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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
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Cited by
Sorted by citations
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Influence of human-machine interactions and task demand on automation selection and use
Navarro, J., Heuveline, L., Avril, E., & Cegarra, J. (2018) · Ergonomics · doi:10.1080/00140139.2018.1501517 · Cited by 32
“In broad terms, automation introduction generally improves the human-machine system performances in regular circumstances, but it can also tarnish performances in case of automation failures (see Wickens and Dixon 2007 for a literature review).”
BackgroundBueno, M., Fabrigoule, C., Deleurence, P., Ndiaye, D., & Fort, A. (2012) · Brain Research · doi:10.1016/j.brainres.2012.06.027 · Cited by 32
Effect of Level of Automation on Unmanned Aerial Vehicle Routing Task
Calhoun, G., Draper, M., & Ruff, H. (2009) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120905300408 · Cited by 32
“%) was close to the estimated “crossover point”, below which unreliable automation is typically worse than no automation at all; Wickens and Dixon, 2005).”
BackgroundInvestigating the Effects of (Empty) Promises on Human-Automation Interaction and Trust Repair
Albayram, Y., Jensen, T., Khan, M. M. H., Fahim, M. A. A., Buck, R., & Coman, E. (2020) · Proceedings of the 8th International Conference on Human-Agent Interaction · doi:10.1145/3406499.3415064 · Cited by 31
“These levels of accuracy were chosen based on prior work identifying 70% as the accuracy at which automation is considered better than the lack thereof [41].”
MethodSimulated automated facial recognition systems as decision-aids in forensic face matching tasks.
Carragher, D. J., & Hancock, P. (2022) · Journal of Experimental Psychology General · doi:10.1037/xge0001310 · Cited by 36
“Third, these fi ctitious AFRS had unchar-acteristically low accuracy, which can reduce the operator ’ s reliance on a decision-aid (Wickens & Dixon, 2007), and limits the generalization of these fi ndings to operational settings with more accurate systems.”
BackgroundResultInfluentialPractice makes better - Learning effects of driving with a multi-stage collision warning.
Winkler, S., Kazazi, J., & Vollrath, M. (2018) · Accident Analysis and Prevention · doi:10.1016/j.aap.2018.01.018 · Cited by 31
Why Are People’s Decisions Sometimes Worse with Computer Support?
Alberdi, E., Strigini, L., Povyakalo, A. A., & Ayton, P. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-04468-7_3 · Cited by 29
“Similarly, Wickens and Dixon [23] question the notions of complacency or reduced vigilance as explanations of automation bias.”
BackgroundYadav, A., & Sagar, M. (2021) · Global Journal of Flexible Systems Management · doi:10.1007/s40171-021-00278-6 · Cited by 29
Bueno, M., Fabrigoule, C., Ndiaye, D., & Fort, A. (2014) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2014.04.012 · Cited by 29
Felisberto, M., Lima, G. D. S., Celuppi, I. C., Fantonelli, M. D. S., Zanotto, W. L., Dias de Oliveira, J. M., Mohr, E. T. B., dos Santos, R. A., Scandolara, D. H., Cunha, C. L., et al. (2024) · Health Informatics Journal · doi:10.1177/14604582241263242 · Cited by 28
“37 In this context, Wickens and Dixon (2007) 38 reviewed the literature in search of indirect Figure 3.”
Ruskin, K., Corvin, C. G., Rice, S., Richards, G., Winter, S., & Ruskin, A. C. (2021) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2021.100502 · Cited by 28
Flammini, F., Marrone, S., Nardone, R., Caporuscio, M., & D'Angelo, M. (2020) · Future generations computer systems · doi:10.1016/j.future.2020.06.036 · Cited by 28
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
“even when it is imperfectly reliable, given that its reliability is greater than the threshold of automation assistance between 0.70 and 0.75 (Wickens & Dixon, 2007).”
BackgroundMethodResultInfluentialSelf-citationLi, M., Erickson, I. M., Cross, E. V., & Lee, J. D. (2023) · Hum. Factors · doi:10.1177/00187208231166624 · Cited by 27
“…that a reliability below 70% is the “ crossover point, ” where unreliable automation can be worse than no automation at all (Dixon and Wickens, 2006; Wickens and Dixon, 2007), future studies should further test the differences of conversational indicators of trust with a gradient level of…”
BackgroundHarada, Y., Katsukura, S., Kawamura, R., & Shimizu, T. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18115562 · Cited by 27
“According to a previous study, task performance can worsen by using an automated rather than a manual procedure when the reliability of automation is <70% [20].”
The Apple Does Fall Far from the Tree
Jensen, T., Albayram, Y., Khan, M. M. H., Fahim, M., Buck, R. W., & Coman, E. (2019) · Designing Interactive Systems Conference · doi:10.1145/3322276.3322349 · Cited by 27
“The accuracy in each reliability condition was chosen based on prior work identifying 70% as the level at which automation is considered reliable [43].”
MethodKunar, M., Watson, D., Taylor-Phillips, S., & Wolska, J. (2017) · Journal of experimental psychology. Applied · doi:10.1037/xap0000132 · Cited by 27
“Wolfe and Van Wert’s (2010) Multiple Decision Model (2010) proposed that under LP conditions false alarms should decrease.”
BackgroundTrapsilawati, F., Qu, X.-D., Wickens, C., & Chen, C.-H. (2015) · Ergonomics · doi:10.1080/00140139.2014.997301 · Cited by 27
“Employing data from Metzger and Parasuraman as well as others in a metaanalysis, Wickens and Dixon (2007) suggested that compared to the manual condition people can perform detection tasks better with the automation whose reliability is as low as around 70%.”
MethodSelf-citationOnnasch, L., Ruff, S., & Manzey, D. (2014) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2014.05.001 · Cited by 27
“According to previous studies (e.g. Dixon et al., 2007; Dixon and Wickens; 2006; Rovira et al., 2007; Wickens and Dixon, 2007; Wickens et al., 2005) we expected that, compared to higher reliability levels, lower alarm reliabilities should result in significant performance decrements in the…”
BackgroundMethodResultInfluentialUsing PPT to Analyze Suboptimal Human–Automation Performance
Rice, S. C., Trafimow, D., & Hunt, G. (2010) · The Journal of general psychology · doi:10.1080/00221301003645236 · Cited by 27
“…& McCarley, 2007; Dzindo-let, Pierce, Beck, & Dawe, 1999; Mosier, Skitka, Heers, & Burdick, 1998; Rice, 2009; Rice & Hunt, 2009; Rice & Keller, 2009; Rice, Keller, Hunt, & Trafimow, 2009; Rice, Trafimow, Clayton, & Hunt, in press; Skitka, Mosier, Burdick, & Rosenblatt, 2000; Wickens & Dixon, 2007).”
BackgroundInfluentialWarning Reliability and Driver Performance in Naturalistic Driving
Sullivan, J., Tsimhoni, O., & Bogard, S. (2008) · Hum. Factors · doi:10.1518/001872008x312332 · Cited by 27
“In this context, an unreliable warning may be allocated less attention, resulting in increased response delays (see Wickens & Dixon, 2005, for a discussion about the influence of reliability under high and low workload).”
BackgroundJensen, T., Khan, M. M. H., Fahim, M. A. A., & Albayram, Y. (2021) · Designing Interactive Systems Conference 2021 · doi:10.1145/3461778.3462102 · Cited by 26
“This was based on Wickens and Dixon’s finding that diagnostic aids with less than 70% reliability were worse for performance than no aid at all [46].”
MethodNavarro, J., Yousfi, E., Deniel, J., Jallais, C., Bueno, M., & Fort, A. (2016) · Ergonomics · doi:10.1080/00140139.2016.1158323 · Cited by 26
“This trend would confirm a prediction based on an analysis of 22 studies that indicated a reliability level of 70% as the point below which unreliable assistance would be worse than no assistance at all (Wickens and Dixon 2007).”
MethodRovira, E., Cross, A., Leitch, E., & Bonaceto, C. (2014) · Hum. Factors · doi:10.1177/0018720813519675 · Cited by 26
“This is consistent with previous research that suggests that as long as automation reliability is greater than 70% and the task is not too easy, performance improves (Wickens & Dixon, 2007).”
ResultAttribute-Driven Hidden Markov Model Trees for Intention Prediction
Antwarg, L., Rokach, L., & Shapira, B. (2012) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2012.2198212 · Cited by 24
“According to Wickens and Dixon [2007] below a level of around 70% accuracy, providing automation, assistance or guidance is worse than not providing it at all.”
BackgroundInfluentialHuman Interface and the Management of Information. Information and Interaction Design
Yamamoto, S. (2013) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-39209-2 · Cited by 26
Chavaillaz, A., Schwaninger, A., Michel, S., & Sauer, J. (2018) · Ergonomics · doi:10.1080/00140139.2018.1481231 · Cited by 25
Effects of expertise for automatic train operations
Brandenburger, N., & Jipp, M. (2017) · Cognition, Technology & Work · doi:10.1007/s10111-017-0434-2 · Cited by 25
“(2001) and others (Wickens and Dixon 2007; Ma and Kaber 2007; Chavaillaz et al.”
BackgroundHow does information congruence influence diagnosis performance?
Chen, K.-J., & Li, Z. (2015) · Ergonomics · doi:10.1080/00140139.2015.1005163 · Cited by 24
Zhang, Y., Yadav, A., Hopko, S. K., & Mehta, R. K. (2024) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3610978.3640649 · Cited by 23
Kluy, L., & Roesler, E. (2021) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181321651110 · Cited by 25
“Therefore, a cut-off value of 70% was chosen (Wickens & Dixon, 2007) in order to use a cut-off level where imperfection is perceived but not leading to an impression of complete faultiness.”
MethodTesting the Efficacy of Human-Human Trust Repair Strategies with Machines
Quinn, D. B., Pak, R., & de Visser, E. J. (2017) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601930 · Cited by 22
Chen, J. Y. C., Barnes, M., & Kenny, C. (2011) · IEEE/ACM International Conference on Human-Robot Interaction · doi:10.1145/1957656.1957793 · Cited by 23
“Similarly, Wickens, Dixon and Johnson [12] demonstrated a greater cost associated with FAP automation (than with MP automation) that affected both the automated and concurrent tasks.”
BackgroundInfluentialBustamante, E. A. (2009) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120905300419 · Cited by 23
15. Workload and Automation Reliability in Unmanned Air Vehicles
Wickens, C., Dixon, S. R., & Ambinder, M. S. (2006) · Advances in human performance and cognitive engineering research · doi:10.1016/s1479-3601(05)07015-3 · Cited by 23
Self-citationBowden, V., Griffiths, N., Strickland, L., & Loft, S. (2021) · Hum. Factors · doi:10.1177/00187208211037188 · Cited by 22
“To the extent that automation is reliable and trusted (Wickens & Dixon, 2007), humanautomation performance should exceed human manual performance.”
BackgroundIntersection crossing assist system: Transition from a road-side to an in-vehicle system
Becic, E., Manser, M., Creaser, J., & Donath, M. (2012) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2012.05.010 · Cited by 22
Nuisance Alerts in Operational ATC Environments: Classification and Frequencies
Friedman-Berg, F., Allendoerfer, K. R., & Pai, S. (2008) · doi:10.1177/154193120805200123 · Cited by 22
“Research in other domains has shown that if the reliability rate of an alert is lower than 70%, professionals would perform better, overall, if they ignored the alert entirely and relied on their own detection and decision-making abilities (Wickens & Dixon, 2005).”
BackgroundKim, J. Y., Lester, C., & Yang, X. J. (2025) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208251326795 · Cited by 21
“This reliability is above the baseline threshold level of around 70% to be perceived as useful (Wickens & Dixon, 2007).”
Kintz, J. R., Banerjee, N., Zhang, J. Y., Anderson, A. P., & Clark, T. (2022) · Hum. Factors · doi:10.1177/00187208221129371 · Cited by 21
Automation Type and Reliability Impact on Visual Automation Monitoring and Human Performance
Avril, E., Cegarra, J., Wioland, L., & Navarro, J. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1925435 · Cited by 23
“In their meta-analysis, Wickens and Dixon (2007) also noticed that trust in automation was able to modulate the 70% automation reliability threshold.”
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Drnec, K., & Metcalfe, J. (2016) · Interacción · doi:10.1007/978-3-319-39952-2_16 · Cited by 21
Agent Transparency for Human-Agent Teaming Effectiveness
Chen, J. Y. C., & Barnes, M. (2015) · IEEE International Conference on Systems, Man and Cybernetics · doi:10.1109/smc.2015.245 · Cited by 21
“This also sheds light on Wickens and Dixon [31] findings that automation with below 70% reliability may not be beneficial.”
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How Do We Assess the Trustworthiness of AI? Introducing the Trustworthiness Assessment Model (TrAM)
Schlicker, N., Baum, K., Uhde, A., Sterz, S., Hirsch, M. C., & Langer, M. (2022) · doi:10.31234/osf.io/qhwvx · Cited by 79
Do concurrent task demands impact the benefit of automation transparency?
Tatasciore, M., Bowden, V., & Loft, S. (2023) · Applied Ergonomics · doi:10.1016/j.apergo.2023.104022 · Cited by 20
The Impact of Increasing Autonomy on Training Requirements in a UAV Supervisory Control Task
Cummings, M., Huang, L.-X., Zhu, H., Finkelstein, D., & Wei, R. (2019) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343419868917 · Cited by 20
“In addition, previous research has indicated that 70% is a critical threshold for human trust (Wickens & Dixon, 2007).”
BackgroundTarget Detection and Identification Performance Using an Automatic Target Detection System
Reiner, A. J., Hollands, J. G., & Jamieson, G. (2017) · Hum. Factors · doi:10.1177/0018720816670768 · Cited by 20
“The effect of automation error type on human performance (Wickens & Dixon, 2007) appears to depend on the task being performed.”
BackgroundResultInfluentialDavenport, R. B., & Bustamante, E. A. (2010) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193121005401933 · Cited by 20
“Some automated systems can even harm performance making it worse than at baseline (Wickens & Dixon, 2007).”
BackgroundTsai, C.-C., Kim, J. Y., Chen, Q., Rowell, B. E., Yang, X. J., Kontar, R. A., Whitaker, M., & Lester, C. A. (2024) · Journal of Medical Internet Research · doi:10.2196/59946 · Cited by 20
“At 79% accuracy, our model is above the 0.70 reliability threshold wherein imperfect automation is preferable to no automation [32].”
InfluentialZang, J., & Jeon, M. (2022) · Multimodal Technologies and Interaction · doi:10.3390/mti6090082 · Cited by 19
“SAGAT queries were used to capture drivers’ situation awareness (SA) of their environment [35].”
BackgroundMethodInfluentialHopko, S. K., & Mehta, R. K. (2021) · Frontiers in Neuroergonomics · doi:10.3389/fnrgo.2021.731327 · Cited by 21
Driving with and without automation on the motorway – an observational study
Várhelyi, A., Kaufmann, C., Johnsson, C., & Almqvist, S. (2020) · Journal of Intelligent Transportation Systems / Taylor & Francis · doi:10.1080/15472450.2020.1738230 · Cited by 19
“If reliability is below 70 per cent, it is better having no automation at all (Wickens & Dixon, 2007).”
BackgroundTrust with increasing and decreasing reliability
Rittenberg, B. S. P., Holland, C. W., Barnhart, G. E., Gaudreau, S. M., & Neyedli, H. F. (2024) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208241228636 · Cited by 19
“…perhaps unsurprising given previous research which has indicated that automation needs to be at least 70% reliable to be useful to human operators (Wickens & Dixon, 2007); however; the results demonstrate that for automation that increases in reliability, the 70% reliability level cannot simply…”
InfluentialTransparency improves the accuracy of automation use, but automation confidence information does not
Tatasciore, M., Strickland, L. J. G., & Loft, S. D. (2024) · Cognitive Research Principles and Implications · doi:10.1186/s41235-024-00599-x · Cited by 23
“This reliability exceeds the 70% reliability threshold which increases the probability that humans rely on automation (Wickens & Dixon, 2007), while providing enough data points for statistical power.”
Warden, A. C., Wickens, C. D., Rehberg, D., Ortega, F. R., & Clegg, B. A. (2023) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2023.3302152 · Cited by 24
“[47], but a level of imperfect reliability that is nevertheless helpful in aiding the human-automation team performance [48].”
BackgroundSelf-citationInvestigating User Perceptions and Stereotypic Responses to Gender and Age of Voice Assistants
Watkins, H., & Pak, R. (2020) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181320641434 · Cited by 18
“The selected reliability percentages were informed by prior research detailing critical threshold points of reliability induced automation complacency (Wickens & Dixon, 2007).”
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Epstein, R., & Dexter, F. (2012) · Anesthesia and Analgesia · doi:10.1213/ane.0b013e31825c7f0c · Cited by 18
“The observed percentages of unresolved hypoxemic episodes were compared with 70%, the lower limit of an acceptable true alarm rate for clinical utility (see DISCUSSION).(13) First, analyses were performed including all hypoxemic episodes, and then second, limited to 1 randomly selected episode from each case.”
BackgroundInfluentialUser settings of cue thresholds for binary categorization decisions.
Botzer, A., Meyer, J., Bak, P., & Parmet, Y. (2010) · Journal of experimental psychology. Applied · doi:10.1037/a0018758 · Cited by 18
How Do Automation False Alarms and Misses Affect Operator Compliance and Reliance?
Dixon, S. R., Wickens, C., & McCarley, J. (2006) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120605000106 · Cited by 18
Self-citationMorey, D. A., Rayo, M. F., & Woods, D. D. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01784-y · Cited by 28
Avril, E. (2022) · Ergonomics · doi:10.1080/00140139.2022.2069870 · Cited by 21
“Wickens and Dixon (2007) explained that under a reliability level of 70%, the use of automation should be to ponder.”
BackgroundMethodResultInfluentialWu, X., She, M.-R., Li, Z., Song, F., & Sang, W. (2017) · Ergonomics · doi:10.1080/00140139.2017.1335884 · Cited by 17
“As most diagnoses are forced paced in the MCRs (Rouse 1978), the time pressure and interface design influence the human performance in digitalised task environments (Nikolic and Sarter 2007; Wickens and Dixon 2007).”
BackgroundTrust in Computers and Robots: The Uses and Boundaries of the Analogy to Interpersonal Trust
Atkinson, D., Hancock, P. A., Hoffman, R. R., Lee, J. D., Rovira, E. M., Stokes, C. K., & Wagner, A. R. (2012) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181312561071 · Cited by 15
“A review of twenty automation reliability studies suggests that operator reliance on imperfect automation is greater under high task demands because the operator’s limited resources are being depleted (Wickens and Dixon, 2005).”
BackgroundLyons, J. B., Mator, J. D., Orr, T., Alarcon, G. M., & Barrera, K. (2024) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/15553434231225909 · Cited by 20
The Effect of Two-Stage Warning System on Human Performance Along with Different Takeover Strategies
Wang, S., Liu, Y., Li, S., Liu, Z., You, X.-Q., & Li, Y. (2023) · Social Science Research Network · doi:10.2139/ssrn.4398187 · Cited by 16
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
“Based on the analysis of 20 studies, Wickens and Dixon (2007) focused only on the information stages (stages 1 and 2); therefore, it is also necessary to investigate this threshold using action automation with a range of reliability levels.”
BackgroundMethodIndividual Differences in Human-Robot Interaction in a Military Multitasking Environment
Chen, J. Y. C. (2011) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411399070 · Cited by 16
“The 60% reliability level was chosen on the basis of findings of a meta-analysis by Wickens and Dixon (2005) that operators often ignore alerts with reliability of less than 70% (which the authors called the “cross-over” point, below which unreliable automation was worse than no automation).”
MethodRetention of a Time Pressure Heuristic in a Target Identification Task
Rice, S. C., Keller, D., Trafimow, D., & Sandry, J. (2010) · The Journal of general psychology · doi:10.1080/00221309.2010.484447 · Cited by 16
“The goal of human-automation performance is to exceed that of the automation—a goal that the literature reveals to be quite difficult to attain (Wickens & Dixon, 2007; Dixon, Wickens & McCarley, 2007).”
BackgroundApplying the swift trust model to human-robot teaming
Haring, K. S., Phillips, E. K., Lazzara, E. H., Ullman, D. L., Baker, A. L., & Keebler, J. R. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819472-0.00017-4 · Cited by 20
Dogru, E. Ö., & Krämer, N. C. (2025) · Journal of Decision Systems · doi:10.1080/12460125.2025.2593251 · Cited by 15
“…falls below the critical reliability threshold of 70% identified in prior research as necessary for effective automation support (Onnasch, 2015; Wickens & Dixon, 2007), the reduced accuracy served a critical methodological purpose: it introduced sufficient disagreement between participants’…”
Herse, S., Vitale, J., & Williams, M. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2150691 · Cited by 21
“This notion is acknowledged by Wickens and Dixon (2007) who state, in reference to their 70% performance threshold, that “ in addition to the fact that the constant is only an estimate (which was surrounded by a 95% confidence interval of roughly 0.14) … we acknowledge the potential impact of many…”
BackgroundMethodInfluentialWickens, C. D., & Carswell, C. M. (2021) · Wiley eBooks · doi:10.1002/9781119636113.ch5 · Cited by 112
Self-citationIronic efficiency in automation-aided signal detection
Bartlett, M. L., & McCarley, J. S. (2020) · Ergonomics · doi:10.1080/00140139.2020.1809716 · Cited by 20
Yamani, Y., & McCarley, J. (2018) · Hum. Factors · doi:10.1177/0018720818759356 · Cited by 15
“Numerous other experiments have produced similar results (e.g., Bartlett & McCarley, 2017; Corcoran, Dennett, & Carpenter, 1970; Meyer, Wiczorek, & Gün-zler, 2013; for a review, see Wickens & Dixon, 2007).”
BackgroundResultOperator adaptation to changes in system reliability under adaptable automation
Chavaillaz, A., & Sauer, J. (2016) · Ergonomics · doi:10.1080/00140139.2016.1261187 · Cited by 18
“…review has provided ample evidence for the multiple effects of reduced system reliability, two meta-analyses have suggested that low system reliability does not only have incremental effects but it may also involve a more qualitative change (Wickens and Dixon 2007; Onnasch, Ruff, and Manzey 2014).”
BackgroundThe Duration of Automation Bias in a Realistic Setting
de Boer, R. D., Heems, W. J. H., & Hurts, K. (2014) · International Journal of Aviation Psychology · doi:10.1080/10508414.2014.949205 · Cited by 15
“…time for a discrepancy in Indicated Air Speed was not identified within 2 minutes (Dijk, Merwe, & Zon, 2011), suggesting that a longer period is required to identify contradictory information, particularly concerning systems that have proven to be reliable in the past (Wickens & Dixon, 2007).”
The Effect of Gestalt Psychology on the System-Wide Trust Strategy in Automation
Bean, N. H., Rice, S. C., & Keller, M. (2011) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181311551295 · Cited by 15
“Operators must rely on automation to help them overcome the complexity of these systems as they cannot safely and efficiently monitor and interact with these complex systems by themselves (Lee & See, 2004; Wickens & Dixon, 2007).”
Background(2021) · doi:10.1145/3461778.3461997 · Cited by 14
“that the reliability below 70% is considered worse than no automation [66].”
BackgroundHow do humans learn about the reliability of automation?
Strickland, L. J. G., Farrell, S., Wilson, M. K., Hutchinson, J., & Loft, S. D. (2024) · Cognitive Research Principles and Implications · doi:10.1186/s41235-024-00533-1 · Cited by 14
Buser, D., Schwaninger, A., Sauer, J., & Sterchi, Y. (2023) · Applied Ergonomics · doi:10.1016/j.apergo.2023.103995 · Cited by 14
Chai, C., Zhou, Z., Yin, W., David, H., & Zhang, S. (2022) · Journal of Intelligent and Connected Vehicles · doi:10.1108/jicv-03-2021-0003 · Cited by 14
Human interaction with automated aids: Implications for robo‐advisors
Bartlett, M. L., & McCarley, J. S. (2019) · Financial Planning Review · doi:10.1002/cfp2.1059 · Cited by 15
Acharya, A., Howes, A., Baber, C., & Marshall, T. (2018) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931218621033 · Cited by 14
“Given the review of studies from Wickens and Dixon (2007), it is interesting that we find a 70% threshold in some instances.”
BackgroundInfluentialEffects of information accuracy and volume on decision making
Gamble, K. R., Cassenti, D. N., & Buchler, N. (2018) · Military Psychology · doi:10.1080/08995605.2018.1425586 · Cited by 16
“Although some studies have tested 60% reliability against various other levels, results have been mixed (Wickens & Dixon, 2005).”
BackgroundResultRelationships between User Demographics and User Trust in an Autonomous Agent
Hillesheim, A. J., Rusnock, C. F., Bindewald, J. M., & Miller, M. E. (2017) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601560 · Cited by 14
“Previous research indicates that when automation has near perfect reliability, the human-automation team performs better than if the automation has degraded reliability (de Visser & Parasuraman, 2011; Dixon & Wickens, 2006; Dixon et al., 2006; Endsley, 2015; Wickens & Dixon, 2007).”
BackgroundInfluentialYamani, Y., & McCarley, J. S. (2016) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815621172 · Cited by 18
“Operators often fail to use an aid appropriately and therefore benefit less than possible from the aid’s assistance (Parasuraman & Riley, 1997; Wickens & Dixon, 2007).”
BackgroundConsumers’ Perceptions About Autopilots and Remote-Controlled Commercial Aircraft
Mehta, R., Rice, S., Winter, S., & Oyman, K. (2014) · doi:10.1177/1541931214581384 · Cited by 14
“In the field of aviation, automation has been progressively taking on a larger portion of the workload, while reliability in automation has been shown to improve task performance (Wickens & Dixon, 2007).”
BackgroundImperfect Automation in Scheduling Operator Attention on Control of Multi-Robots
Chien, S.-Y., Lewis, M., Mehrotra, S., & Sycara, K. (2013) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213571260 · Cited by 14
“Considering the inherent uncertainty of automation, assuming perfect assistance from automation is unrealistic (Wickens & Dixon, 2005).”
BackgroundThe Role of Trust as a Mediator between Signaling System Reliability and Response Behaviors
Chancey, E. T., Proaps, A. B., & Bliss, J. P. (2013) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213571063 · Cited by 14
“Researchers have explored the relationship between emergency signal reliability and task operator behavior extensively (see Wickens & Dixon, 2007).”
BackgroundFlammini, F., Mazzocca, N., Pappalardo, A., Pragliola, C., & Vittorini, V. (2011) · ARES · doi:10.1007/978-3-642-23300-5_15 · Cited by 14
“Since a few human operators are usually employed in security surveillance, human-factors related issues also need to be carefully addressed, including cognitive ergonomics in human-machine interaction [6].”
Zang, J., & Jeon, M. (2024) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2024.103384 · Cited by 13
Kim, J. Y., Marshall, V. D., Rowell, B. E., Chen, Q., Zheng, Y., Lee, J. D., Kontar, R. A., Lester, C. A., & Yang, X. J. (2024) · JMIR Human Factors · doi:10.2196/60273 · Cited by 16
“The AI accuracy was set as 82% to ensure that the AI would be perceived as useful while providing sufficient misses and false alarms [55].”
Automation Use: The Roles of Self-Confidence, Trust, and Workload
Patton, C. E. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231192708 · Cited by 14
“It often involves the level of agreement with automation, regardless of the true state of the task (i.e. reliance and compliance; see Wickens & Dixon, 2007; Parasuraman & Manzey, 2010, for reviews).”
BackgroundInhibitory Cognitive Control Allows Automated Advice to Improve Accuracy While Minimizing Misuse
Strickland, L. J. G., Heathcote, A., Bowden, V. K., Boag, R. J., Wilson, M. K., Khan, S., & Loft, S. D. (2021) · Psychological Science · doi:10.1177/09567976211012676 · Cited by 18
“This creates the potential for operators to erroneously act on incorrect advice (misuse; Lee & See, 2004) or disregard correct advice (disuse),1 although this is less likely with reliable automation (Wickens & Dixon, 2007).”
BackgroundDecision making with conflicting information: influencing factors and best practice guidelines
Carroll, M., & Sanchez, P. L. (2020) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2020.1764660 · Cited by 13
“The literature suggests that performers tend to have greater trust in, and utilize more often, those systems with the highest reported, experienced, or perceived reliability (Bahner, Huper, and Manzey 2008; Wickens and Dixon 2007; Skitka 1999; Bolstad and Endsley 1998; Levine and Samet 1973).”
BackgroundBaber, C., Morar, N., & McCabe, F. (2019) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2019.2896838 · Cited by 13
“It might be the case that EID provides sufficient overview of the domain to allow information gathering to be performed with no effect of automation reliability [3], [14]–[17].”
BackgroundXu, Z., Wang, G., Zhai, S., & Liu, P. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2176986 · Cited by 12
“In the literatures of human – automation interaction (HAI), human – computer interaction, and human factors engineering, dozens of studies offer evidence of the negative influences of unreliable and imperfect automation and of automation failures (e.g., Chen et al., 2021; Wickens & Dixon, 2007).”
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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