research-article

Trust, self-confidence, and operators' adaptation to automation

Authors:

Neville MorayAuthors Info & Claims

International Journal of Human-Computer Studies, Volume 40, Issue 1

Pages 153 - 184

https://doi.org/10.1006/ijhc.1994.1007

Published: 01 January 1994 Publication History

Abstract

The increasing use of automation to supplant human intervention in controlling complex systems changes the operators' role from active controllers (directly involved with the system) to supervisory controllers (managing the use of different degrees of automatic and manual control). This paper examines the relationship between trust in automatic controllers, self-confidence in manual control abilities, and the use of automatic controllers in operating a simulated semi-automatic pasteurization plant. Trust, combined with self-confidence, predicted the operators' allocation strategy. A Multitrait-multimethod matrix and logit functions showed how trust and self-confidence relate to the use of automation. An ARMAV time series model of the dynamic interaction of trust and self-confidence, combined with individual biases, accounted for 60.9-86.5% of the variance in the use of the three automatic controllers. In general, automation is used when trust exceeds self-confidence, and manual control when the opposite is true. Since trust and self-confidence are two factors that guide operators' interactions with automation, the design of supervisory control systems should include provisions to ensure that operators' trust reflects the capabilities of the automation and operators' self-confidence reflects their abilities to control the system manually.

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Cited By

Qian CWexler J(2024)Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI CollaborationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645198(370-384)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645198
Tankelevitch LKewenig VSimkute AScott ASarkar ASellen ARintel S(2024)The Metacognitive Demands and Opportunities of Generative AIProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642902(1-24)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642902
Zhang YYadav AHopko SMehta RGrollman DBroadbent EJu WSoh HWilliams T(2024)In Gaze We Trust: Comparing Eye Tracking, Self-report, and Physiological Indicators of Dynamic Trust during HRICompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640649(1188-1193)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640649
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Index Terms

Trust, self-confidence, and operators' adaptation to automation
1. Applied computing
  1. Computers in other domains
  2. Operations research
    1. Industry and manufacturing
      1. Command and control
2. Social and professional topics
  1. Professional topics
    1. Computing and business
      1. Automation

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Published In

cover image International Journal of Human-Computer Studies

International Journal of Human-Computer Studies Volume 40, Issue 1

Jan. 1994

180 pages

ISSN:1071-5819

Editor:
B. R. Gaines
Univ. of Calgary, Alberta, Canada

Issue’s Table of Contents

Copyright © Academic Press.

Publisher

Academic Press, Inc.

United States

Publication History

Published: 01 January 1994

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Cited By

Qian CWexler J(2024)Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI CollaborationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645198(370-384)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645198
Tankelevitch LKewenig VSimkute AScott ASarkar ASellen ARintel S(2024)The Metacognitive Demands and Opportunities of Generative AIProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642902(1-24)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642902
Zhang YYadav AHopko SMehta RGrollman DBroadbent EJu WSoh HWilliams T(2024)In Gaze We Trust: Comparing Eye Tracking, Self-report, and Physiological Indicators of Dynamic Trust during HRICompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640649(1188-1193)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640649
Smith CRoychoudhury APaiva AAbreu RStorey M(2024)Trustworthy by DesignProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3649400(1-4)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3649400
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https://dl.acm.org/doi/10.1145/3626705.3627773
Williams KYuh MJain N(2023)A Computational Model of Coupled Human Trust and Self-confidence DynamicsACM Transactions on Human-Robot Interaction10.1145/359471512:3(1-29)Online publication date: 23-Jun-2023
https://dl.acm.org/doi/10.1145/3594715
Chung MYang YWang LCento GJerath KRaman ALie DChignell M(2023)Implementing Data Exfiltration Defense in Situ: A Survey of Countermeasures and Human InvolvementACM Computing Surveys10.1145/358207755:14s(1-37)Online publication date: 25-Jan-2023
https://dl.acm.org/doi/10.1145/3582077
Kim AYang MZhang J(2023) When Algorithms Err: Differential Impact of Early vs. Late Errors on Users’ Reliance on AlgorithmsACM Transactions on Computer-Human Interaction10.1145/355788930:1(1-36)Online publication date: 18-Mar-2023
https://dl.acm.org/doi/10.1145/3557889
Degachi CTielman MAl Owayyed M(2023)Trust and Perceived Control in Burnout Support ChatbotsExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585780(1-10)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585780
Svikhnushina ESchellenberg MNiedbala ABarisic IMiles J(2023)Expectation vs Reality in Users’ Willingness to Delegate to Digital AssistantsExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585763(1-7)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585763
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