AI-assisted Reviewing is Necessary and Should be Open

AI-assisted Reviewing is Necessary and Should be Open

Peer review is facing a death spiral. AI production tools are speeding it up. AI-assisted reviewing is necessary and should be open.

Peer review is overwhelmed—can it survive in the AI era?

As research and AI-assisted papers surge, volunteer reviewers struggle to keep up.

How do authors want to use AI for review?

A survey of researchers who compared AI-generated scientific reviews with journal-agnostic human peer review reveals that they overwhelmingly prefer using AI as a self-checking tool before submission rather than as a replacement for human reviewers. It encourages an “author-centric” model in which AI helps researchers improve their manuscripts before they are reviewed by their peers.

Guest Post — Now is the Time for AI in Peer Review, and Publishing Policies Need to Recognize This - The Scholarly Kitchen

Today's post asks us to acknowledge the role of AI in peer review and ensure practical guidance and policies that help scholars respond with consistency and confidence.

AI-Assisted Tools in the CHI 2027 Papers Review Process: What They Do, What They Do Not Do, and How Humans Remain Responsible - ACM CHI 2027

AI-Assisted Tools in the CHI 2027 Papers Review Process: What They Do, What They Do Not Do, and How Humans Remain Responsible Authors: Anna Cox, Tony Tang, Thomas Kosch, Erin Solovey, Petra Isenberg, Regan MandrykDate: 2026-08-29 Introduction In our recent post explaining the CHI 2027 Papers review process, we said we would pilot several AI-assisted […]

AI peer review goes pro

A what we're reading spotlight

The future of peer review requires AI support, not AI bans

Letter to the Editor

How well does AI peer review work?

A new evaluation benchmark

AI reviewers are here — we are not ready

Nature - Artificial intelligence promises rapid and polite feedback on papers — but we must first review the reviewer.

AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot

Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and timeliness. Recent advances in AI have led the community to consider its use in peer review, yet a key unresolved question is whether AI can generate technically sound reviews at real-world conference scale. Here we report the first large-scale field deployment of AI-assisted peer review: every main-track submission at AAAI-26 received one clearly identified AI review from a state-of-the-art system. The system combined frontier models, tool use, and safeguards in a multi-stage process to generate reviews for all 22,977 full-review papers in less than a day. A large-scale survey of AAAI-26 authors and program committee members showed that participants not only found AI reviews useful, but actually preferred them to human reviews on key dimensions such as technical accuracy and research suggestions. We also introduce a novel benchmark and find that our system substantially outperforms a simple LLM-generated review baseline at detecting a variety of scientific weaknesses. Together, these results show that state-of-the-art AI methods can already make meaningful contributions to scientific peer review at conference scale, opening a path toward the next generation of synergistic human-AI teaming for evaluating research.

ChicagoHAI/OpenAIReview

AI reviewing paper drafts for improvement.

AI’s Growing Role as Scientific Peer Reviewer | Stanford HAI

Stanford computer scientist James Zou is exploring how AI can accelerate scientific research and peer review. His finding: AI excels at spotting gaps, but judgment calls still need humans.

Major AI conference flooded with peer reviews written fully by AI

Nature - Controversy has erupted after 21% of manuscript reviews for an international AI conference were found to be generated by artificial intelligence.