인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This paper offers an update - from the European perspective - to the debate on property rights in personal data. It argues that recent developments in the data processing technology and practices, specifically, the AI-driven Big Data Analytics, have rendered personal data a difficult object of enforceable individual property rights. There are two main reasons for this. First, data processing resulting from a decision of one person will inevitably have spill-over effects on others, e.g. as a result of profiling, or as a result of the same piece of data relating to a group of people, e.g. genetic data. This phenomenon is also called ‘network effect’. Therefore, true individual control over personal data and also the effective enforcement of the individual property rights in personal data are difficult if not impossible to achieve. Second, creating and managing property rights that are transparent in terms of the object of property and establishing the rights-holders is also challenging. This is due to the dynamic approach to the definition of personal data adopted in Europe: the same piece of data, depending on a particular context, can be personal and non-personal, more or less likely to relate to an identifiable natural person, and with a stronger or weaker link to that person. While it is debatable if this necessarily constitutes a problem for the purposes of applying the data protection law, and if the broadest definition of personal data can achieve the goals of complete and effective protection, enforcing property rights in personal data is difficult. The difficulty lies, first, in determining at which point the level of relation to an individual is sufficient to establish property rights, and second, in tracing the presence of such a relation to a person, the ‘data owner’.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.