AI Peer Review Faces Scrutiny Over Bias, Cost, and Reliability
AI tools are increasingly integrated into academic peer review, but new studies reveal significant flaws. While AI can audit the entire scientific corpus for a fraction of the cost of human review, it suffers from high acceptance rates, inability to judge novelty, and sensitivity to author metadata. Critics warn that current models may reinforce existing biases rather than ensure objective scientific evaluation.