机器人服装对第一印象的影响,性别,人形,和适合一个机器人的职业

K. Hindriks, Marijn Hagenaar, A. L. Huckelba
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引用次数: 2

摘要

服装通常被用来表达一个人的身份。它可以提供诸如性别、年龄、职业和地位等特征信息,也可以提供诸如可信度和友好度等更为主观的属性信息。在本文中,我们报告了探索性研究,我们通过三项研究来调查服装对胡椒机器人的影响。三套不同风格和颜色的服装与不穿衣服的机器人相互比较。一项在线调查的结果表明,服装可以左右性别感知,而不是人的长相。我们还发现,对专业知识和亲和力的第一印象可能因服装风格而异,并可能引发刻板印象的工作联想。在第二项研究中,我们采访了熟悉Pepper平台的专家,以获得对机器人服装更定性的看法。采访清楚地表明,服装的特定特征可能会引发与职业的强烈联系,而头饰等特征可能会使一套服装看起来更像制服。最后,我们进行了现场实验,比较了接待员机器人在自然环境下的两种着装条件,发现穿制服的机器人看起来更有吸引力。我们的研究结果表明,机器人服装可能会对第一印象、性别感知以及与野外用户互动的参与度产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of Robot Clothing on First Impressions, Gender, Human-Likeness, and Suitability of a Robot for Occupations
Clothing is often used as a way to communicate about one’s identity. It can provide information about characteristics such as gender, age, occupation, and status as well as more subjective attributes such as trustworthiness and friendliness. In this paper we report on exploratory research that we conducted by means of three studies to investigate the effects of clothing on a Pepper robot. Three outfits that varied in style and colour were compared with each other and the robot without clothing. Findings from an online survey suggest that gender perception but not human-likeness can be manipulated by clothing. We also found that first impressions on expertise and likeability may vary with clothing style and may induce stereotypical job associations. In a second study, we interviewed experts which were all familiar with the Pepper platform to obtain a more qualitative perspective on robot clothing. The interviews made clear that specific features of clothing may trigger strong associations with, for example, occupations, and that features such as headdress may make an outfit look more like a uniform. Finally, we conducted a field experiment comparing two clothing conditions for a receptionist robot in a natural setting and found that a robot with uniform appears to be more engaging. Our findings suggest that robot clothing may have an effect on first impressions, gender perception, and engagement in interactions with users in the wild.
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