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

AI, peer review and the human activity of science

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

AI peer review goes pro

A what we're reading spotlight

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.

More Versus Better: Artificial Intelligence, Incentives, and the Emerging Crisis in Peer Review | Organization Science

As the AI Task Force for Organization Science, we provide an early account of artificial intelligence’s (AI) impact on both submissions and reviews at a major academic journal. Submission volume ha...

Science Is Drowning in AI Slop

Peer review has met its match.

Project Rachel: Can an AI Become a Scholarly Author?

This paper documents Project Rachel, an action research study that created and tracked a complete AI academic identity named Rachel So. Through careful publication of AI-generated research papers, we investigate how the scholarly ecosystem responds to AI authorship. Rachel So published 10+ papers between March and October 2025, was cited, and received a peer review invitation. We discuss the implications of AI authorship on publishers, researchers, and the scientific system at large. This work contributes empirical action research data to the necessary debate about the future of scholarly communication with super human, hyper capable AI systems.

A New Paradigm for Scientific Publishing, Peer Review, and Impact Assessment

Scientific publishing and peer review have evolved little in three centuries, while the demands placed on them have grown profoundly. The growing role of artificial intelligence has underscored deep, systemic shortcomings of an aging system that has largely evaded innovation, a system whose origins are appallingly closer to the invention of the printing press than to the internet. We can do better – much better. This article is intended as the beginning of a communal experiment: a living document that critically reviews the modern academic publishing and peer-review system and presents a concrete framework to address what bibliometrics experts¹ have characterized as "the pervasive misapplication of indicators to the evaluation of scientific performance". Building on the Leiden Manifesto, DORA, and a body of scholarship spanning many disciplines and decades, we present a community-governed, non-profit platform organized around three trust-weighted impact factors, for articles, authors, and reviewers, with full algorithmic transparency, an open development log, and structural decoupling of credibility scoring from content moderation and from monetization. We invite the community to discuss, critique, and help shape it.

AI has supercharged scientists—but may have shrunk science

Analysis of 41 million papers finds that although AI expands individual impact, it narrows collective scientific exploration

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.

Charting AI’s Role in Scientific Discovery — Renaissance Philanthropy – A brighter future for all through science, technology, and innovation

Renaissance Philanthropy, with support from Google.org , is conducting a landscape study of AI integration in scientific research — and we want your perspective.

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...