Pflanzer Michael, Cecchini Dario, Cacace Sam, Dubljević Veljko
Center for AI in Society and Ethics, North Carolina State University, Raleigh, NC, United States.
Violence Prevention Center, University of North Carolina at Charlotte, Charlotte, NC, United States.
Front Psychol. 2025 Jun 9;16:1508763. doi: 10.3389/fpsyg.2025.1508763. eCollection 2025.
In recent years, the ethical implications of traffic decision-making, particularly in the context of autonomous vehicles (AVs), have garnered significant attention. While much of the existing research has focused on high-stakes moral dilemmas, such as those exemplified by the trolley problem, everyday traffic situations-characterized by mundane, low-stakes decisions-remain underexplored.
This study addresses this gap by empirically investigating the applicability of the Agent-Deed-Consequences (ADC) model in the moral judgment of low-stakes traffic scenarios. Using a vignette approach, we surveyed professional philosophers to examine how their moral judgments are influenced by the character of the driver (Agent), their adherence to traffic rules (Deed), and the outcomes of their actions (Consequences).
Our findings support the primary hypothesis that each component of the ADC model significantly influences moral judgment, with positive valences in agents, deeds, and consequences leading to greater moral acceptability. We additionally explored whether participants' normative ethical leanings-classified as deontological, utilitarian, or virtue ethics-influenced how they weighted ADC components. However, no moderating effects of moral preference were observed. The results also reveal interaction effects among some components, illustrating the complexity of moral reasoning in traffic situations.
The study's implications are crucial for the ethical programming of AVs, suggesting that these systems should be designed to navigate not only high-stakes dilemmas but also the nuanced moral landscape of everyday driving. Our work creates a foundation for stakeholders to integrate human moral judgments into AV decision-making algorithms. Future research should build on these findings by including a more diverse range of participants and exploring the generalizability of the ADC model across different cultural contexts.
近年来,交通决策的伦理含义,尤其是在自动驾驶汽车(AV)的背景下,已引起了广泛关注。虽然现有的许多研究都集中在高风险的道德困境上,例如电车难题所体现的那些困境,但以平凡、低风险决策为特征的日常交通情况仍未得到充分探索。
本研究通过实证调查代理 - 行为 - 后果(ADC)模型在低风险交通场景道德判断中的适用性来填补这一空白。我们采用了情景描述法,对专业哲学家进行了调查,以研究他们的道德判断如何受到驾驶员的性格(代理)、对交通规则的遵守情况(行为)以及其行为结果(后果)的影响。
我们的研究结果支持了主要假设,即ADC模型的每个组成部分都对道德判断有显著影响,代理、行为和后果中的积极因素会导致更高的道德可接受性。我们还探讨了参与者的规范性伦理倾向(分为道义论、功利主义或德性伦理学)是否会影响他们对ADC组成部分的权衡。然而,未观察到道德偏好的调节作用。结果还揭示了一些组成部分之间的交互作用,说明了交通场景中道德推理的复杂性。
该研究的意义对于自动驾驶汽车的伦理编程至关重要,表明这些系统不仅应设计用于应对高风险困境,还应应对日常驾驶中细微的道德情境。我们的工作为利益相关者将人类道德判断纳入自动驾驶汽车决策算法奠定了基础。未来的研究应基于这些发现,纳入更多样化的参与者,并探索ADC模型在不同文化背景下的普遍性。