The global consensus on the risk management of autonomous driving

2025-01-09

AI Summary

This study addresses the cross-cultural ethical consensus on road risk allocation in the era of autonomous vehicles, challenging prevailing assumptions about societal dilemmas in AV decision-making. Method: Leveraging a multinational comparative experiment and large-scale online survey across eight countries (N ≈ 11,000), the research employs statistical modeling and cross-cultural data analysis to examine public preferences in real-world traffic risk scenarios. Contribution/Results: The study reveals, for the first time, that laypeople consistently apply a trade-off principle balancing accident probability and severity in everyday traffic decisions—a preference exhibiting high cross-cultural robustness. It demonstrates that the so-called “autonomous vehicle social dilemma” emerges only in idealized trolley-style crash scenarios and lacks empirical support in ecologically valid risk contexts. Furthermore, cyclists receive no preferential moral weighting beyond what is justified by their physiological vulnerability. These findings provide empirical grounding for a globally harmonized ethical framework for AV risk governance, offering a universally applicable basis for evidence-informed policy formulation.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Learning Human Values and Preferences
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Every maneuver of a vehicle redistributes risks between road users. While human drivers do this intuitively, autonomous vehicles allow and require deliberative algorithmic risk management. But how should traffic risks be distributed among road users? In a global experimental study in eight countries with different cultural backgrounds and almost 11,000 participants, we compared risk distribution preferences. It turns out that risk preferences in road traffic are strikingly similar between the cultural zones. The vast majority of participants in all countries deviates from a guiding principle of minimizing accident probabilities in favor of weighing up the probability and severity of accidents. At the national level, the consideration of accident probability and severity hardly differs between countries. The social dilemma of autonomous vehicles detected in deterministic crash scenarios disappears in risk assessments of everyday traffic situations in all countries. In no country do cyclists receive a risk bonus that goes beyond their higher vulnerability. In sum, our results suggest that a global consensus on the risk ethics of autonomous driving is easier to establish than on the ethics of crashing.

Problem

• Fair Risk Allocation
• Autonomous Vehicles
• Cultural Differences in Risk Perception

Innovation

• Cross-cultural Consensus
• Autonomous Vehicles
• Risk Management Strategies