Serge Horbach, Michael Ochsner, and Wolfgang Kaltenbrunner, in a Leiden Madtrics post, detail a vexing guest-editing role at a Frontiers journal, circa late 2022:
Reviewers are selected by an internal artificial intelligence algorithm on the basis of keywords automatically attributed by the algorithm based on the content of the submitted manuscript and matched with a database of potential reviewers, a technique somewhat similar to the one used for reviewer databases of other big publishers. While the importance of the keywords for the match can be manually adjusted, the fit between submissions and the actually required domain expertise to review them is often less than perfect. This would not be a problem were the process of contacting reviewers fully under the control of the editors. Yet the numerous potential reviewers are contacted by means of a preformulated email in a quasi-automated fashion, apparently under the assumption that many of them will reject anyway. We find this to be problematic because it ultimately erodes the willingness of academics to donate their time for unpaid but absolutely vital community service. In addition, in some cases it resulted in reviewers being assigned to papers in our Research Topic that we believed were not qualified to perform reviews. Significant amounts of emailing and back-and-forth with managing editors and Frontiers staff were required to bypass this system, retract review invitations and instead focus only on the reviewers we actually wanted to contact.
Their post appeared just one month before ChatGPT’s public roll-out. How many AI peer-review “solutions” like this are in the works now?