Conducting Polyphonic Human-Robot Communication: Mastering Crescendos and Diminuendos in Transparency

Abstract

Intelligent Agent-based transparency is an important tool for improving trust and reliance calibration in human-agent teaming. Further, flexibility in amount and type of transparency information provided to human collaborators may allow for the accommodation of known biases (e.g., misuse and disuse). To understand the utility of transparency manipulation, it is important to consider the context of the manipulation. This report considers two contextual factors that might influence the impact of transparency: hysteresis and face threat. We describe the nature of the influence of these factors, and provide a short demonstration of their influence. Outcomes show that order of transparency and face threat affect the impact of transparency information on performance, reliance, and trust. This demonstration makes the case that an adaptive transparency paradigm should consider other aspects of human-agent interaction for successful application.