).”
BackgroundResultSelf-citationVagia, M., Transeth, A. A., & Fjerdingen, S. A. (2016) · Applied Ergonomics · doi:10.1016/j.apergo.2015.09.013 · Cited by 299
Effects of Imperfect Automation on Decision Making in a Simulated Command and Control Task
Rovira, E. M., McGarry, K. A., & Parasuraman, R. (2007) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872007779598082 · Cited by 289
“In a recent review, Wickens and Dixon (2005) suggested that human performance is sensitive to the level of automation imperfection.”
BackgroundOn 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
“This is particularly true of diagnostic automation, which must make diagnoses and long-range predictions in a world of imperfect probabilistic information (Wickens & Dixon, 2007).”
BackgroundSelf-citationStages and Levels of Automation: An Integrated Meta-analysis
Wickens, C., Li, H., Santamaria, A., Sebok, A., & Sarter, N. (2010) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193121005400425 · Cited by 260
“A similar approach was applied earlier by Wickens and Dixon (2007) who examined stage 2 automation reliability.”
MethodSelf-citationSupervisory Control of Multiple Robots: Human-Performance Issues and User-Interface Design
Chen, J. Y. C., Barnes, M., & Harper-Sciarini, M. (2011) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2010.2056682 · Cited by 246
“target cueing is ineffective below a certain level of reliability (approximately 60%–70%) [32], [33].”
Backgroundde Visser, E., & Parasuraman, R. (2011) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411410160 · Cited by 207
“Despite the costs of automation unreliability, studies have also shown that imperfect automation can still yield system performance benefits above baseline performance (Wickens & Dixon, 2005).”
BackgroundIndividual differences in response to automation: The five factor model of personality.
Szalma, J. L., & Taylor, G. S. (2011) · Journal of Experimental Psychology Applied · doi:10.1037/a0024170 · Cited by 188
“Note that 75% reliability is within the confidence interval of the automation effectiveness threshold identified by Wickens and Dixon (2007). They also reported that dependence on automation is stronger at higher levels of task demand, even in situations in which the “raw data” are available to the operator.”
BackgroundTrust and Reliance on an Automated Combat Identification System
Wang, L., Jamieson, G. A., & Hollands, J. G. (2009) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720809338842 · Cited by 157
“Our results seem to align well with the results of Wickens and Dixon (2007) and suggest that CID performance is indeed similar to the results typically obtained in other automation domains.”
BackgroundResultInfluentialKunze, A., Summerskill, S. J., Marshall, R., & Filtness, A. J. (2019) · Ergonomics · doi:10.1080/00140139.2018.1547842 · Cited by 165
“An additional challenge relevant to automated driving is the presence of concurrent tasks, which further promote the attention allocation away from the automated task (Wickens and Dixon 2007).”
BackgroundAttention: Theory, Principles, Models and Applications
Wickens, C. D. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1874741 · Cited by 222
“Using a relatively simple regression model, with weights based on a meta-analysis, Wickens and Dixon (2007) found that such calibration was reasonably good, so long as automation reliability remained above about 80%; but was found wanting when automation erred more frequently.”
MethodSelf-citationExamining Single- and Multiple-Process Theories of Trust in Automation
Rice, S. C. (2009) · The Journal of general psychology · doi:10.3200/genp.136.3.303-322 · Cited by 139
“Thus, system designers should use highly reliable automation when possible because less reliable automation tends to harm human–automation performance to such a degree that one might argue that no automation at all is more beneficial than unreliable automation (Wickens & Dixon, 2007).”
BackgroundDirecting driver attention with augmented reality cues
Rusch, M. L., Schall, M., Gavin, P., Lee, J. D., Dawson, J., Vecera, S. P., & Rizzo, M. (2013) · Transportation Research Part F: Traffic Psychology and Behaviour · doi:10.1016/j.trf.2012.08.007 · Cited by 130
Situation Awareness in Future Autonomous Vehicles: Beware of the Unexpected
Endsley, M. (2018) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-319-96071-5_32 · Cited by 121
Rayo, M. F., & Moffatt-Bruce, S. D. (2015) · BMJ Quality & Safety · doi:10.1136/bmjqs-2014-003373 · Cited by 115
False Alerts in Air Traffic Control Conflict Alerting System: Is There a “Cry Wolf” Effect?
Wickens, C., Rice, S. C., Keller, D., Hutchins, S., Hughes, J. S., & Clayton, K. (2009) · Hum. Factors · doi:10.1177/0018720809344720 · Cited by 114
“The approach based on d′ asks how low the reliability of an alerting or diagnostic system can get while preserving performance that is superior to that of the unaided human (Wickens & Dixon, 2007; Xu Rantanen & Wickens, 2007).”
BackgroundMethodSelf-citationIncreasing anthropomorphism and trust in automated driving functions by adding speech output
Forster, Y., Naujoks, F., & Neukum, A. (2017) · 2017 IEEE Intelligent Vehicles Symposium (IV) · doi:10.1109/ivs.2017.7995746 · Cited by 114
“The 3:1 (system maneuver : take-over) ratio was chosen in order to get 75% system reliability for interaction scenarios as proposed by [21].”
MethodIndividual Differences in the Calibration of Trust in Automation
Pop, V. L., Shrewsbury, A., & Durso, F. T. (2015) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720814564422 · Cited by 109
“For example, Wickens and Dixon (2007) found that in some cases operators relied on automated aids even when it resulted in worse diagnostic monitoring than when the operator had not used automation at all.”
BackgroundYang, X. J., Schemanske, C., & Searle, C. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211034716 · Cited by 132
“In their study of sequential effects on 8 perceptions of job candidates, Wexley et al. (1972) found that up to 12% of variance in ratings of candidates could be attributed to a contrast effect from the two candidates preceding the target candidate.”
BackgroundSupervisory Control of Multiple Robots
Chen, J. Y. C., & Barnes, M. (2012) · Hum. Factors · doi:10.1177/0018720811435843 · Cited by 105
“Finally, Wickens and Dixon (2007) demonstrated that when the reliability level is below approximately 70%, operators will often ignore the alerts.”
A Little Anthropomorphism Goes a Long Way
de Visser, E. J., Monfort, S. S., Goodyear, K., Lu, L., O’Hara, M., Lee, M. R., Parasuraman, R., & Krüeger, F. (2017) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816687205 · Cited by 118
“We chose 50% reliability as a control condition to match the lottery condition typically used in oxytocin research with economic games and because automation below 70% reliability is generally considered unreliable (Wickens & Dixon, 2007).”
MethodWright, J. L., Chen, J. Y. C., & Lakhmani, S. G. (2019) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2019.2925717 · Cited by 137
Coleman, J. J., van der Sijs, H., Haefeli, W. E., Slight, S. P., McDowell, S. E., Seidling, H. M., Eiermann, B., Aarts, J. E. C. M., Ammenwerth, E., Ferner, R. E., et al. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-111 · Cited by 107
System-Wide versus Component-Specific Trust Using Multiple Aids
Keller, D., & Rice, S. C. (2009) · The Journal of general psychology · doi:10.1080/00221300903266713 · Cited by 102
“In many complex systems, the number or complexity of the tasks is too much for human operators to handle safely or efficiently (Sheridan, 1987; Wickens & Dixon, 2007).”
BackgroundSystem reliability, performance and trust in adaptable automation.
Chavaillaz, A., Wastell, D., & Sauer, J. S. (2016) · Applied Ergonomics · doi:10.1016/j.apergo.2015.07.012 · Cited by 102
“Although some studies have not shown such negative effects (e.g. Parasuraman et al., 1993a), they are outnumbered by studies which do (for an overview, see Wickens and Dixon, 2007).”
Augmented Reality Cues and Elderly Driver Hazard Perception
Schall, M., Rusch, M. L., Lee, J. D., Dawson, J., Thomas, G. W., Aksan, N., & Rizzo, M. (2013) · Hum. Factors · doi:10.1177/0018720812462029 · Cited by 101
“The system had an overall reliability of at least 85% in all driving scenarios and was greater than the estimated 70% “crossover point” below which unreliable automation appears to be worse than no automation at all (Wickens & Dixon, 2007).”
BackgroundChen, J. Y. C., & Terrence, P. (2009) · Ergonomics · doi:10.1080/00140130802680773 · Cited by 99
“Furthermore, Wickens and Dixon (2005) demonstrated that when the reliability level is below approximately 70%, operators often ignore the alerts.”
BackgroundMacnamara, B. N., Berber, I., Çavuşoğlu, M. C., Krupinski, E. A., Nallapareddy, N., Nelson, N. E., Smith, P. J., Wilson-Delfosse, A. L., & Ray, S. (2024) · Cognitive Research: Principles and Implications · doi:10.1186/s41235-024-00572-8 · Cited by 97
“Quantitative syntheses of the literature suggest that the ‘crossover point’ from benefits to detriments, at least in high work-load conditions, is around 70% accuracy (Parasuraman & Manzey, 2010; Wickens & Dixon, 2007).”
BackgroundAgent Transparency: A Review of Current Theory and Evidence
Bhaskara, A., Skinner, M., & Loft, S. (2020) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2020.2965529 · Cited by 95
“If increased transparency can increase the ease of cross checking the validity of recommendations by highlighting key information, then transparency should mitigate the impact of two key factors known to reduce the extent to which operators seek to validate recommendations: 1) high concurrent task demands and 2) high…”
BackgroundCognitive conflict in human-automation interactions: a psychophysiological study.
Dehais, F., Causse, M., Vachon, F., & Tremblay, S. (2012) · Applied Ergonomics · doi:10.1016/j.apergo.2011.09.004 · Cited by 91
“, 2005) and deteriorate the human operator’s global performance (Dixon et al., 2007; Wickens and Dixon, 2007).”
BackgroundWhat, if all alerts were specific - estimating the potential impact on drug interaction alert burden
Seidling, H. M., Klein, U., Schaier, M., Czock, D., Theile, D., Pruszydlo, M. G., Kaltschmidt, J., Mikus, G., & Haefeli, W. E. (2014) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2013.12.006 · Cited by 91
Understanding human management of automation errors
McBride, S. E., Rogers, W. A., & Fisk, A. D. (2014) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2013.817625 · Cited by 82
“Wickens and Dixon (2007) focused on modelling the role of reliability in human interaction with automated diagnostic aids.”
BackgroundBalfe, N., Sharples, S., & Wilson, J. R. (2014) · Applied Ergonomics · doi:10.1016/j.apergo.2014.08.002 · Cited by 87
“During disruption, ARS cannot be relied upon to make a correct decision, due to limitations in the algorithms that cannot account for all circumstances or for changes in the timetable since the algorithmswere designed, and therefore this system represents that of an ‘imperfect’ automation system (Wickens and Dixon, 20…”
BackgroundInfluentialCooperative warning systems: The impact of false and unnecessary alarms on drivers' compliance.
Naujoks, F., Kiesel, A., & Neukum, A. (2016) · Accident Analysis and Prevention · doi:10.1016/j.aap.2016.09.009 · Cited by 80
A framework for explaining reliance on decision aids
van Dongen, K., & van Maanen, P.-P. (2012) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2012.10.018 · Cited by 82
Sauer, J., Chavaillaz, A., & Wastell, D. (2016) · Ergonomics · doi:10.1080/00140139.2015.1094577 · Cited by 71
“The focus of research on the management of automation failure has been on improving system design (e.g. reliability levels, Wickens and Dixon 2007; message style of warnings, Lee, Gore, and Campbell 1999), whereas the issue of training has been given less attention, even though training is critical…”
BackgroundNeyedli, H., Hollands, J. G., & Jamieson, G. (2011) · Hum. Factors · doi:10.1177/0018720811413767 · Cited by 71
“Wickens and Dixon (2007) performed a meta-analysis of studies examining automation reliability and human performance and found that human performance improved mono-tonically with system reliability and also that automation with a reliability level less than about 70% was no better than manual…”
BackgroundWickens, C., & Colcombe, A. (2007) · Hum. Factors · doi:10.1518/001872007x230217 · Cited by 71
“…become less dependent, but even as reliability drops below a threshold at around r = .75 (d′ = 1.35), humans may continue to depend on the imperfect diagnostic automation, even if their performance would be better if this automated advice were ignored (Maltz & Shinar, 2003; Wickens & Dixon, 2007).”
BackgroundInfluentialSelf-citationUnderstanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System
Balfe, N., Sharples, S., & Wilson, J. R. (2018) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720818761256 · Cited by 74
“Automation must therefore be extremely reliable if high levels of trust and usage are to be achieved; Wickens and Dixon (2007), in a meta-analysis, found that less than 70% reliability of automation is worse than useless.”
BackgroundGeels-Blair, K., Rice, S. C., & Schwark, J. D. (2013) · International Journal of Aviation Psychology · doi:10.1080/10508414.2013.799355 · Cited by 69
“For example, diagnostic automated aids associated with a task typically assist the operator by reducing cognitive load (Wickens & Dixon, 2007).”
Benchmarking Aided Decision Making in a Signal Detection Task
Bartlett, M. L., & McCarley, J. S. (2017) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720817700258 · Cited by 74
“Even if the automation errs in occasional judgments, the human operator may be able to achieve a higher sensitivity with the aid’s assistance than without it (Wickens & Dixon, 2007).”
BackgroundJiao, J. R., Zhou, F., Gebraeel, N., & Duffy, V. G. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1722324 · Cited by 78
“…as levels of trust dynamically change throughout the course of observations about the automation’s behaviour, it is important that interaction decisions and consequent behaviours should reflect the extant level of trust under uncertainty (Wickens and Dixon 2007; Wang, Jamieson, and Hollands 2009).”
BackgroundAutomation trust and attention allocation in multitasking workspace.
Karpinsky, N. D., Chancey, E. T., Palmer, D. B., & Yamani, Y. (2018) · Applied Ergonomics · doi:10.1016/j.apergo.2018.03.008 · Cited by 64
Drnec, K., Marathe, A. R., Lukos, J. R., & Metcalfe, J. S. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00290 · Cited by 81
“…is important enough that as long as errors are predictable and the automation error rate is at a consistent rate of approximately 30% or less, most human users will decide to continue to use and benefit from the automation (Parasuraman et al., 2000; Wickens and Dixon, 2007; Wang et al., 2009).”
BackgroundEpstein, R., Dexter, F., & Patel, N. (2015) · Anesthesia and Analgesia · doi:10.1213/ane.0000000000000677 · Cited by 62
“57 Consequently, we also elected not to implement this PACU census management system.”
BackgroundMethodThe Role of Trust as a Mediator Between System Characteristics and Response Behaviors
Chancey, E. T., Bliss, J. P., Proaps, A. B., & Madhavan, P. (2015) · Hum. Factors · doi:10.1177/0018720815582261 · Cited by 61
“Because of the effects of false alarms and misses on human behavior, system reliability is often discussed in the automation literature (Wickens & Dixon, 2007).”
BackgroundResultInfluentialPak, R., McLaughlin, A., & Bass, B. (2014) · Ergonomics · doi:10.1080/00140139.2014.928750 · Cited by 59
“In their review of the literature, Wickens and Dixon (2007) proposed that an automation reliability of about 70% represented a critical inflection point; less than about 70% reliable was not relied upon while reliabilities higher than 70% led to complacency.”
Rovira, E., & Parasuraman, R. (2010) · Hum. Factors · doi:10.1177/0018720810375692 · Cited by 59
“The reason could be simply the low power associated with analyzing data from single trials (Wickens & Dixon, 2005).”
Lee, J., Abe, G., Sato, K., & Itoh, M. (2021) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2021.06.013 · Cited by 76
Kumar, A., McMahon, G., Reid, T., & Jain, N. (2020) · IEEE Control Systems · doi:10.1109/mcs.2020.3019151 · Cited by 58
“Nevertheless, even imperfect acquisition and analysis automation at a reliability as low as 70% , can improve performance as compared to unaided human performance [20].”
BackgroundWang, N., Pynadath, D., Rovira, E., Barnes, M., & Hill, S. (2018) · International Conference on Persuasive Technology · doi:10.1007/978-3-319-78978-1_5 · Cited by 56
“Research on automation reliability on trust and human-automation team has indicated that a reliability of 80% ([25]) or above 70% ([26]) to be a suitable setting for similar studies.”
ResultHattenschwiler, N., Sterchi, Y., Mendes, M., & Schwaninger, A. (2018) · Applied Ergonomics · doi:10.1016/j.apergo.2018.05.003 · Cited by 54
AUGMENTED REALITY CUES TO ASSIST OLDER DRIVERS WITH GAP ESTIMATION FOR LEFT-TURNS
Rusch, M. L., Schall, M., Lee, J. D., Dawson, J., & Rizzo, M. (2014) · Accident Analysis and Prevention · doi:10.1016/j.aap.2014.05.020 · Cited by 54
“Differences across conditions would have suggested variable levels of trust (consistent with Wickens and Dixon, 2007).”
Ezer, N., Fisk, A., & Rogers, W. (2008) · Hum. Factors · doi:10.1518/001872008x375018 · Cited by 54
“…reliability level was chosen because previous research has found this to be a critical “crossover” point for performance with imperfect automation (Wickens & Dixon, 2007) and because older adults appear to be sensitive to changes from 80% to 60% decision aid reliability (Fisk, Rogers, &…”
MethodHuman Performance Consequences of Automated Decision Aids: The Impact of Time Pressure
Rieger, T., & Manzey, D. (2020) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820965019 · Cited by 55
“…level in order to create a clear variation but still have a level that seems to be realistic for false-prone systems and that is still higher than the 70% threshold assumed to be the minimum reliability where automated sys - tems are still considered to be useful (Wickens & Dixon, 2007).”
BackgroundModels of Attention, Distraction, and Highway Hazard Avoidance
Wickens, C., & Horrey, W. (2009) · CRC Press eBooks · doi:10.1201/9781420007497.ch5 · Cited by 53
Self-citationUsing Tools to Help Us Think: Actual but Also Believed Reliability Modulates Cognitive Offloading
Weis, P., & Wiese, E. (2018) · Hum. Factors · doi:10.1177/0018720818797553 · Cited by 51
“Specifically, Wickens and Dixon (2007) found that automation with reliabilities below 70% was, on average, worse than no automation at all.”
BackgroundInfluentialMitigation of Conflicts with Automation
Dehais, F., Causse, M., & Tremblay, S. (2011) · Hum. Factors · doi:10.1177/0018720811418635 · Cited by 51
“Unreliable diagnostic automation has been shown to negatively affect attentional resources (Wickens, Dixon, Goh, & Hammer, 2005) and to degrade global human operator performance (Dixon, Wickens, & McCarley, 2007; Wickens & Dixon, 2007).”
BackgroundPassalacqua, M., Pellerin, R., Yahia, E., Magnani, F., Rosin, F., Joblot, L., & Léger, P. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2319914 · Cited by 56
“Additionally, a reliability percentage of approximately 85% has been commonly used in past studies (e.g., Avril et al., 2022; Wickens & Dixon, 2007).”
Expertise, Automation and Trust in X-Ray Screening of Cabin Baggage
Chavaillaz, A., Schwaninger, A., Michel, S., & Sauer, J. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00256 · Cited by 49
Using System-Wide Trust Theory to Make Predictions About Dependence on Four Diagnostic Aids
Rice, S. C., & Geels, K. (2010) · The Journal of general psychology · doi:10.1080/00221309.2010.499397 · Cited by 49
“It is intuitive that the number or complexity of the tasks may be too much for operators to handle safely ( Sheridan, 1987 ; Wickens & Dixon, 2007 ); therefore, automation may be used to augment or even to replace these tasks.”
BackgroundDevelopment of design principles for automated systems in transport control
Balfe, N., Wilson, J. R., Sharples, S. C., & Clarke, T. (2012) · Ergonomics · doi:10.1080/00140139.2011.636456 · Cited by 47
“Workload refers to the load or demand imposed on the human operator and may be either physical or cognitive in nature (Wickens and Dixon 2007).”
BackgroundAutomation trust increases under high-workload multitasking scenarios involving risk
Sato, T., Yamani, Y., Liechty, M., & Chancey, E. T. (2019) · Cognition Technology & Work · doi:10.1007/s10111-019-00580-5 · Cited by 52
Rovira, E., Pak, R., & McLaughlin, A. (2017) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2016.1252806 · Cited by 46
“We manipulated task load because evidence from a review of 20 automation reliability studies suggested that dependence on imperfect automation would be stronger under higher task load (because the operator ’ s limited resources are expended; Wickens and Dixon 2007).”
Team Performance in Networked Supervisory Control of Unmanned Air Vehicles
McKendrick, R. D., Shaw, T. H., de Visser, E. J., Saqer, H., Kidwell, B., & Parasuraman, R. (2013) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720813496269 · Cited by 44
“Single-operator systems still gain performance benefits from automated decision aids even when the information presented by the aid is imperfect or less than fully informative (de Visser & Para-suraman, 2011; Wickens & Dixon, 2007).”
BackgroundWashburn, A., Adeleye, A., An, T., & Riek, L. (2020) · ACM Trans. Hum. Robot Interact. · doi:10.1145/3380783 · Cited by 45
“This is consistent with previous work showing that the performance of a human-automation team will be more efficient than a human completing the same task without automation as long as the reliability of the automation is greater than 70% [75].”
ResultInfluence of lane departure warnings onset and reliability on car drivers' behaviors.
Navarro, J., Deniel, J., Yousfi, E., Jallais, C., Bueno, M., & Fort, A. (2017) · Applied Ergonomics · doi:10.1016/j.apergo.2016.08.010 · Cited by 45
“Following this rationale, assistances with less than approximately 70% of reliability were found to be worse than no assistance (Wickens and Dixon, 2007).”
InfluentialFoundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience
Schmorrow, D., & Fidopiastis, C. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-39952-2 · Cited by 45
“Barriers to incorporating ITS (and digital tools, in general) are further compounded for classrooms in developing countries with respect to availability of hardware, infrastruc‐ ture, and appropriate instructional content [11].”
BackgroundMethodInfluentialDelPreto, J., Lipton, J., Sanneman, L. M., Fay, A. J., Fourie, C. K., Choi, C., & Rus, D. (2020) · IEEE International Conference on Robotics and Automation · doi:10.1109/icra40945.2020.9196754 · Cited by 44
“It has been observed that automation must maintain at least a 70% success level to maintain user trust [43], and that imperfect automation can still be beneficial [44].”
BackgroundThe out-of-the-loop Brain: A neuroergonomic approach of the human automation interaction
Berberian, B., Somon, B., Sahaï, A., & Gouraud, J. (2017) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2017.09.010 · Cited by 52
“Interestingly, these findings have been modeled computationally (Farrell & Lewandowsky, 2000; Wickens & Dixon, 2007).”
BackgroundAI Reliance and Decision Quality: Fundamentals, Interdependence, and the Effects of Interventions
Schoeffer, J., Jakubik, J., Vössing, M., Kühl, N., & Satzger, G. (2025) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.15873 · Cited by 36
“A relevant line of prior work has studied how different degrees of reliability of automation support affect human decision-making (Dunning et al., 2024; Rovira et al., 2007; Wickens & Dixon, 2007; de Visser & Parasuraman, 2011).”
BackgroundMethodHussein, A., Elsawah, S., & Abbass, H. A. (2020) · Ergonomics · doi:10.1080/00140139.2020.1764112 · Cited by 51
Wohleber, R. W., Matthews, G., Lin, J., Szalma, J., Calhoun, G., Funke, G., Chiu, C., & Ruff, H. (2018) · Hum. Factors · doi:10.1177/0018720818799468 · Cited by 42
Taking advice from intelligent systems: the double-edged sword of explanations
Ehrlich, K., Kirk, S. E., Patterson, J., Rasmussen, J. C., Ross, S. I., & Gruen, D. (2011) · International Conference on Intelligent User Interfaces · doi:10.1145/1943403.1943424 · Cited by 42
“Studies on automation in decision-support have explored the consequences of providing imperfect information [11, 22].”
InfluentialPotential performance theory (PPT): Describing a methodology for analyzing task performance
Trafimow, D., & Rice, S. C. (2009) · Behavior Research Methods · doi:10.3758/brm.41.2.359 · Cited by 42
“…automation during performance tasks (e.g., Bainbridge, 1983; Dixon & Wickens, 2006; Dixon, Wickens, & Chang, 2005; Dixon, Wickens, & McCarley, 2007; Lee & Moray, 1994; Parasuraman & Riley, 1997; Parasuraman, Sheridan, & Wickens, 2000; Rice, in press; Rice et al., in press; Wickens & Dixon, 2007).”
Rebensky, S., Carmody, K., Ficke, C., Carroll, M., & Bennett, W. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.782134 · Cited by 40
“This is similar to other UAV studies (e.g., 86%, Wohleber et al., 2019; 90%, Chen and Barnes, 2012; 95%, Ruff et al., 2002) and was chosen as automation will always be, to some extent, imperfect but needs to be higher than 70% to still be utilized by operators (Wickens and Dixon, 2007).”
ResultTrust Mediating Reliability–Reliance Relationship in Supervisory Control of Human–Swarm Interactions
Hussein, A., Elsawah, S., & Abbass, H. (2019) · Hum. Factors · doi:10.1177/0018720819879273 · Cited by 40
“These levels were chosen to be at least 70% (Wickens & Dixon, 2007) to ensure that automation is beneficial to the performance (Guideline 1).”
BackgroundInfluentialThe Effect of Incorrect Reliability Information on Expectations, Perceptions, and Use of Automation
Barg‐Walkow, L. H., & Rogers, W. A. (2015) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815610271 · Cited by 51
“Wickens and Dixon (2005) found that automation with less than approximately 70% reliability is considered worse than not using automation.”
BackgroundMethodHuman factors in non-destructive testing (NDT): risks and challenges of mechanised NDT
Bertovic, M. (2015) · doi:10.14279/depositonce-4685 · Cited by 40
“…error rates have found evidence of misuse rather than disuse, and that disuse is more likely to happen when working with systems with reliability lower than 70 % (Wickens & Dixon, 2007), it implies that the error rate might not have been a direct cause of disuse, or at least not the only one.”
BackgroundA Hidden Markov Framework to Capture Human–Machine Interaction in Automated Vehicles
Janssen, C., Boyle, L., Kun, A. L., Ju, W., & Chuang, L. (2019) · International journal of human computer interactions · doi:10.1080/10447318.2018.1561789 · Cited by 39
“Dynamically adjusting the system mode, given an understanding of the changes in user’s beliefs over time, might also be crucial given their trust in the automation (Abe & Richardson, 2006; Bliss & Acton, 2003; Riener, Boll, & Kun, 2016; Wickens & Dixon, 2007).”
BackgroundAutopilots 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
Huegli, D., Merks, S., & Schwaninger, A. (2020) · Applied Ergonomics · doi:10.1016/j.apergo.2020.103094 · Cited by 38
Crossing the boundaries of automation - Function allocation and reliability
Onnasch, L. (2015) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2014.12.004 · Cited by 38
TIP: A Trust Inference and Propagation Model in Multi-Human Multi-Robot Teams
Guo, Y., Yang, X. J., & Shi, C. (2023) · Autonomous Robots · doi:10.1007/s10514-024-10175-3 · Cited by 37
“90% and 60% were chosen because they are commonly used in Human Factors/HCI studies as the upper and lower bounds of imperfect autonomy (Wickens and Dixon, 2007).”
Towards Meaningfully Integrating Human-Autonomy Teaming in Applied Settings
Schelble, B. G., Flathmann, C., & Mcneese, N. J. (2020) · International Conference on Human-Agent Interaction · doi:10.1145/3406499.3415077 · Cited by 37
“Research has shown that autonomous agents with a reliability level below 70% produce such negative results that not implementing any autonomous agent is better [42].”
BackgroundRice, S., & Winter, S. (2015) · Aviation Psychology and Applied Human Factors · doi:10.1027/2192-0923/a000081 · Cited by 37
Ehrenfeld, J. M., Dexter, F., Rothman, B., Minton, B. S., Johnson, D., Sandberg, W., & Epstein, R. (2013) · Anesthesia and Analgesia · doi:10.1213/ane.0b013e3182a8b0bd · Cited by 37
Carter, O. B. J., Loft, S. D., & Visser, T. A. W. (2023) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208231218156 · Cited by 42
“%) is well below the 70% threshold traditionally assumed necessary to achieve human-automation team trust (Lee & See, 2004; Wickens & Dixon, 2007).”
BackgroundKnowing When to Pass: The Effect of AI Reliability in Risky Decision Contexts
Elder, H., Canfield, C., Shank, D. B., Rieger, T., & Hines, C. (2022) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208221100691 · Cited by 53
“In general, systems above a threshold of .70 reliability tend to improve user performance (Wickens & Dixon, 2007).”
BackgroundMichailovs, S., Visser, T. A. W., Huf, S., & Loft, S. D. (2017) · Journal of Experimental Psychology Applied · doi:10.1037/xap0000126 · Cited by 37
Effects of Agent Transparency on human-autonomy teaming effectiveness
Chen, J. Y. C., Barnes, M., Selkowitz, A. R., & Stowers, K. (2016) · IEEE International Conference on Systems, Man and Cybernetics · doi:10.1109/smc.2016.7844505 · Cited by 34
Indian and American consumer perceptions of cockpit configuration policy
Winter, S., Rice, S., Mehta, R., Cremer, I., Reid, K. M., Rosser, T. G., & Moore, J. C. (2015) · Journal of Air Transport Management · doi:10.1016/j.jairtraman.2014.11.003 · Cited by 34
Exploring system wide trust prevalence and mitigation strategies with multiple autonomous agents
Walliser, J. C., de Visser, E. J., & Shaw, T. H. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107671 · Cited by 37
Metadata
- Authors
- Wickens, C. D., & Dixon, S. R.
- Corresponding author
- Wickens, Christopher D.
- Venue
- Theoretical Issues in Ergonomics Science
- Publisher
- Informa UK Limited
- Published
- 2007-05
- Volume
- 8
- Issue
- 3
- Pages
- 201-212
- ISSN
- 1463-922X (ISSN-L)
- 1464-536X
- OpenAlex
- W2019160338
- Cited by
- 423
- References
- 0
- Citations by year
- 2026: 31 · 2025: 25 · 2024: 32 · 2023: 26 · 2022: 27 · 2021: 28 · 2020: 29 · 2019: 19 · 2018: 24 · 2017: 18 · 2016: 26 · 2015: 19 · 2014: 22 · 2013: 27 · 2012: 18
- FWCI
- 15.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Theoretical Issues in Ergonomics Science (publishedVersion)
- Funders
- University of Illinois at Urbana-Champaign
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Risk and Safety Analysis
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Keywords
- automated diagnosis, automation reliability, operator performance, human-automation interaction, workload, crossover point, dual-task performance
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