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  • 标题:The role of reciprocity in human-robot social influence
  • 本地全文:下载
  • 作者:Joshua Zonca ; Anna Folsø ; Alessandra Sciutti
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2021
  • 卷号:24
  • 期号:12
  • 页码:1-22
  • DOI:10.1016/j.isci.2021.103424
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryHumans are constantly influenced by others’ behavior and opinions. Of importance, social influence among humans is shaped by reciprocity: we follow more the advice of someone who has been taking into consideration our opinions. In the current work, we investigate whether reciprocal social influence can emerge while interacting with a social humanoid robot. In a joint task, a human participant and a humanoid robot made perceptual estimates and then could overtly modify them after observing the partner’s judgment. Results show that endowing the robot with the ability to express and modulate its own level of susceptibility to the human’s judgments represented a double-edged sword. On the one hand, participants lost confidence in the robot’s competence when the robot was following their advice; on the other hand, participants were unwilling to disclose their lack of confidence to the susceptible robot, suggesting the emergence of reciprocal mechanisms of social influence supporting human-robot collaboration.Graphical abstractDisplay OmittedHighlights•If a social robot is susceptible to our advice, we lose confidence in it•However, robot’s susceptibility does not deteriorate social influence•These effects do not appear during interaction with a computer•Susceptible robots can promote reciprocity but also hinder social learning
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