For advancements in scholarly output discovery to exist, systematic content structuring, clustering and categorisation must evolve, writes Sally Ekanayaka
This piece discusses the interesting and exciting directions AI is taking scholarly publishing, but for us it raising a troubling question, what will this mean for independent researchers, poorer publications, institutions or countries that cannot afford AI? Could this exacerbate the exclusions and inequalities that already exist in science?
Granted, scholarly communications is ever-expanding, never-ceasing, certainly more and more openly available, and build up of content across preprint servers, journals and books. But with a digitised, more predominantly open access (OA) landscape come new norms and new expectations, all connected to a wave of novel publishing technologies and standards.
So, the question. Where is AI, the newest comrade in publishing, taking us?
MyScienceWork Data Scientist Maha Amami, Ph.D shares some success stories about AI applications in scholarly communications as related to research artefacts.