Suppr超能文献

在困难情况下指责自动驾驶车辆。

Blaming automated vehicles in difficult situations.

作者信息

Franklin Matija, Awad Edmond, Lagnado David

机构信息

Department of Experimental Psychology, University College London, London WC1E 6BT, UK.

Department of Economics, University of Exeter Business School, Exeter EX4 4PU, UK.

出版信息

iScience. 2021 Mar 1;24(4):102252. doi: 10.1016/j.isci.2021.102252. eCollection 2021 Apr 23.

Abstract

Automated vehicles (AVs) have made huge strides toward large-scale deployment. Despite this progress, AVs continue to make mistakes, some resulting in death. Although some mistakes are avoidable, others are hard to avoid even by highly skilled drivers. As these mistakes continue to shape attitudes toward AVs, we need to understand whether people differentiate between them. We ask the following two questions. When an AV makes a mistake, does the perceived difficulty or novelty of the situation predict blame attributed to it? How does that blame attribution compare to a human driving a car? Through two studies, we find that the amount of blame people attribute to AVs and human drivers is sensitive to situation difficulty. However, while some situations could be more difficult for AVs and others for human drivers, people blamed AVs more, regardless. Our results provide novel insights in understanding psychological barriers influencing the public's view of AVs.

摘要

自动驾驶汽车(AVs)在大规模部署方面已经取得了巨大进展。尽管有这一进展,但自动驾驶汽车仍会犯错,有些错误甚至导致死亡。虽然有些错误是可以避免的,但即使是技术高超的驾驶员也难以避免其他一些错误。由于这些错误继续影响着人们对自动驾驶汽车的态度,我们需要了解人们是否会对它们进行区分。我们提出以下两个问题。当自动驾驶汽车犯错时,人们对情况的感知难度或新奇性是否能预测归咎于它的责任?这种责任归咎与人类驾驶汽车相比如何?通过两项研究,我们发现人们归咎于自动驾驶汽车和人类驾驶员的责任程度对情况难度很敏感。然而,虽然有些情况对自动驾驶汽车来说可能更困难,而另一些情况对人类驾驶员来说更困难,但无论如何,人们更多地归咎于自动驾驶汽车。我们的研究结果为理解影响公众对自动驾驶汽车看法的心理障碍提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26e5/7995526/85f15a2efcc7/fx1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验