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Overtrusting robots: Setting a research agenda to mitigate overtrust in automation

机译:覆盖的机器人:设置研究议程以缓解自动化的过度

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There is increasing attention given to the concept of trustworthiness for artificial intelligence and robotics. However, trust is highly context-dependent, varies among cultures, and requires reflection on others’ trustworthiness, appraising whether there is enough evidence to conclude that these agents deserve to be trusted. Moreover, little research exists on what happens when too much trust is placed in robots and autonomous systems. Conceptual clarity and a shared framework for approaching overtrust are missing. In this contribution, we offer an overview of pressing topics in the context of overtrust and robots and autonomous systems. Our review mobilizes insights solicited from in-depth conversations from a multidisciplinary workshop on the subject of trust in human–robot interaction (HRI), held at a leading robotics conference in 2020. A broad range of participants brought in their expertise, allowing the formulation of a forward-looking research agenda on overtrust and automation biases in robotics and autonomous systems. Key points include the need for multidisciplinary understandings that are situated in an eco-system perspective, the consideration of adjacent concepts such as deception and anthropomorphization, a connection to ongoing legal discussions through the topic of liability, and a socially embedded understanding of overtrust in education and literacy matters. The article integrates diverse literature and provides a ground for common understanding for overtrust in the context of HRI.
机译:越来越关注人工智能和机器人可靠性的概念。然而,信任是依赖的高度上下文,文化中的各种各样地不同,并且需要对他人的可靠性反映,评价是否有足够的证据表明这些代理人值得信任。此外,在机器人和自主系统中置于太多信任时,存在很少的研究。缺少概念清晰度和接近过度的共享框架。在这一贡献中,我们提供了在过度特点和机器人和自主系统的背景下按压主题的概述。我们的审查调动了从2020年领先的机器人互动(HRI)的多学科讲课中的深入谈话中求解的见解,这是在2020年领先的机器人大会上举行的。广泛的参与者带来了他们的专业知识,允许制定机器人和自治系统中的过度特图和自动化偏差前瞻性研究议程。关键点包括在生态系统视角下位于生态系统视角的多学科谅解,审议欺骗和人为化等相邻概念,通过责任主题的持续法律讨论,以及对教育过度的社会嵌入式了解和扫盲事项。本文整合了不同的文学,并为HRI的背景下提供了对过度的共同理解的理由。

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