The calibration of trust in an automated system: A sensemaking process

Today operators in complex task domains such as aviation, process control, medicine and the military must work closely with automation to achieve levels of performance that would be impossible to reach independently. To maximize the full benefit of this man-machine relationship operator trust must be appropriately calibrated with the trustworthiness of the system. Misalignment of trust with the automation´s capabilities and limitations may lead to error, inefficiency and possible rejection of the technology. The purpose of this paper is to propose sensemaking as a theoretical framework for describing trust calibration. This framework can serve as a guide for developers of intelligent software tools to improve trust calibration training. The authors discuss the Experiential User Guide (EUG) concept as one example of how to train trust calibration by improving operator sensemaking.