Effects of Information Source, Pedigree, and Reliability on Operator Interaction With Decision Support Systems

Madhavan, Poornima; Wiegmann, Douglas A.

doi:10.1518/001872007x230154

Cited by 118 publications

(105 citation statements)

References 25 publications

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“… If an automated system makes an error, then it is broken  If an automated system makes a mistake, then it is completely useless  Correctly-functioning automated systems are perfectly reliable  Only faulty automated systems provide imperfect results Madhavan and Wiegmann (2007) argued that initial biases related to perceptions of automation are likely to be implicit in nature (pp. 775).…”

Section: All-or-none Belief Itemsmentioning

confidence: 99%

“…Biases toward automation may be partly implicit in nature (Madhavan and Wiegmann, 2007). Thus, an IAT was used to assess participants' implicit attitudes toward automation.…”

Section: Manipulationsmentioning

confidence: 99%

“…The notion of the PAS has been discussed theoretically in several additional studies (Madhavan, et al, 2006;Madhavan & Wiegmann, 2007;Wickens & Hollands, 2000;Wiegmann, Rich, & Zhang, 2001), but no self-report measure has yet been developed to assess the PAS and associated expectations. Given the frequency with which the PAS is called upon in the automation trust literature, the lack of ability to directly assess it is a significant impediment to the advancement of knowledge in this area.…”

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confidence: 99%

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Continuous Calibration of Trust in Automated Systems

Merritt¹,

Huber²,

LaChapell-Unnerstall³

et al. 2014

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. SPONSOR/MONITOR'S ACRONYM(S)AFRL/RHXS SPONSORING/MONITORING AGENCY REPORT NUMBER AFRL-RH-WP-TR-2014-0026 DISTRIBUTION AVAILABILITY STATEMENTDistribution Statement A: Approved for public release. Distribution is unlimited SUPPLEMENTARY NOTES ABW-2014-2241; Cleared 12 May 201414. ABSTRACT This report details three studies that have been conducted in order to explore user calibration of trust in automation. In the first, we discover that allor-none thinking about automation reliability was associated with severe decreases in trust following an aid error, but high expectations for automation performance were not. In the second study, we examine predictors and outcomes of calibration of trust. We measured calibration in three different ways. We found that awareness of the aid's accuracy trajectory (whether it was getting more or less reliable over time) was a significant predictor of calibration. However, we found that none of the three measurements of calibration had strong associations with task performance or the ability to identify aid errors. We also describe the conceptual premise and design of our third and final study. This study examines the development, loss, and recovery of trust in a route planning aid in a military simulation context. The results of this study will be presented in our final report. 15.

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Section: All-or-none Belief Itemsmentioning

confidence: 99%

“…Biases toward automation may be partly implicit in nature (Madhavan and Wiegmann, 2007). Thus, an IAT was used to assess participants' implicit attitudes toward automation.…”

Section: Manipulationsmentioning

confidence: 99%

mentioning

confidence: 99%

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Continuous Calibration of Trust in Automated Systems

Merritt¹,

Huber²,

LaChapell-Unnerstall³

et al. 2014

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“…They called this effect cognitive anchoring. Studies have also shown that people generally trust in automated systems and consider them more reliable than manual operation ("perfect automation schema"; [24]) or other people [18,31,36]. Those positive attitudes may result a higher tendency to rely on the aid and comply with its suggestions, i.e.…”

Section: Aims Of the Study And Hypothesesmentioning

confidence: 99%

A human factors perspective on the use of automated aids in the evaluation of NDT data

Bertovic

2016

AIP Conference Proceedings

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Abstract. In comparison to manual NDT methods, mechanized NDT is considered to be more reliable for a number of reasons, one of which being that the role of the inspectors and, therewith, the potential for human error, have been reduced. However, human-automation interaction research suggests that in spite of its numerous benefits, automation can lead to new yet unknown risks. One of those risks is inappropriate reliance on automation, which can result in automation misuse and disuse. The aim of this study was to investigate the potential inappropriate use of automation (specificallythe automated aids) in NDT addressing therewith the prevalent belief in the high reliability of automation held by the NDT community. To address this issue, 70 NDT trainees were asked to control the results of an eddy current data evaluation, allegedly provided by an automated aid, i.e. indication detection and sizing software. Seven errors were implemented into the task and it was measured to what extent the participants agreed with the aid. The results revealed signs of both misuse (agreeing with the aid even though it is incorrect) and disuse (disagreeing with the aid even though it is correct) of the aid that can affect the reliability with which inspections are carried out. Whereas misuse could be explained by a lower propensity to take risks and by a decreased verification behavior-possibly due to bias towards automation and complacent behavior-, disuse was assigned to problems in establishing the sizing criterion or to general difficulties in sizing. The implications of these results for the NDT praxis including suggestions for the decrease of automation bias are discussed.

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“…These applications of intelligent automated agent systems have fundamentally changed the relationship between humans and automation. The role of human operators has transformed from a main controller to a teammate sharing control with automated agents [32]. However, when automated agents become more like a 'partners' rather than just tools [14], how humans calibrate appropriate trust relations while interacting with intelligent agent systems becomes an important but challenging question.…”

Section: Introductionmentioning

confidence: 99%

Personal Influences on Dynamic Trust Formation in Human-Agent Interaction

Huang

Bashir

2017

Proceedings of the 5th International Conference on Human Agent Interaction

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The development of automated technologies in our daily life has transformed the role of human operators from a controller to a teammate who shares control with automated agents. However, this 'teammate' relationship between humans and automation raises an important but challenging research question regarding the formation of human-agent trust. Considering that the formation of human-agent trust is a dynamic and sophisticated process involving human factors, this study conducted a two-phase online experiment to examine personal influences on users' trust propensity and their trust formation in human-agent interactions. Our findings revealed distinctive personal influences on dispositional trust and the formation of human-agent trust at different stages. We found that users who exhibit higher trust propensities in humans also develop higher trust toward automated agents in initial stages. This study, as the first of its kind, not only fills the gap of knowledge about personal influences on human-agent trust, but also offers opportunities to enhance the future design of automated agent systems.

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Effects of Information Source, Pedigree, and Reliability on Operator Interaction With Decision Support Systems

Abstract: The results provide a reference point for deriving indices of "optimal" user interaction with decision aids and for developing frameworks of trust in decision support systems.

Cited by 118 publications

References 25 publications

Continuous Calibration of Trust in Automated Systems

Continuous Calibration of Trust in Automated Systems

A human factors perspective on the use of automated aids in the evaluation of NDT data

Personal Influences on Dynamic Trust Formation in Human-Agent Interaction

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