People Negotiate Better with Emotional Human-Like Virtual Agents Than Android Robots

Motoaki Sato, Takahisa Uchida, Yuichiro Yoshikawa, Celso M. de Melo, Jonathan Gratch, Kazunori Terada

Abstract: Emotional expressions serve as important communicative tools in human negotiations, and prior work has shown that artificial agents can use synthetic expressions to enhance negotiation outcomes and to train negotiation skills. These prior findings have focused on virtual agents and little is known about the effect of expressions when negotiating with physical robots. Therefore, in this study, we compared how participants negotiated with emotionally expressive virtual agents and android robots. Participants $(\mathrm{n}={82})$, as a proposer, played a nonverbal version of a four-issue ultimatum bargaining game with a counterpart who was either a virtual agent or an android robot. Before negotiating, participants observed their counterpart's emotional reactions to potential deals. The results showed that participants were better able to estimate the preferences of virtual counterparts compared with robotic counterpart, and thereby achieve better win-win solutions. We find this effect was mediated by uncanniness: participants found the emotional robot to be uncanny, and this undermined their ability to extract information from the robot's expressions. We discuss theoretical mplications for our understanding of human-robot negotiation and practical implications for the design of effective robot negotiators.

External IDs:dblp:conf/acii/SatoUYMGT24