当前位置: X-MOL 学术Int. J. Soc. Robotics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
The Mind in the Machine: Mind Perception Modulates Gaze Aversion During Child–Robot Interaction
International Journal of Social Robotics ( IF 3.8 ) Pub Date : 2020-05-17 , DOI: 10.1007/s12369-020-00656-7
Lorenzo Desideri , Paola Bonifacci , Giulia Croati , Angelica Dalena , Maria Gesualdo , Gianfelice Molinario , Arianna Gherardini , Lisa Cesario , Cristina Ottaviani

This study examined whether interacting with a humanoid robot influences children’s gaze aversion, an effortless strategy that people commonly use to facilitate thinking when asked challenging questions. Following the intentional stance model, we hypothesized that interacting with agents perceived as having a mind would modulate the social relevance assigned by the children to their interlocutor. Accordingly, we expected to observe an increase in children’s gaze aversion rates when questioned by an interaction partner believed to have a mind, compared to interaction conditions in which the questioner was believed to be a machine. To test this hypothesis, we involved 94 children in two experiments. In Experiment 1, the children interacted either with a humanoid robot (Human–Robot; n = 22) or with a human (Human–Human; n = 22) questioner. In Experiment 2, all the children interacted with a humanoid robot: one group was told the robot was controlled by a human (Avatar; n = 25), while the other group was told the robot was controlled by a computer algorithm (Machine; n = 25). Our results show that: (1) adopting an intentional stance (Human–Human; Avatar) increases gaze aversion rates; (2) gaze aversion increases and (3) response accuracy decreases as a function of question difficulty; (4) accuracy does not differ between interaction conditions. Based on these findings, we propose that gaze aversion rates might be considered an objective behavioural indicator of mind perception. Implications for robot-mediated education are also discussed.



中文翻译:

机器中的思维:思维感知在儿童与机器人交互过程中调节凝视厌恶

这项研究检查了与人形机器人的互动是否会影响儿童的注视规避,这是人们通常在询问具有挑战性的问题时会用来帮助思考的一种轻松策略。遵循有意姿态模型,我们假设与被认为有思想的特工进行互动会调节孩子分配给对话者的社会相关性。因此,与认为发问者是机器的交互条件相比,我们希望观察到在被认为有思想的交互伙伴进行询问时儿童的注视厌恶率会增加。为了验证这一假设,我们让94名儿童参与了两个实验。在实验1中,孩子们与人形机器人互动(Human–Robot; n = 22)或与人类(Human–Human; n  = 22)发问者一起使用。在实验2中,所有孩子都与人形机器人互动:一组被告知该机器人是由人控制的(头像; n  = 25),而另一组被告知该机器人是由计算机算法控制的(机器; n  = 25)。我们的结果表明:(1)采取故意的立场(人与人;阿凡达)会提高凝视厌恶率;(2)注视厌恶感增加,(3)回答准确性随问题难度而变;(4)交互条件之间的准确性没有差异。基于这些发现,我们建议凝视厌恶率可以被认为是心理感知的客观行为指标。还讨论了对机器人中介教育的影响。

更新日期:2020-05-17
down
wechat
bug