Legal Discipline of Data Procurement and Corporate Governance in Generative AI Development: A Comparative Analysis of U.S.-Japan Copyright Law and Responsibility Allocation for Infrastructure Providers and Users

Abstract:This research monograph provides a rigorous comparative legal and corporate governance analysis of data procurement in frontier generative artificial intelligence development. Focusing on the normative divergence between Article 30-4 of the Japanese Copyright Act and the Fair Use doctrine under 17 U.S.C. §107, we examine cross-border conflicts of law arising when data extraction, compute training, and model serving occur in separate jurisdictions. Furthermore, the paper analyzes the liability allocation between AI developers and compute/cloud infrastructure providers, distinguishing passive IaaS/PaaS conduits from integrated strategic partnerships. Grounded in Delaware corporate governance standards (the Caremark doctrine) and ESG supply-chain due diligence, we establish a practical compliance and contractual risk-allocation architecture to ensure sustainable, transparent knowledge ecosystems.