机器人被认为是优秀的决策者吗?一项调查足球比赛中机器人和人类边裁的信任和偏好的研究

Kaustav Das, Yixiao Wang, K. Green
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引用次数: 0

摘要

机器人越来越多地成为制造业、金融、医学和其他领域的决策者,但由于期望与能力之间的差距、可解释人工智能的挑战、用户对技术的接触程度等原因,这项技术可能得不到足够的信任。为了调查用户和机器人之间的信任问题,作者在这项研究中采用了机器人在足球(或在美国被称为“足球”)比赛中作为裁判做出决策的案例。更具体地说,我们提出了一项关于人类和三个机器人边裁(Malle等人的研究)的外观如何影响球迷对他们的信任和偏好的研究。我们对104名参与者进行的在线研究发现,对人形和真人裁判员的“信任”和“偏好”之间存在正相关关系,但对“人工智能”和“机械”裁判员则没有。尽管不同类型的边裁之间没有明显的信任差异,但参与者确实更喜欢真人边裁而不是机械和人形边裁。我们的定性研究通过探究人们偏好的可能原因进一步验证了这些定量研究结果:当边裁的外观不像人类时,人们更少关注信任问题,而是更多地关注他们偏爱边裁的其他原因,如效率、稳定性和最小机器人设计。这些发现为设计可靠的决策机器人提供了重要的见解,这些机器人越来越多地融入我们日常生活的各个方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Are robots perceived as good decision makers? A study investigating trust and preference of robotic and human linesman-referees in football
Abstract Increasingly, robots are decision makers in manufacturing, finance, medicine, and other areas, but the technology may not be trusted enough for reasons such as gaps between expectation and competency, challenges in explainable AI, users’ exposure level to the technology, etc. To investigate the trust issues between users and robots, the authors employed in this study, the case of robots making decisions in football (or “soccer” as it is known in the US) games as referees. More specifically, we presented a study on how the appearance of a human and three robotic linesmen (as presented in a study by Malle et al.) impacts fans’ trust and preference for them. Our online study with 104 participants finds a positive correlation between “Trust” and “Preference” for humanoid and human linesmen, but not for “AI” and “mechanical” linesmen. Although no significant trust differences were observed for different types of linesmen, participants do prefer human linesman to mechanical and humanoid linesmen. Our qualitative study further validated these quantitative findings by probing possible reasons for people’s preference: when the appearance of a linesman is not humanlike, people focus less on the trust issues but more on other reasons for their linesman preference such as efficiency, stability, and minimal robot design. These findings provide important insights for the design of trustworthy decision-making robots which are increasingly integrated to more and more aspects of our everyday lives.
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