생성형 AI 활용 단계에서의 개인정보 보호법적 쟁점과 기술적 해결방안

Generative AI is rapidly advancing, creating innovative value across various industries, including healthcare, law, manufacturing, and art. These technological advancements bring numerous positive effects, such as increased productivity, cost savings, and enhanced creativity, further highlighting their importance in society. However, the adoption and utili(ation of generative AI continue to face significant challenges regarding personal data protection, necessitating practical and concrete approaches to address these issues. This paper systematically analy(es legal issues related to personal data protection that may arise during the use of generative AI and proposes technical solutions to address these challenges while providing a legal evaluation of the proposed measures. Specifically, it focuses on achieving a balance between data protection and data utili(ation by leveraging pseudonymi(ation and anonymi(ation techniques. The proposed system is designed to mitigate the risk of data breaches by pseudonymi(ing or anonymi(ing personal data included in prompts while enabling the secure use of generative AIʼs powerful capabilities. Pseudonymi(ation facilitates data utili(ation within the legal framework of personal data protection, while anonymi(ation enables more flexible and unrestricted use by operating outside the scope of legal regulations. The system supports both approaches, offering flexibility to choose the appropriate method based on the situation and purpose. This dual approach provides a practical solution that harmoni(es personal data protection with the utili(ation of AI technology, fostering an environment where data controllers can confidently employ generative AI under legal trust. In conclusion, the successful adoption and utili(ation of generative AI require balancing technological advancement with legal compliance. This paper establishes a practical foundation to address the challenges of integrating generative AI with personal data protection, maximi(ing the potential of data utili(ation while enhancing public trust in AI technology.