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When Stereotypes Meet Robots: The Effect of Gender Stereotypes on People’s Acceptance of a Security Robot

机译:当刻板印象符合机器人时:性别刻板印象对人们接受安全机器人的影响

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A recent development of social robotics suggests the integration of human characteristics social robots, which allows a more natural interaction between users and these social robots targeting better task performance and greater user acceptance to such social robots. It is interesting to note that the recent successful integration of human characteristics has brought an overarching research paradigm, known as Computers Are Social Actors (CASA) theory which suggests that people react and respond to computers and robots, often similar to the way they treat another social entities. Based on the research paradigm of CASA theory, this study further examined the impact of gender-related role stereotypes on the assessment of a social robot in a particular occupation. Though previous research in social science found that stereotyping makes a significant influence on personal decisions, involving career promotion, development, and supervision, as well as personal competence evaluations, limited insights has been found in HRI research. A between-subject experiment was conducted with 40 participants (gender balanced) at a public university in Singapore to investigate the effect of gender-related role stereotypes on user acceptance of a social robot as a security guard. Largely within our expectations, the results also showed that users perceived the security robot with matching gender-related role stereotypes more useful and acceptable than the mismatched security robot as a second-degree social response.
机译:最近的社会机器人的发展表明,人类特色社会机器人的整合,这允许用户与这些社会机器人之间的更自然的互动,这些社会机器人瞄准更好的任务性能以及对这些社会机器人的更大的用户接受。值得注意的是,最近的人类特征的成功整合带来了一个总体研究范式,被称为计算机是社会行动者(CASA)理论,这表明人们对计算机和机器人的反应和回应,通常类似于他们对待另一个人的反应社会实体。基于Casa理论的研究范式,本研究进一步研究了与对特定职业中社会机器人评估的性别相关角色刻板印象的影响。虽然以前的社会科学研究发现,刻板印象对个人决策产生了重大影响,涉及职业促进,发展和监督,以及个人能力评估,在HRI研究中发现了有限的见解。在新加坡的公立大学进行了一项对象实验,在新加坡的公立大学进行了40名参与者(性别平衡),以调查性别相关的角色刻板印象对作为保安人员的用户接受社会机器人的影响。在很大程度上,在我们的期望范围内,结果还表明,用户认为具有匹配性别相关的角色刻板印象的安全机器人比不匹配的安全机器人作为二级社会反应更有用和可接受。

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