Abstract

With the rapid development of new technology, robots are increasingly being introduced into decision-making such that people can receive advice from them. Decision-making involves many variables, which should be investigated together. In the current study, we explored human-robot interaction in decision-making from the perspectives of confidence, trust, decision change, and reciprocity. We also investigated the effects of robot ability, task complexity, and risk on human-robot interaction in decision-making. We conducted an experiment where participants received advice from robots in a length judgment task, for which the participants had to select the longest line among eight lines. The results showed that participants had higher trust and confidence when receiving advice from high-ability robots. However, the participants had less confidence, reduced trust in the robots, a lower tendency to change their decision, and shared more losses with robots during complex tasks. They placed less trust in the robots and shared fewer benefits with them in a high-risk condition. Additionally, the participants’ self-construal was significantly correlated with trust and gender was significantly correlated with confidence, benefits shared with the robot, and decision change. These findings can aid researchers and designers in the development of service robots.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.