AI reviewers are here — we are not ready

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.

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.

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.

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.

ChicagoHAI/OpenAIReview

AI reviewing paper drafts for improvement.

Adil on Twitter / X

being assigned to review AI generated slop papers is very frustrating. the way this is supposed to work is that first you take the time to write something and then i take the time to read it. if you don't do the first part then i shouldn't have to do the second part.— Adil (@adilsoubki) August 26, 2026

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.

Accelerating Science with Human+AI Review

This issue of NEJM AI features the first two articles published through our accelerated human+AI review process. In this editorial, we describe the invitation-only “Fast Track” process used to revi...

AI peer review goes pro

A what we're reading spotlight

Towards Automating Scientific Review with Google's Paper Assistant Tool

Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem proving. However, this rapid acceleration is creating a systemic challenge: traditional human peer review cannot scale to match the influx of AI-assisted science. Ultimately, to resolve this tension, we must also deploy AI to accelerate the verification and review process itself. To frame the discussion around this transition, we propose a taxonomy consisting of four progressive levels of AI-human collaboration in scientific evaluation, and discuss various trade-offs involved with each. As a step toward this future, we introduce the Paper Assistant Tool (PAT), an agentic AI framework built for deep scientific review and verification. PAT ingests full scientific manuscripts and produces a comprehensive evaluation, checking theoretical results, validating experiments, suggesting improvements, and identifying potential flaws. By utilizing inference scaling techniques, PAT is able to identify deeper issues than a single model call alone, achieving a 34% improvement over zero-shot recall on mathematical errors in the SPOT benchmark. Pilot deployments of PAT as a pre-submission tool for authors at two major Computer Science conferences -- STOC and ICML -- demonstrate its ability to identify critical errors and suggest substantive improvements to research papers. By catching errors early, PAT eases the cognitive burden placed on referees, while preserving their control over the outcomes of the review process.

AI-powered Literature Review & Synthesis

Recording from my workshop last week on smarter literature review with AI

AI, peer review and the human activity of science

When researchers cede their scientific judgement to machines, we lose something important.