Do I trust a machine?: Differences in user trust based on system performance

Kun Yu; Shlomo Berkovsky; Dan Conway; Ronnie Taib; Jianlong Zhou; Fang Chen

doi:10.1007/978-3-319-90403-0_12

Do I trust a machine? Differences in user trust based on system performance

Kun Yu, Shlomo Berkovsky, Dan Conway, Ronnie Taib, Jianlong Zhou, Fang Chen

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Trust plays an important role in various user-facing systems and applications. It is particularly important in the context of decision support systems, where the system’s output serves as one of the inputs for the users’ decision making processes. In this chapter, we study the dynamics of explicit and implicit user trust in a simulated automated quality monitoring system, as a function of the system accuracy. We establish that users correctly perceive the accuracy of the system and adjust their trust accordingly. The results also show notable differences between two groups of users and indicate a possible threshold in the acceptance of the system. This important learning can be leveraged by designers of practical systems for sustaining the desired level of user trust.

Original language	English
Title of host publication	Human and machine learning
Subtitle of host publication	visible, explainable, trustworthy and transparent
Editors	Jianlong Zhou, Fang Chen
Place of Publication	Cham, Switzerland
Publisher	Springer, Springer Nature
Chapter	12
Pages	245-264
Number of pages	20
ISBN (Electronic)	9783319904030
ISBN (Print)	9783319904023
DOIs	https://doi.org/10.1007/978-3-319-90403-0_12
Publication status	Published - 2018
Externally published	Yes

Publication series

Name	Human-Computer Interaction Series
Publisher	Springer
ISSN (Print)	1571-5035
ISSN (Electronic)	2524-4477

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10.1007/978-3-319-90403-0_12

Cite this

Yu, K., Berkovsky, S., Conway, D., Taib, R., Zhou, J., & Chen, F. (2018). Do I trust a machine? Differences in user trust based on system performance. In J. Zhou, & F. Chen (Eds.), Human and machine learning: visible, explainable, trustworthy and transparent (pp. 245-264). (Human-Computer Interaction Series). Springer, Springer Nature. https://doi.org/10.1007/978-3-319-90403-0_12

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title = "Do I trust a machine?: Differences in user trust based on system performance",

abstract = "Trust plays an important role in various user-facing systems and applications. It is particularly important in the context of decision support systems, where the system{\textquoteright}s output serves as one of the inputs for the users{\textquoteright} decision making processes. In this chapter, we study the dynamics of explicit and implicit user trust in a simulated automated quality monitoring system, as a function of the system accuracy. We establish that users correctly perceive the accuracy of the system and adjust their trust accordingly. The results also show notable differences between two groups of users and indicate a possible threshold in the acceptance of the system. This important learning can be leveraged by designers of practical systems for sustaining the desired level of user trust.",

author = "Kun Yu and Shlomo Berkovsky and Dan Conway and Ronnie Taib and Jianlong Zhou and Fang Chen",

year = "2018",

doi = "10.1007/978-3-319-90403-0_12",

language = "English",

isbn = "9783319904023",

series = "Human-Computer Interaction Series",

publisher = "Springer, Springer Nature",

pages = "245--264",

editor = "Jianlong Zhou and Fang Chen",

booktitle = "Human and machine learning",

address = "United States",

}

Yu, K, Berkovsky, S, Conway, D, Taib, R, Zhou, J & Chen, F 2018, Do I trust a machine? Differences in user trust based on system performance. in J Zhou & F Chen (eds), Human and machine learning: visible, explainable, trustworthy and transparent. Human-Computer Interaction Series, Springer, Springer Nature, Cham, Switzerland, pp. 245-264. https://doi.org/10.1007/978-3-319-90403-0_12

Do I trust a machine? Differences in user trust based on system performance. / Yu, Kun; Berkovsky, Shlomo; Conway, Dan et al.
Human and machine learning: visible, explainable, trustworthy and transparent. ed. / Jianlong Zhou; Fang Chen. Cham, Switzerland: Springer, Springer Nature, 2018. p. 245-264 (Human-Computer Interaction Series).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Do I trust a machine?

T2 - Differences in user trust based on system performance

AU - Yu, Kun

AU - Berkovsky, Shlomo

AU - Conway, Dan

AU - Taib, Ronnie

AU - Zhou, Jianlong

AU - Chen, Fang

PY - 2018

Y1 - 2018

N2 - Trust plays an important role in various user-facing systems and applications. It is particularly important in the context of decision support systems, where the system’s output serves as one of the inputs for the users’ decision making processes. In this chapter, we study the dynamics of explicit and implicit user trust in a simulated automated quality monitoring system, as a function of the system accuracy. We establish that users correctly perceive the accuracy of the system and adjust their trust accordingly. The results also show notable differences between two groups of users and indicate a possible threshold in the acceptance of the system. This important learning can be leveraged by designers of practical systems for sustaining the desired level of user trust.

AB - Trust plays an important role in various user-facing systems and applications. It is particularly important in the context of decision support systems, where the system’s output serves as one of the inputs for the users’ decision making processes. In this chapter, we study the dynamics of explicit and implicit user trust in a simulated automated quality monitoring system, as a function of the system accuracy. We establish that users correctly perceive the accuracy of the system and adjust their trust accordingly. The results also show notable differences between two groups of users and indicate a possible threshold in the acceptance of the system. This important learning can be leveraged by designers of practical systems for sustaining the desired level of user trust.

U2 - 10.1007/978-3-319-90403-0_12

DO - 10.1007/978-3-319-90403-0_12

M3 - Chapter

SN - 9783319904023

T3 - Human-Computer Interaction Series

SP - 245

EP - 264

BT - Human and machine learning

A2 - Zhou, Jianlong

A2 - Chen, Fang

PB - Springer, Springer Nature

CY - Cham, Switzerland

ER -

Yu K, Berkovsky S, Conway D, Taib R, Zhou J, Chen F. Do I trust a machine? Differences in user trust based on system performance. In Zhou J, Chen F, editors, Human and machine learning: visible, explainable, trustworthy and transparent. Cham, Switzerland: Springer, Springer Nature. 2018. p. 245-264. (Human-Computer Interaction Series). doi: 10.1007/978-3-319-90403-0_12

Do I trust a machine? Differences in user trust based on system performance

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