머신러닝 알고리즘의 데이터 처리에 대한 법적 제한의 한계

• 영문명: Limitations of Legal Regulations for Data Processing Performed by Machine Learning Algorithm : With Respect to Data Privacy and Anti-Discrimination
• 발행기관: 충북대학교 법학연구소
• 저자명: 남중권(Nam, Joong Kweon)
• 간행물 정보: 『과학기술과 법』제10권 제1호, 65~94쪽, 전체 30쪽
• 주제분류: 법학 > 법학
• 파일형태: PDF
• 발행일자: 2019.06.30

영문 초록

This article addresses the issues of how the evolution of machine learning field has an impact on the legal system. In the area of automated data processing, a legal model for data privacy protection is applied in a manner that regulates the collection and use of personal data. This model assumes primarily with the personal identification or identifiability. However, if we look closely at the process of collecting and using these data, we can confirm that the legal model for anti-discrimination based on the principle of anti-classification can also be applied in an overlapping manner. I analyze several legal cases in order to identify the overlapping points. In each cases, there are some legal issues about automated data processing for data privacy and/or anti-discrimination. Data processing performed by machine learning algorithm which is trained with dataset, is divided into three steps: collection(or selection), analysis, and application. Based on these distinctions, limitations of legal regulations for data processing that can be encountered in each step are reviewed through models for data privacy protection and anti-discrimination.

목차

Ⅰ. 서론

Ⅱ. 데이터 처리에 관한 법적 제한의 적용 사례

Ⅲ. 개인정보보호법 모델과 차별금지법 모델의 해석 방식

Ⅳ. 머신러닝 알고리즘의 데이터 분석에 대한 법적 제한의 한계

Ⅴ. 머신러닝 알고리즘의 분석 결과 사용에 대한 법적 제한의 한계

Ⅵ. 결론

키워드

머신러닝 알고리즘 통계적 데이터 분석 개인정보보호 차별금지 인공지능 에이 전트의 법적 책임 Machine Learning Algorithm Statistical Data Analysis Data Privacy Anti-Discrimination Legal Responsibility to AI Agent