Artificial Intelligence in Scientific Judgment: Assistance, Dependence, or Disruption?

Abstract

Artificial intelligence (AI) is transforming scholarly publishing not by replacing editors or reviewers, but by reshaping how scientific judgment is formed within editorial and peer review systems. Traditionally, manuscripts entered peer review carrying their methodological weaknesses, analytical inconsistencies, and unsupported conclusions for human reviewers to identify and challenge. That sequence is changing. AI is increasingly being used during editorial triage and peer review workflows to evaluate methodological coherence, identify analytical gaps, summarize manuscripts, and highlight potential weaknesses before independent human critique fully develops. While this may improve efficiency, manuscript quality, and the precision of editorial screening, its deeper influence lies in the less visible ways scientific evaluation may become framed by machine-generated interpretation. As reviewers increasingly begin their assessment through AI-generated summaries and critiques, concerns arise regarding the gradual outsourcing of scientific judgment and the potential erosion of independent critical thought. These shifts are emerging within academic systems already strained by publication pressure, reviewer fatigue, and expanding research output. AI may strengthen scholarly publishing by supporting human evaluation, but its growing influence also raises an important question: can scientific judgment remain truly independent when machine interpretation increasingly precedes human critique?