Blaming automated vehicles in difficult situations. Franklin, M., Awad, E., & Lagnado, D. iScience, 24(4):102252, April, 2021. ![Blaming automated vehicles in difficult situations [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{franklin_blaming_2021,
title = {Blaming automated vehicles in difficult situations},
volume = {24},
issn = {2589-0042},
url = {https://www.sciencedirect.com/science/article/pii/S2589004221002200},
doi = {10.1016/j.isci.2021.102252},
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.},
language = {en},
number = {4},
urldate = {2023-03-08},
journal = {iScience},
author = {Franklin, Matija and Awad, Edmond and Lagnado, David},
month = apr,
year = {2021},
keywords = {Artificial Intelligence, Psychology, Research Methodology Social Sciences},
pages = {102252},
}
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