New Article: AI Peer Reviewers Unleashed to Ease Publishing Grind
Most researchers have good reason to grumble about peer review: it is time-consuming and error-prone, and the workload is unevenly spread, with just 20% of scientists taking on most reviews.
Now peer review by artificial intelligence (AI) is promising to improve the process, boost the quality of published papers — and save reviewers time.
A handful of academic publishers are piloting AI tools to do anything from selecting reviewers to checking statistics and summarizing a paper’s findings.
In June, software called StatReviewer, which checks that statistics and methods in manuscripts are sound, was adopted by Aries Systems, a peer-review management system owned by Amsterdam-based publishing giant Elsevier.
And ScholarOne, a peer-review platform used by many journals, is teaming up with UNSILO of Aarhus, Denmark, which uses natural language processing and machine learning to analyse manuscripts. UNSILO automatically pulls out key concepts to summarize what the paper is about.
Crucially, in all cases, the job of ruling on what to do with a manuscript remains with the editor.
About Gary Price
Gary Price (firstname.lastname@example.org) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.