Abstract
Trust is a critical factor in successful and productive human-automation interactions. Human trust in machines is sensitive to machine performance. When automation malfunctions, trust is negatively affected. The development of increasingly complex multiple-component systems, or those with several autonomous elements, introduces even more ways for a system to err. One example is in smart home control systems where different subsystems may be controlled by different autonomous routines or rules. Multiple studies suggest that one error-prone component can lower user trust in the remaining components. This has been termed a “pull down effect.” Other research suggests that increasing the amount of information presented to the user can reduce the strength of the pull down effect by promoting heterogeneity of components. Although a majority of this research has been tested in the industrial domain, there exist certain types of information that are best suited for consumer automation (e.g., granting the automation a name and a voice). Providing this kind of information to the user may diminish the strength of the pull down effect. Thus, the current study will investigate the effectiveness of trust-preserving heterogeneity strategies in consumer multiple-component systems.
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