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Human and Machine Learning pp 245–264Cite as

Do I Trust a Machine? Differences in User Trust Based on System Performance

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Part of the book series: Human–Computer Interaction Series ((HCIS))

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.

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Acknowledgements

This work was supported in part by AOARD under grant No. FA2386-14-1-0022 AOARD 134131.

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Authors and Affiliations

  1. DATA61, CSIRO, 13 Garden St, Eveleigh, NSW, 2015, Australia

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

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  1. Kun Yu
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  2. Shlomo Berkovsky
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  3. Dan Conway
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  4. Ronnie Taib
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  5. Jianlong Zhou
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  6. Fang Chen
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Corresponding author

Correspondence to Kun Yu .

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Editors and Affiliations

  1. DATA61, CSIRO, Eveleigh, New South Wales, Australia

    Jianlong Zhou

  2. DATA61, CSIRO, Eveleigh, New South Wales, Australia

    Fang Chen

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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: Zhou, J., Chen, F. (eds) Human and Machine Learning. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-90403-0_12

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  • DOI: https://doi.org/10.1007/978-3-319-90403-0_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90402-3

  • Online ISBN: 978-3-319-90403-0

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