Yeji Choi, Jaewook Byun, Dabin Lee, Hangbae Chang, Journal of Internet Computing and Services, Vol. 26, No. 6, pp. 63-74, Dec. 2025
10.7472/jksii.2025.26.6.63, Full Text:  HTML
Keywords: Generative AI, Personal Data Protection, Regulatory Comparison, Keyword Network Analysis, International Policy Coordination

Abstract

With the rapid advancement and widespread adoption of generative AI technology, Personal Data Protection has emerged as a significant societal concern. Given the discrepancies among Personal Data Protection regulations across various jurisdictions, establishing globally consistent regulatory standards has become increasingly critical. The extensive use of data inherent in generative AI applications raises considerable risks regarding potential breaches or misuse of Personal Data. However, an internationally unified response remains inadequate. In this research, we conducted a comparative analysis of 85 provisions related to Personal Data Protection extracted from regulatory frameworks including the "National Artificial Intelligence Initiative Act of 2020" from the United States, the EU's "Artificial Intelligence Act (Regulation (EU) 2024/1689)," and China's "Interim Measures for the Management of Generative Artificial Intelligence Services," utilizing a keyword network analysis methodology. Our analysis identified distinct regulatory characteristics for each region. The United States places significant emphasis on safeguarding fundamental civil rights, data ownership, and security, promoting a balanced approach between technological innovation and the protection of individual rights. The European Union prioritizes the prevention of Personal Data infringements through clearly delineated roles for supervisory authorities and explicit objectives for data processing. Conversely, China implements stringent, state-driven administrative controls aimed primarily at preserving national security and social stability. Additionally, our study uncovered common keywords across jurisdictions, such as "provider," "enforcement," and "risk," thus offering a foundational basis for enhanced international regulatory collaboration. The findings of this research are expected to provide practical foundational insights for establishing global regulatory standards and facilitating policy discussions on generative AI.

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