The application potential, challenges, and implications of artificial intelligence in psychobiography

Abstract: The rapid development of large language models (LLMs) in artificial intelligence presents new opportunities for psychobiography to address longstanding challenges, such as large data volumes, complex processing, and subjectivity. This paper systematically explores the potential, challenges, and implications of applying LLMs in psychobiography research. On the one hand, LLMs can improve research efficiency and analytical capacity. On the other hand, they also pose potential challenges, including data bias, interpretive deviation, and limitations in semantic understanding, as well as associated ethical risks. Facing these challenges, this paper proposes three possible solutions: first, constructing a localized large language model database to provide solutions to address cultural context and data bias issues; second, proposing ethical guidelines for human-machine collaboration in the field of psychobiography to guide the standardized development of psychobiography research in the era of artificial intelligence; third, proposing a theoretical concept of constructing a researcher-led human-machine collaborative research framework to point out the direction for the methodological path of psychobiography in the era of artificial intelligence.