INTERNATIONAL LEGAL EXPERIENCES WITH USING AI FOR AUTOMATED QUALITY AND SAFETY CONTROL OF GOODS

Artificial intelligence promises major benefits in automating quality control and safety inspections for manufactured products. However, deploying AI also poses regulatory challenges at the nexus of products liability law, data protection, and AI governance. Through comparative analysis, this paper examines emerging legal issues including unclear liability for AI-related defects, proving causation for machine-driven harms, balancing innovation incentives and precautionary consumer protection, addressing algorithmic opacity and bias, and adapting 20th century safety rules to an AI context. Results reveal needs to modernize liability rules, enhance algorithmic transparency, strengthen international coordination on technical standards, pursue gradual experimental approaches like regulatory sandboxes, and invest in "safe-by-design" innovations that augment human inspectors. Successfully integrating automation in quality assurance requires governance balancing safety with progress. Empirical study is essential to guide policy as applications advance