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AI flood overwhelms peer review in 2023

Peer review faces collapse due to an overwhelming surge of 4.5 million AI-assisted research papers in 2023, straining unpaid reviewers and degrading review quality. Solutions like paying reviewers orโ€ฆ

Peer review is overwhelmedโ€”can it survive in the AI era?
Ars Technica โ€” 10 August 2026
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Peer review is drowning. The flood of research papersโ€”now turbocharged by AI toolsโ€”has overwhelmed a system built for a slower age. In 2023, scientists uploaded over 4.5 million papers to the arXiv preprint server alone. Add journals, conferences, and grant applications, and the deluge is crushing the army of unpaid volunteers who decide what gets published.

The crisis has been building for years. Journals once handled a trickle of submissions from small research communities. Then came the internet, which made publishing easier and research fields exploded. Now AI accelerates the flow even faster: tools like large language models help researchers write drafts, generate figures, and churn out literature reviews. But they also swell the volume of submissions and sometimes compromise quality, pushing editors to send more papers to reviewers who are already overloaded. A 2022 study in Nature found that 70% of reviewers say their workload has risen sharply in five years, yet only 20% feel they can give each paper enough time.

The strain shows. A 2023 survey of 340 journals by the Association of Learned and Professional Society Publishers found average review times rose by 50% since 2019. Some fields fared worse: in machine learning, median review times hit eight weeks, up from four. Editors admit theyโ€™re increasingly accepting lower-quality reviews or desk-rejecting papers without full peer review just to keep up. Researchers report getting referee reports that read like AI-generated summariesโ€”vague, generic, or full of errors. The system risks becoming a rubber stamp, where speed replaces scrutiny and mistakes slip through.

Whatโ€™s next is unclear. Some propose radical fixes: paying reviewers, using AI reviewers, or crowdsourcing quality checks. Others want to shrink the volume by promoting preprint cultureโ€”letting work circulate before formal peer review. But none of these solutions address the root problem: thereโ€™s simply too much to review, and too few hands to do it. Without change, the peer review system that underpins scientific trust may buckle under its own weight.

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