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August 26, 2025Interdisciplinary Humanities and Communication StudiesOpen Access

Liability Challenges in AI-Driven Autonomous Vehicles

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Authors

ZWZihe Wang

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Overview

This analysis demonstrates that a strict liability framework enhances public trust and ensures compensation for accidents involving autonomous vehicles.

Key Points

  • A strict liability regime enhances public trust and compensates victims effectively in autonomous vehicle accidents.
  • The key argument centers on how liability should be assigned when AI systems, not human drivers, are involved, promoting fairness and pragmatism.
  • Observational analysis addresses the complexities inherent in accidents involving AI, which stem from software and environmental interactions.
  • This framework supports sustainable integration of AI into transportation while countering claims about potential hindrances to innovation.

Cite This Study

Zihe Wang (2025) studied this question.

synapsesocial.com/papers/68af61fdad7bf08b1eae2854https://doi.org/10.61173/4g7f3t35
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Legal Challenges in Attributing Responsibility for Autonomous Driving Accidents2025 · 2 citations
  2. 2The basis of civil liability for damages to self-driving vehicles under traditional liability rules2024
  3. 3Criminal Liability Subjects in Autonomous Vehicle Accidents and Research on the Duty of Care2025
  4. 4AI Liability and Accountability: A Review of Emerging Legal Frameworks2025
  5. 5AI-Driven Autonomous Vehicles: Safety, Ethics, and Regulatory Challenges2024 · 1 citations