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Helping Not Hurting: Applying the Stereotype Content Model and BIAS Map to Social Robotics

机译:帮忙:将刻板印象内容模型和BIAS映射应用于社交机器人

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This paper examines relationships between perceptions of warmth and competence, emotional responses, and behavioral tendencies in the context of social robots. Participants answered questions about these three aspects of impression formation after viewing an image of one of 342 social robots in the Stanford Social Robots Database. Results suggest that people have similar emotional and behavioral reactions to robots as they have to humans; impressions of the robots' warmth and competence predicted specific emotional responses (admiration, envy, contempt, pity) and those emotional responses predicted distinct behavioral tendencies (active facilitation, active harm, passive facilitation, passive harm). However, the predicted relationships between impressions and harmful behavioral tendencies were absent. This novel asymmetry for perceptions and intentions towards robots is deliberated in the context of the computers as social actors framework and opportunities for further research are discussed.
机译:本文研究了社交机器人背景下对温暖和能力的感知,情绪反应和行为倾向之间的关系。在查看斯坦福社交机器人数据库中342个社交机器人之一的图像后,参与者回答了关于印象形成的这三个方面的问题。结果表明,人们对机器人的情感和行为反应与对人类的反应相似。机器人对温暖和能力的印象预示了特定的情绪反应(钦佩,嫉妒,鄙视,可怜),而这些情绪反应预示了不同的行为倾向(主动促进,主动伤害,被动促进,被动伤害)。但是,没有印象和有害的行为倾向之间的预测关系。随着社会参与者的框架和进一步研究的机会被讨论,这种在机器人感知和意图方面的新颖的不对称性在计算机的背景下得到了考虑。

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