Zonca Joshua, Folsø Anna, Sciutti Alessandra
Cognitive Architecture for Collaborative Technologies (CONTACT) Unit, Italian Institute of Technology, Via Enrico Melen, 83, 16152 Genoa, GE, Italy.
Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, Italy.
iScience. 2021 Nov 11;24(12):103424. doi: 10.1016/j.isci.2021.103424. eCollection 2021 Dec 17.
Humans 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.
人类不断受到他人行为和观点的影响。重要的是,人类之间的社会影响是由互惠性塑造的:我们更倾向于听从那些考虑过我们观点的人的建议。在当前的研究中,我们探究在与社交类人机器人交互时,互惠性社会影响是否会出现。在一项联合任务中,人类参与者和类人机器人进行感知估计,然后在观察到对方的判断后可以公开修改自己的估计。结果表明,赋予机器人表达和调节其自身对人类判断的易感性水平的能力是一把双刃剑。一方面,当机器人听从他们的建议时,参与者对机器人的能力失去信心;另一方面,参与者不愿意向易受影响的机器人透露自己缺乏信心,这表明支持人机协作的社会影响互惠机制出现了。