A New Era of Scientific Discourse: Transparent, AI-Augmented Peer Review for Rapid and Unbiased Scholarly Publishing

Abstract

Traditional academic peer review is plagued by systemic issues including significant delays, reviewer bias, and prohibitive costs. This paper introduces a novel operational model for scholarly publishing that leverages multiple large language models to conduct rapid, transparent, and unbiased peer review. We describe the architecture of our AI-augmented system, which requires consensus from at least two out of three different AI models, with all reviews published alongside manuscripts. Initial data from the first year demonstrates significant reduction in time-to-publication and successful evaluation of highly interdisciplinary research.