自动驾驶技术有潜力减少每年因人为失误造成的大量道路交通事故,，但它也带来了新类型的风险，需要从技术,、道德和法规方面进行评估。根据美国国家公路交通安全管理局 (NHTSA), 的公开碰撞数据、加州机动车辆管理局 (DMV), 的脱离报告、麻省理工学院道德机器数据集, 以及五个管辖区, 的比较监管分析，我们发现技术故障模式的主要类型是感知和分类错误。这些在报告的事故中占比较大,，可以得出结论，自动驾驶汽车决策存在不同的伦理框架,，不同领域的法规不一致增加了广泛应用的不确定性。一般来说,技术,道德问题和监管问题密切相关，需要一起解决。因此,本文建议采用一种更具适应性和合作性的治理方法，将工程标准,伦理讨论,与机构监督相结合。
Autonomous driving technology has the potential to reduce the large number of road traffic accidents caused by human error each year, but it also brings new types of risks that need to be evaluated from the aspects of technology, ethics and regulations. Based on public crash data from the National Highway Traffic Safety Administration (NHTSA), disengagement reports from the California Department of Motor Vehicles (DMV), the MIT Moral Machines dataset, and a comparative regulatory analysis of five jurisdictions, we have found that the main types of technical failure modes are perception and classification errors. These account for a relatively large proportion of the reported accidents, and it can be concluded that there are different ethical frameworks for autonomous vehicle decision-making, and inconsistent regulations in different areas increase the uncertainty of widespread application. Generally speaking, the problems of technology, ethics and regulation are closely related and need to be solved together. Therefore, this paper recommends a more adaptive and cooperative governance approach that combines engineering standards, ethical discussion, and institutional supervision.
科目:人工智能(cs.AI)
Subjects: Artificial Intelligence (cs.AI)