Opening the moral machine’s cover: How algorithmic aversion shapes autonomous vehicle adoption

IF 6.3 1区 工程技术 Q1 ECONOMICS Transportation Research Part A-Policy and Practice Pub Date : 2024-08-02 DOI:10.1016/j.tra.2024.104193
Danitza Gordillo Chávez , Julien Cloarec , Lars Meyer-Waarden
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Abstract

Autonomous driving technology has made its way into the market at various levels, yet fully autonomous vehicles remain unavailable. The psychological barriers that must be overcome before fully automated vehicles (AVs) become mainstream are numerous. In addition to technological advancements, persuading consumers to transition from the traditional human-driven model to AVs poses a significant challenge. According to the Moral Machine Experiment, Latin American countries form distinct sub-clusters and exhibit the highest preference for action in moral decision-making. To foster user acceptance of AVs in these countries, it is imperative to comprehend cognitive, affective, and ethical factors. To this end, we conducted experiments with respondents from Colombia to examine how varying levels of automation influence algorithm aversion and user acceptance. Algorithm aversion is explored from two perspectives: ethical judgment and behavior, and emergency evaluation and performance. Our findings reveal two key insights. Firstly, higher levels of automation negatively impact people’s assessment of the emergency evaluation capabilities of AVs, partially contributing to algorithm aversion. Secondly, the intention to use AVs is adversely affected by algorithm aversion, encompassing both ethical considerations and emergency performance-related aspects. Furthermore, mediation analysis demonstrates that perceived hedonism elucidates the inverse relationship between algorithm aversion and the intention to use AVs.

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打开道德机器的盖子:算法厌恶如何影响自动驾驶汽车的采用
自动驾驶技术已在不同层面进入市场,但完全自动驾驶汽车仍未问世。在全自动驾驶汽车(AV)成为主流之前,必须克服的心理障碍有很多。除了技术进步之外,说服消费者从传统的人类驾驶模式过渡到自动驾驶汽车也是一项重大挑战。根据 "道德机器实验"(Moral Machine Experiment),拉美国家形成了独特的亚群,在道德决策中表现出最高的行动偏好。为了促进这些国家的用户接受自动驾驶汽车,当务之急是理解认知、情感和道德因素。为此,我们对哥伦比亚的受访者进行了实验,研究不同程度的自动化如何影响算法厌恶和用户接受度。我们从两个角度探讨了算法厌恶问题:道德判断和行为,以及应急评估和表现。我们的研究结果揭示了两个关键问题。首先,较高的自动化水平会对人们对自动驾驶汽车应急评估能力的评估产生负面影响,从而部分导致算法厌恶。其次,使用自动驾驶汽车的意愿受到算法厌恶的负面影响,包括道德考虑和应急性能相关方面。此外,中介分析表明,感知享乐主义阐明了算法厌恶与使用 AVs 的意愿之间的反向关系。
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来源期刊
CiteScore
13.20
自引率
7.80%
发文量
257
审稿时长
9.8 months
期刊介绍: Transportation Research: Part A contains papers of general interest in all passenger and freight transportation modes: policy analysis, formulation and evaluation; planning; interaction with the political, socioeconomic and physical environment; design, management and evaluation of transportation systems. Topics are approached from any discipline or perspective: economics, engineering, sociology, psychology, etc. Case studies, survey and expository papers are included, as are articles which contribute to unification of the field, or to an understanding of the comparative aspects of different systems. Papers which assess the scope for technological innovation within a social or political framework are also published. The journal is international, and places equal emphasis on the problems of industrialized and non-industrialized regions. Part A''s aims and scope are complementary to Transportation Research Part B: Methodological, Part C: Emerging Technologies and Part D: Transport and Environment. Part E: Logistics and Transportation Review. Part F: Traffic Psychology and Behaviour. The complete set forms the most cohesive and comprehensive reference of current research in transportation science.
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