Can AI Reduce Human Bias in Peer Review? A Proposal for a Hybrid Editorial System

Artificial intelligence (AI) has emerged as a powerful tool capable of assisting users across various fields of knowledge by enabling faster and more accurate decision-making. One notable application of AI is in the management and support of editorial boards for academic journals. In this context, AI can facilitate the initial review of submitted articles by identifying minor errors, formatting inconsistencies, or general quality issues without compromising the scientific rigor or reliability of the peer-review process. While scholarly judgment and critical evaluation must ultimately remain the responsibility of human reviewers, AI can serve as a valuable assistant, streamlining routine tasks and allowing reviewers to focus on the core scientific content and methodological soundness of manuscripts. By providing rapid preliminary assessments, AI can help editorial boards prioritize submissions, detect potential issues early, and significantly reduce the time and effort required for the editorial workflow. This integration not only accelerates the publication process but also enhances efficiency, ensuring that high-quality research reaches the scholarly community in a timely manner.