Cross Emily S, Ramsey Richard, Liepelt Roman, Prinz Wolfgang, de C Hamilton Antonia F
Wales Institute for Cognitive Neuroscience, School of Psychology, Bangor University, Wales, The Netherlands Department of Social and Cultural Psychology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, The Netherlands
Wales Institute for Cognitive Neuroscience, School of Psychology, Bangor University, Wales, The Netherlands.
Philos Trans R Soc Lond B Biol Sci. 2016 Jan 19;371(1686):20150075. doi: 10.1098/rstb.2015.0075.
Although robots are becoming an ever-growing presence in society, we do not hold the same expectations for robots as we do for humans, nor do we treat them the same. As such, the ability to recognize cues to human animacy is fundamental for guiding social interactions. We review literature that demonstrates cortical networks associated with person perception, action observation and mentalizing are sensitive to human animacy information. In addition, we show that most prior research has explored stimulus properties of artificial agents (humanness of appearance or motion), with less investigation into knowledge cues (whether an agent is believed to have human or artificial origins). Therefore, currently little is known about the relationship between stimulus and knowledge cues to human animacy in terms of cognitive and brain mechanisms. Using fMRI, an elaborate belief manipulation, and human and robot avatars, we found that knowledge cues to human animacy modulate engagement of person perception and mentalizing networks, while stimulus cues to human animacy had less impact on social brain networks. These findings demonstrate that self-other similarities are not only grounded in physical features but are also shaped by prior knowledge. More broadly, as artificial agents fulfil increasingly social roles, a challenge for roboticists will be to manage the impact of pre-conceived beliefs while optimizing human-like design.
尽管机器人在社会中的存在日益增加,但我们对机器人的期望与对人类的期望不同,对待方式也不一样。因此,识别人类生命迹象线索的能力是引导社会互动的基础。我们回顾了相关文献,这些文献表明与人物感知、动作观察和心理化相关的皮层网络对人类生命迹象信息很敏感。此外,我们发现大多数先前的研究都探讨了人工代理的刺激属性(外观或动作的人性化程度),而对知识线索(一个代理被认为具有人类还是人工起源)的研究较少。因此,目前在认知和大脑机制方面,对于人类生命迹象的刺激线索和知识线索之间的关系知之甚少。通过功能磁共振成像、精心设计的信念操纵以及人类和机器人化身,我们发现人类生命迹象的知识线索会调节人物感知和心理化网络的参与度,而人类生命迹象的刺激线索对社会大脑网络的影响较小。这些发现表明,自我与他人的相似性不仅基于身体特征,还受到先验知识的影响。更广泛地说,随着人工代理承担越来越多的社会角色,机器人专家面临的一个挑战将是在优化类人设计的同时,管理先入为主信念的影响。