Difficulties and explorations in data privacy protection for large language models

Abstract

Large language models based on massive data training bring the possibility of generalized artificial intelligence, but also bring new risks and challenges to data privacy protection. This paper analyzes the risks of data privacy protection in the whole process of large language model, argues the new ethical difficulties faced by the principle of informed consent and the principle of "justification and necessity" of data collection, and explores the possible solution frameworks and paths, as well as the ethical difficulties that may still exist in the practice.

Keywords

• large language model;generative artificial intelligence;data privacy;informed consent;data liability