Trust, Automation, and Feedback: An Integrated Approach

This chapter reviews research in which an integrative framework, based on the lens model, was developed. The framework characterizes aspects of automated systems that affect human trust in those systems and allows assessment of aspects of human trust through the application of lens modeling outcomes. Implications are drawn from an empirical study that relied on this integrative framework and are provided for the design of training systems and displays. Specifically, the chapter addresses the situation in which human judgments are not only made in concert with automation but also in part on the basis of the information provided by an automated decision aid. It is shown that the developed framework along with the companion experiment demonstrate both theoretically and empirically how outcomes from the lens model can be expanded beyond their traditional applications toward improving judgment performance in a single-judge system. In particular, meta-information based on concepts of cognitive feedback can be used in a feedforward manner to provide information about an agent's judgment policies and performance to other agents in a multiagent judgment system. This framework also has particular implications for systems composed of humans and automated judgment agents.