Can AI Replace Human Peer Reviewers? A Comparative Analysis of AI-Generated and Human Expert Reviews
Pit Pichappan, Preethi Pichappan
Journal of Digital Information Management, Vol. 23, No. 4, 2025.
DOI: https://doi.org/10.6025/jdim/2025/23/4/220-233
Link: https://www.dline.info/fpaper/jdim/v23i4/jdimv23i4_2.pdf
Abstract:
This work analyses the performance of AI-generated peer reviews compared to human expert reviews
across 62 manuscripts in the Real-Time Intelligent Systems track of the Springer Lecture Notes in Networks
and Systems. Using four large language models ChatGPT 3.5, Perplexity AI, Qwen-3 Max, and DeepSeek the
study evaluated 141 reviews using both AI and human reviews against 12 quality criteria, scored by five
domain experts. Results show human reviews scored higher overall (mean = 3.98 vs. 3.15 for AI) with greater
consistency and depth, particularly in methodological critique, literature contextualisation, and review
confidence. AI reviews were more generic and less specific, struggled with scholarly subtlety, though they
excelled at summarisation and formatting checks. While the difference approached statistical significance (p
= 0.08), the effect size (Cohen's d = 0.56) indicated a moderate practical gap. The study concludes AI cannot
replace human reviewers but may ethically augment the process in hybrid models under human oversight.