Abstract
In human-robot interaction, addressing disparities in action perception is vital for fostering effective collaboration. Our study delves into the integration of explanatory mechanisms during robotic actions, focusing on aligning robot perspectives with the human’s knowledge and beliefs. A comprehensive study involving 143 participants showed that providing explanations significantly enhances transparency compared to scenarios where no explanations are offered. However, intriguingly, lower transparency ratings were observed when these explanations considered participants’ existing knowledge. This observation underscores the nuanced interplay between explanation mechanisms and human perception of transparency in the context of human-robot interaction. These preliminary findings contribute to emphasize the crucial role of explanations in enhancing transparency and highlight the need for further investigation to understand the multifaceted dynamics at play.
This work has been supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955778 (G. Angelopoulos), by the Italian Ministry for Universities and Research (MUR) under the grant FAIR (MUR: PE0000013) (S. Rossi), and Italian PON R &I 2014-2020 - REACT-EU (CUP E65F21002920003) (A. Rossi).
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Angelopoulos, G., Imparato, P., Rossi, A., Rossi, S. (2024). Using Theory of Mind in Explanations for Fostering Transparency in Human-Robot Interaction. In: Ali, A.A., et al. Social Robotics. ICSR 2023. Lecture Notes in Computer Science(), vol 14454. Springer, Singapore. https://doi.org/10.1007/978-981-99-8718-4_34
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