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Enhancing component-specific trust with consumer automated systems through humanness design
Jeremy Lopez1, Heather Watkins1, Richard Pak1
1Department of Psychology, Clemson University, Clemson, SC, USA.
Ergonomics
|May 18, 2022
Summary
Humanness design methods can enhance trust in multi-component consumer automation systems. Increasing the number of voice assistants improved component-specific trust when one component became unreliable.
Area of Science:
- Human-computer interaction
- Consumer automation systems
- Trust in automation
Background:
- Consumer automation systems often comprise multiple interacting components.
- Understanding how users develop trust in these complex systems is crucial for effective design.
- Humanness design methods offer potential for influencing user trust.
Purpose of the Study:
- To investigate the efficacy of humanness design methods in promoting component-specific trust (CST) in multi-component automation.
- To examine how the number of simulated voice assistants affects trust and behavior in a smart home context.
- To assess the impact of component unreliability on user trust and system interaction.
Main Methods:
- 82 participants interacted with a simulated smart home system with either one or four voice assistants.
- System components were reliable initially, then one became unreliable (60% reliability).
- Subjective (trust, self-confidence) and behavioral (use, manual override) measures were collected.
Main Results:
- In the single-assistant condition, component unreliability affected trust in all components.
- In the four-assistant condition, trust decreased only for the unreliable component.
- System use decreased across conditions when a component became unreliable, but agent number did not influence this.
Conclusions:
- Humanness design can effectively enhance component-specific trust in consumer automation.
- The number of agents (voice assistants) influences how trust is affected by component unreliability.
- Findings suggest tailored humanness design approaches are beneficial for complex automated systems.
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