CYAICRDec 16, 2025

Criminal Liability in AI-Enabled Autonomous Vehicles: A Comparative Study

arXiv:2512.14330v11 citationsh-index: 1SSRN
Originality Synthesis-oriented
AI Analysis

It addresses the problem of unclear liability attribution for infractions in autonomous vehicles for policymakers and legal systems, but is incremental as it synthesizes existing legal frameworks without proposing new solutions.

This study tackled the problem of criminal liability in AI-enabled autonomous vehicles by conducting a comparative legal analysis across five jurisdictions, revealing fragmented regulatory landscapes with varying approaches such as loose state laws in the US and India, and stricter regimes in the UK, Germany, and China.

AI revolutionizes transportation through autonomous vehicles (AVs) but introduces complex criminal liability issues regarding infractions. This study employs a comparative legal analysis of primary statutes, real-world liability claims, and academic literature across the US, Germany, UK, China, and India; jurisdictions selected for their technological advancement and contrasting regulatory approaches. The research examines the attribution of human error, AI moral agency, and the identification of primary offenders in AV incidents. Findings reveal fragmented regulatory landscapes: India and the US rely on loose networks of state laws, whereas the UK enacted the pioneering Automated and Electric Vehicles Act 2018. Germany enforces strict safety standards, distinguishing liability based on the vehicle's operating mode, while China similarly aims for a stringent liability regime. The study concludes that globally harmonized legal standards are essential to foster technological innovation while ensuring minimum risk and clear liability attribution.

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