The individual physical appearances of robots are considered significant, similar to the way that those of humans are. We investigated whether users prefer robots with male or female physical appearances for use in daily communication situations and whether egalitarian gender role attitudes are related to this preference. One thousand adult men and women aged 20–60 participated in the questionnaire survey. The results of our study showed that in most situations and for most subjects, “males” was not selected and “females” or (...) “neither” was selected. Moreover, the number of respondents who chose “either” was higher than that who chose “female.” Furthermore, we examined the relationship between gender and gender preference and confirmed that the effect of gender on the gender preference for a robot weakened when the human factor was eliminated. In addition, in some situations for android-type robots and in all situations for machine-type robots, equality orientation in gender role attitudes was shown to be higher for people who were not specific about their gender preferences. It is concluded that there is no need to introduce a robot that specifies its gender. Robots with a gender-neutral appearance might be more appropriate for applications requiring complex human–robot interaction and help avoid reproducing a gender bias. (shrink)

The anticipated social capabilities of robots may allow them to serve in authority roles as part of human-machine teams. To date, it is unclear if, and to what extent, human team members will comply with requests from their robotic teammates, and how such compliance compares to requests from human teammates. This research examined how the human-likeness and physical embodiment of a robot affect compliance to a robot's request to perseverate utilizing a novel task paradigm. Across a set of two studies, (...) participants performed a visual search task while receiving ambiguous performance feedback. Compliance was evaluated when the participant requested to stop the task and the coach urged the participant to keep practicing multiple times. In the first study, the coach was either physically co-located with the participant or located remotely via a live-video. Coach type varied in human-likeness and included either a real human, a Nao robot, or a modified Roomba robot. The second study expanded on the first by including a Baxter robot as a coach and replicated the findings in a different sample population with a strict chain of command culture. Results from both studies showed that participants comply with the requests of a robot for up to 11 min. Compliance is less than to a human and embodiment and human-likeness on had weak effects on compliance. (shrink)

In our daily lives, we are continually involved in decision-making situations, many of which take place in the context of social interaction. Despite the ubiquity of such situations, there remains a gap in our understanding of how decision-making unfolds in social contexts, and how communicative signals, such as social cues and feedback, impact the choices we make. Interestingly, there is a new social context to which humans are recently increasingly more frequently exposed—social interaction with not only other humans but also (...) artificial agents, such as robots or avatars. Given these new technological developments, it is of great interest to address the question of whether—and in what way—social signals exhibited by non-human agents influence decision-making. The present study aimed to examine whether robot non-verbal communicative behavior has an effect on human decision-making. To this end, we implemented a two-alternative-choice task where participants were to guess which of two presented cups was covering a ball. This game was an adaptation of a “Shell Game.” A robot avatar acted as a game partner producing social cues and feedback. We manipulated robot's cues (pointing toward one of the cups) before the participant's decision and the robot's feedback (“thumb up” or no feedback) after the decision. We found that participants were slower (compared to other conditions) when cues were mostly invalid and the robot reacted positively to wins. We argue that this was due to the incongruence of the signals (cue vs. feedback), and thus violation of expectations. In sum, our findings show that incongruence in pre- and post-decision social signals from a robot significantly influences task performance, highlighting the importance of understanding expectations toward social robots for effective human–robot interactions. (shrink)