Why Is Artificial Intelligence Blamed More? Analysis of Faulting Artificial Intelligence for Self-Driving Car Accidents in Experimental Settings
Why Is Artificial Intelligence Blamed More? Analysis of Faulting Artificial Intelligence for Self-Driving Car Accidents in Experimental Settings
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DOI：
10.1080/10447318.2020.1785693
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发表时间：
2020-06-27
影响因子：
4.7
通讯作者：
Lanz, Paulina
中科院分区：
文献类型：
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作者：
Hong, Joo-Wha;Wang, Yunwen;Lanz, Paulina
这项研究进行了一项实验，根据归因理论和计算机是社会参与者 (CASA) 来测试人工智能 (AI) 和人类驾驶员之间的责备程度有何不同。它采用 2（人类 vs. AI 驾驶员）x 2（受害者幸存 vs. 受害者死亡）x 2（女性 vs. 男性驾驶员）设计。阅读给定场景后，参与者 (N = 284) 被要求为司机分配一定的责任级别。与司机是人类时相比，当司机是人工智能时，参与者更多地指责司机。此外，当结果越严重时，责备的程度就越高。然而，在指责司机时，性别偏见并不显着。这些结果表明，指责人工智能的意图来自于对差异的感知，而结果的严重性会影响指责的程度。讨论了研究结果对应用和理论的影响。
This study conducted an experiment to test how the level of blame differs between an artificial intelligence (AI) and a human driver based on attribution theory and computers are social actors (CASA). It used a 2 (human vs. AI driver) x 2 (victim survived vs. victim died) x 2 (female vs. male driver) design. After reading a given scenario, participants (N = 284) were asked to assign a level of responsibility to the driver. The participants blamed drivers more when the driver was AI compared to when the driver was a human. Also, the higher level of blame was shown when the result was more severe. However, gender bias was found not to be significant when faulting drivers. These results indicate that the intention of blaming AI comes from the perception of dissimilarity and the seriousness of outcomes influences the level of blame. Implications of findings for applications and theory are discussed.