Impact of Explanations on Transparency in HRI: A Study Using the HRIVST Metric

This paper presents an exploration of the role of explanations provided by robots in enhancing transparency during human-robot interaction (HRI). We conducted a study with 85 participants to investigate the impact of different types and timings of explanations on transparency. In particular, we tested different conditions: (1) no explanations, (2) short explanations, (3) detailed explanations, (4) short explanations for unexpected robot actions, and (5) detailed explanations for unexpected robot actions. We used the Human-Robot Interaction Video Sequencing Task (HRIVST) metric to evaluate legibility and predictability. The preliminary results suggest that providing a short explanation is sufficient to improve transparency in HRI. The HRIVST score for short explanations is higher and very close to the score for detailed explanations of unexpected robot actions. This work contributes to the field by highlighting the importance of tailored explanations to enhance the mutual understanding between humans and robots.