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Artificial Intelligence and Data Protection from a Japanese Perspective

  • Yoichiro Itakura

摘要

This paper examines the relationship between artificial intelligence (AI), particularly generative AI, and data protection law in Japan. Although AI lacks a fixed definition, it is generally understood as computer systems that mimic human cognitive processes. Generative AI, based on large-scale pre-trained models, produces outputs such as text, images, and sound, and has rapidly gained societal adoption. Unlike the European Union’s GDPR and forthcoming AI Act, Japan does not have comprehensive AI regulation. Instead, it relies on soft-law instruments such as principles and guidelines. By contrast, the Act on the Protection of Personal Information (APPI), enforced by the Personal Information Protection Commission (PIPC), provides a comprehensive framework regulating acquisition, purpose limitation, security measures, third-party transfers, cross-border data flows, and data subject rights. The APPI does not contain AI-specific provisions; trained parameters generated through machine learning are not considered “personal information” unless linked to identifiable individuals. Recent developments include PIPC alerts concerning generative AI and successive APPI reforms through the triennial review system, which have tightened cross-border transfer rules and breach notification obligations. A notable feature of Japan’s framework is Copyright Act Article 30-4, which broadly permits the use of data for machine learning, leading some to call Japan a “Machine Learning Heaven.” Nonetheless, unresolved challenges remain, particularly regarding contractual safeguards, transparency in AI training, and harmonization with international standards. In conclusion, Japan primarily addresses AI through its existing legal framework, favoring flexibility over comprehensive regulation. However, given the rapid expansion of generative AI, more concrete governance on transparency, accountability, cross-border transfers, and research exemptions will be increasingly necessary.