不仅奇怪,而且"不可思议"? 对人机交互研究中的多样性进行系统审查
Katie Seaborn1, Giulia Barbareschi2, Shruti Chandra3
1Tokyo Institute of Technology, Tokyo, Japan.
International journal of social robotics
|June 26, 2023
概括
人机交互 (HRI) 研究主要采用来自西方,受过教育,工业化,富裕和民主 (WEIRD) 人口的样本. 这项研究揭示了不同参与者人口统计学中的显著代表性不足,影响了HRI知识.
科学领域:
- 人与机器人的交互 (HRI)
- 人与计算机的交互 (HCI)
- 社会科学 社会科学 社会科学
背景情况:
- 有关科学研究参与者的多样性存在担忧,特别是WEIRD (西方,受过教育,工业,富裕,民主) 样本的流行.
- 之前的工作在HCI研究中发现了WEIRD采样偏差.
- 在HRI研究中采样偏差的程度和性质仍未得到充分研究.
研究的目的:
- 从ACM/IEEE人机交互国际会议 (2006-2022) 系统审查HRI研究中的参与者抽样.
- 为了确定HRI研究是否表现出WEIRD采样偏差.
- 调查参与者在HRI中的代表性不足和边缘化的其他潜在因素.
主要方法:
- 进行了对749篇论文 (827篇研究) 的系统文献审查,这些论文来自ACM/IEEE人机交互国际会议 (2006-2022年).
- 分析了在审查的研究中报告的参与者人口统计数据.
- 扩展了超越WEIRD标准的分析,包括多样性的交叉因素.
主要成果:
- 研究结果证实,HRI研究主要从WEIRD群体中抽取参与者的样本.
- 证据表明,有关性别/性别,种族/种族,年龄,性取向,残疾,身体类型,意识形态和领域专业知识的数据是有限的,模糊的或错误的.
- 在多个多样性维度的报告和代表性方面发现了显著的差距.
结论:
- 类似于其他领域的HRI研究,也受到WEIRD采样偏差的影响.
- 不充分的参与者多样性和报告实践带来了方法论和道德方面的挑战.
- 解决这些代表性问题对于推动HRI知识的科学有效性和包容性至关重要.
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