Andrews outlines four-step workflow for managing scientific literature with AI
Shea Andrews, an assistant professor at the University of California, San Francisco, describes a four-step workflow for navigating the growing volume of scientific papers. The process involves discovery, triage, skimming, and deep reading, with artificial intelligence assisting at each stage but not replacing critical judgment. Andrews emphasizes that selective reading is essential for managing the exponential growth of literature, particularly in fields like Alzheimer’s disease and genetics. While AI tools can summarize and search for papers, they risk fabricating citations, requiring researchers to verify outputs against original sources. This approach helps scientists balance efficiency with rigorous analysis, ensuring that AI aids rather than dictates their research process.
