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User Trust Dynamics: An Investigation Driven by Differences in System Performance

Published: 07 March 2017 Publication History

Abstract

Trust is a key factor affecting the way people rely on automated systems. On the other hand, system performance has comprehensive implications on a user's trust variations. This paper examines systems of varied levels of accuracy, in order to reveal the relationship between system performance, a user's trust and reliance on the system. In particular, it is identified that system failures have a stronger effect on trust than system successes. We also describe how patterns of trust change according to a number of consecutive system failures or successes. Importantly, we show that increasing user familiarity with the system decreases the rate of trust change, which provides new insights on the development of user trust. Finally, our analysis established a correlation between a user's reliance on a system and their trust level. Combining all these findings can have important implications in general system design and implementation, by predicting how trust builds and when it stabilizes, as well as allowing for indirectly reading a user's trust in real time based on system reliance.

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  1. User Trust Dynamics: An Investigation Driven by Differences in System Performance

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    cover image ACM Conferences
    IUI '17: Proceedings of the 22nd International Conference on Intelligent User Interfaces
    March 2017
    654 pages
    ISBN:9781450343480
    DOI:10.1145/3025171
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 07 March 2017

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    Author Tags

    1. acquisition and extinction
    2. reliance
    3. system performance
    4. temporal examination
    5. trust dynamics

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    • (2025)ContractMind: Trust-calibration interaction design for AI contract review toolsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103411196(103411)Online publication date: Feb-2025
    • (2024)Michael is better than Mehmet: exploring the perils of algorithmic biases and selective adherence to advice from automated decision support systems in hiringFrontiers in Psychology10.3389/fpsyg.2024.141650415Online publication date: 10-Sep-2024
    • (2024)In human–machine trust, humans rely on a simple averaging strategyCognitive Research: Principles and Implications10.1186/s41235-024-00583-59:1Online publication date: 2-Sep-2024
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    • (2024)The Trust Recovery Journey. The Effect of Timing of Errors on the Willingness to Follow AI Advice.Proceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645167(609-622)Online publication date: 18-Mar-2024
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