Preprint by author Richard Murdoch Montgomery presents a radical reassessment of scientific validation processes, arguing that traditional peer review has become an outdated, inefficient, and ultimately flawed mechanism for ensuring research quality.
Modern artificial intelligence systems demonstrate superior capabilities in analyzing methodological rigor, statistical validity, and literature comprehensiveness, while being free from human cognitive biases, professional rivalries, and institutional politics. Through examination of empirical evidence, demonstrated how AI systems consistently outperform human reviewers in speed, accuracy, and comprehensiveness of research evaluation.
The current peer review system, characterized by months-long delays, substantial costs, and demonstrable biases, actively impedes scientific progress. Author proposes a fully automated AI-driven validation framework that can evaluate research in real-time, identify methodological flaws, verify statistical analyses, and assess significance within the broader scientific context.
