What you need to know about artificial intelligence in research and publishing
Artificial intelligence (AI) makes it possible for machines to “learn” and perform human-like tasks. Every industry is now implementing some form of AI, and these applications are continuing to grow. AI has become a part of our daily lives too. Moments ago, as I sat typing this, AlexaTM
informed me that based on my previous purchases, it might be time to re-order microwaveable popcorn!
As with nearly any industry, AI technology has made inroads into various processes in the publishing industry. The scope and applications of AI throughout the publication process are tremendous and constantly evolving.
AI can assist authors, editors, and publishers
AI in publishing is no longer just a novelty; it is being applied at various points in the publication pipeline. Further, the growing volume of open access scholarly content, including datasets and code, provides a rich resource for training datasets.
Authors can harness AI tools to speed up the publication cycle
Several AI offerings can support different steps in the scholarly publication cycle. AI-powered tools for literature discovery and summarization can free up time for other research activities. AI-trained platforms can assist with grammar and language checks and formatting checks. Further, AI-based pre-peer review screening can guide authors to revise their paper before it is sent for peer review. This reduces the chances of desk rejection and can shorten the peer review period.
Editors and reviewers can benefit from AI tools for faster turnarounds
At journal editorial offices, AI tools have the potential to take the load off various tedious tasks—managing astronomical submission volumes, increasing process efficiency, and developing more efficient peer review processes. AI has been used to assist with selecting journals, identifying a paper’s subject matter, determining if the subject falls within the journal’s scope, suggesting reviewers, assessing language quality, detecting plagiarism and duplicate submission, formatting documents, and assessing the appropriateness of experimental design and statistical analyses.1 Other opportunities include assessing the novelty of a study and checking for ethical compliance, copyright issues, and image duplication. The opportunities for AI in publishing are expected to keep growing and evolving rapidly.
