Using Large Language Models to Summarize Evidence in Biomedical Articles: Exploratory Comparison Between AI- and Human-Annotated Bibliographies

Rapidly learning a body of scientific literature is a vital yet daunting task that may be made more efficient by AI tools. In our study, ChatGPT quickly generated concise summaries of academic literature and also provided quality and context more consistently than humans. However, ChatGPT's discussion of the quality and context was not always accurate, and ChatGPT annotations included more errors. Annotated bibliographies that are AI-generated and carefully verified by humans may thus be an efficient way to provide a rapid overview of literature. More research is needed to determine the extent that prompt engineering can reduce errors and improve chatbot performance.