How AI Is Reshaping Science’s Most Trusted Tool
A new wave of tools, based on generative AI, aims to go beyond sorting papers and to automate various stages of the reviewing process. Some products, such as Elicit and SciSpace, feel like the chatbots we are so accustomed to: users can type a question, and the system returns a summary of the research (with sources). Effectively, these tools are trying to handle all aspects of the review—the search, inclusion, and synthesis. Others, like Nested Knowledge, are more constrained, and look more like the specialized software reviewers already trust, just with AI features layered in. In both cases, the promise is that work that currently takes months could soon be done in minutes or hours.
Now, a process typically filled with red tape feels like a scientific wild west. Generative AI-based tools are being heavily marketed, while strict guidelines for how to integrate them into the review pipeline have lagged behind. “Everything is moving very, very fast” said Kristen Scotti, STEM Librarian at Carnegie Mellon. “A lot of the recommendations are not out yet, so people are just kind of flopping around.”
An increasing number of reviews are being conducted with these new tools. So far, these haven’t been published in the most prestigious journals, where they are likely to make the most impact, partly because there were no widely accepted standards for what responsible AI use looks like.
