Catastrophic Liability: Managing Systemic Risks in Frontier AI Development
arXiv:2505.00616
Abstract
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current practices at many AI labs developing these systems lack sufficient transparency around safety measures, testing procedures, and governance structures. This opacity makes it challenging to verify safety claims or establish appropriate liability when harm occurs. Drawing on liability frameworks from nuclear energy, aviation software, cybersecurity, and healthcare, we propose a comprehensive approach to safety documentation and accountability in frontier AI development.
10 pages, 1 figure, 1 table, in review for AIES 2025, presented at TAIS 2025