Scholarly and scientific publishing is constantly evolving, and most recently driven by major movements towards open science and also influenced by the widespread availability of technology, like generative artificial intelligence. Negative influencers such as misaligned academic incentives, “pay-to-publish” publishing models, paper mills and plagiarism, and other unethical behaviors and their consequences are on the rise. The evergreen challenge? Keeping research transparent, trustworthy, and just plain honest. Research integrity is super important, to say the very least – and it is HOT! 

The integration of artificial intelligence (AI) into the peer review process is a rapidly evolving landscape, offering the promise of streamlined efficiency and increased objectivity. However, this exciting development also highlights several ethical considerations that reviewers should thoughtfully address and navigate. Most importantly, if a reviewer is considering using generative AI to help them with performing a peer review, first check journal policy on whether this is permissible and, if so, then how.

Peer review is a cornerstone of scholarly publishing, acting as a way to support the publication of high-quality research and to maintain scientific integrity. During peer review, experts evaluate the work of their peers, providing invaluable feedback. Some examples of key feedback during peer reviews include: evaluations of the validity of the scientific question(s) and approach, methodological rigor, how the work contributes to scientific advancement, potential errors or missing relevant/milestone references in the field, and significance and originality of the research (or appropriateness of reproduction in reproducibility studies, if applicable).