Artificial Intelligence (AI) has been the talk of the town in recent years, and the field of scholarly publishing is not left out of this AI revolution. With the deluge of research articles being published, AI has been identified as a game-changer in the publishing industry, from content creation to evaluation, enhancement, and distribution of research papers. AI has been used to improve editorial decision-making, accelerate time-to-submission by automating some areas of content creation, and help editors automate the creation of knowledge graphs, amongst other things. It has also been used to enhance the peer review process, improve the searchability of scholarly articles, and minimize the retraction of research papers.
Several organizations have already adopted AI in scholarly publishing. For instance, the American Association for Cancer Research uses AI to identify image duplication in manuscripts. The National Natural Science Foundation of China uses AI-enabled automation to reduce bias and workload in their grant review process. Also, Harvard, MIT, and EdX are using an automated essay scoring system to assess the large volumes of written work that emerge as part of MOOCs.
AI is commonly used across sectors and decision-making positions to enable better decision-making, like the tool called Penelope.ai, which can tell if the references and structure of a manuscript meet a journal’s norms and style. Meanwhile, another AI tool called Ripeta evaluates the integrity and reproducibility of scientific research, while Sciscore helps scholarly publishers to evaluate transparency in submitted manuscripts.
Several AI tools are available to automate some content creation areas, like the AI tool that fast-tracks research and analyzes research papers intelligently enough to output summaries. Other tools like Alviss automate abstract generation, UNSILO recognizes key concepts in a research paper to create a summary, while Audemic turns out audio summaries of research papers.
AI is also making strides in statistical and grammatical analysis, taxonomy, and ontology, making tools like StatCheck useful in assessing consistency in statistics reporting with a special focus on p-values. Graphium and Sciflow help editors automate the creation of knowledge graphs and enable faster editing and proofreading of manuscripts at scale.
AI can also help minimize the retraction of research papers, as retraction can occur due to manipulated images or unsound statistics that editors and reviewers might not be able to spot. AI-based image-checking tools like FigCheck, Proofig, ImaChek, and Imagetwin can now identify image manipulation and aid editors in ensuring that research papers are trustworthy.
In conclusion, AI has revolutionized the scholarly publishing industry, and as new advancements in AI continue to emerge, the way we produce and consume scholarly articles will continue to evolve.