Factors influencing subjective opinion attribution to conversational robots.

Abstract

The usefulness of conversational robots has been demonstrated in various fields. It is suggested that expressing subjective opinions is essential for conversational robots to stimulate users' willingness to engage in conversation. However, a challenge remains in that users often find it difficult to attribute subjective opinions to robots. Therefore, this study aimed to examine the factors influencing the attribution of subjective opinions to robots. We investigated robot and human factors that may affect subjective opinion attribution to robots. Furthermore, these factors were investigated in four different cases, adopting a combination of the robots' types and control methods, considering actual scenarios of robot usage. The survey was conducted online, and the participants completed a questionnaire after receiving instructions regarding the robot. The results revealed that the perception of the robots' sensory capabilities significantly influenced the attribution of subjective opinions in all the surveyed cases. Additionally, in the case of an autonomous small robot, there is a possibility that participants' self-perception of their judgment abilities might also impact their subjective opinion attribution to the robot. The findings highlight the importance of aligning subjective opinion utterances in conversational robots with user perceptions of the robot's sensory capabilities. They also emphasized the significance of exploring how users' self-perceptions influence their perceptions of robots. These insights provide valuable guidance for designing conversational strategies and speech generation in robots that engage in the exchange of subjective opinions with humans.