Ethics and Information Technology ( IF 3.633 ) Pub Date : 2021-09-02 , DOI: 10.1007/s10676-021-09613-y Peng Liu 1 , Manqing Du 2 , Tingting Li 2
A human driver and an automated driving system (ADS) might share control of automated vehicles (AVs) in the near future. This raises many concerns associated with the assignment of responsibility for negative outcomes caused by them; one is that the human driver might be required to bear the brunt of moral and legal responsibilities. The psychological consequences of responsibility misattribution have not yet been examined. We designed a hypothetical crash similar to Uber’s 2018 fatal crash (which was jointly caused by its distracted driver and the malfunctioning ADS). We incorporated five legal responsibility attributions (the human driver should bear full, primary, half, secondary, and no liability, that is, the AV manufacturer should bear no, secondary, half, primary, and full liability). Participants (N = 1524) chose their preferred liability attribution and then were randomly assigned into one of the five actual liability attribution conditions. They then responded to a series of questions concerning liability assignment (fairness and reasonableness), the crash (e.g., acceptability), and AVs (e.g., intention to buy and trust). Slightly more than 50% of participants thought that the human driver should bear full or primary liability. Legal responsibility misattribution (operationalized as the difference between actual and preferred liability attributions) negatively influenced these mentioned responses, regardless of overly attributing human or manufacturer liability. Overly attributing human liability (vs. manufacturer liability) had more negative influences. Improper liability attribution might hinder the adoption of AVs. Public opinion should not be ignored in developing a legal framework for AVs.
中文翻译:
与自动驾驶汽车相关的法律责任错误归因的心理后果
在不久的将来,人类驾驶员和自动驾驶系统 (ADS) 可能会共享自动驾驶汽车 (AV) 的控制权。这引起了许多与对它们造成的负面结果的责任分配相关的担忧;一是人类司机可能需要首当其冲地承担道德和法律责任。责任错误归因的心理后果尚未得到研究。我们设计了一个类似于 Uber 2018 年致命车祸的假设车祸(这是由司机分心和 ADS 故障共同引起的)。我们纳入了五种法律责任归属(人类司机应承担全部、主要、一半、次要和不承担责任,即AV制造商应承担不承担、次要、一半、主要和全部责任)。参与者 ( N = 1524) 选择了他们偏好的责任归属,然后被随机分配到五个实际责任归属条件之一。然后他们回答了一系列关于责任分配(公平和合理)、崩溃(例如,可接受性)和 AV(例如,购买意向和信任)的问题。略多于 50% 的参与者认为人类司机应该承担全部或主要责任。法律责任错误归因(作为实际责任归因和首选责任归因之间的差异进行操作)对上述反应产生了负面影响,而不管过度归因于人为或制造商责任。过度归因于人为责任(相对于制造商责任)会产生更多负面影响。不正确的责任归属可能会阻碍自动驾驶汽车的采用。