Robot Authority in Human-Machine Teams: Effects of Human-Like Appearance on Compliance

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Abstract

Current technology allows for the deployment of security patrol and police robots. It is expected that in the near future robots and similar technologies will exhibit some degree of authority over people within human-machine teams. Studies in classical psychology investigating compliance have shown that people tend to comply with requests from others who display or are assumed to have authority. In this study, we investigated the effect of a robot’s human-like appearance on compliance with a request. We compared two different robots to a human control condition. The robots assumed the role of a coach in learning a difficult task. We hypothesized that participants would have higher compliance with robots high compared to robots low in human-like appearance. The coach continuously prompts the participant to continue to practice the task beyond the time the participant wishes to actually proceed. Compliance was measured by time practiced after the first prompt and the total number of images processed. Results showed that compliance with the request was the highest with a human and compliance with both robots was significantly lower. However, we showed that robots can be used as persuasive coaches that can help a human teammate to persist in training task. There were no differences between the High and Low Human-Like robot for compliance time, however the Low Human-Like robot has people practise on more images than the High Human-Like robot. The implication of this study is that robots are currently inferior to humans when it comes to compliance in a human-machine team. Future robots need to be carefully designed in an authoritative way if maximizing compliance to their requests is the primary goal.

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APA

Haring, K. S., Mosley, A., Pruznick, S., Fleming, J., Satterfield, K., de Visser, E. J., … Funke, G. (2019). Robot Authority in Human-Machine Teams: Effects of Human-Like Appearance on Compliance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11575 LNCS, pp. 63–78). Springer Verlag. https://doi.org/10.1007/978-3-030-21565-1_5

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