Building And Measuring Trust In Human-Machine Systems

Abstract

In human-machine systems (HMS), trust placed by humans on machines is a complex concept and attracts increasingly research efforts. Herein, we reviewed recent studies on building and measuring trust in HMS. The review was based on one comprehensive model of trust – IMPACTS, which has 7 features of intention, measurability, performance, adaptivity, communication, transparency, and security. The review found that, in the past 5 years, HMS fulfill the features of intention, measurability, communication, and transparency. Most of the HMS consider the feature of performance. However, all of the HMS address rarely the feature of adaptivity and neglect the feature of security due to using stand-alone simulations. These findings indicate that future work considering the features of adaptivity and/or security is imperative to foster human trust in HMS.