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Today many systems are highly automated. The human operator's role in these systems is to supervise the automation and intervene to take manual control when necessary. The operator's choice of automatic or manual control has important consequences for system performance, and therefore it is important to understand and optimize this decision process. One important determinant of operators' choice of manual or automatic control may be their degree of trust in the automation. However, there have been no experimental tests of this hypothesis until recently, nor is there a model of human trust in machines to form a theoretical foundation for empirical studies. In this paper a model of human trust in machines is developed, taking models of trust between people as a starting point, and extending them to the human-machine relationship. The resulting model defines human trust in machines and specifies how trust changes with experience on a system, providing a framework for experimental research on trust and human intervention in automated systems.
Bonnie M. Muir (Tue,) studied this question.
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