Journal Article 1 Mention
More Versus Better: Artificial Intelligence, Incentives, and the Emerging Crisis in Peer Review
Claudine Madras Gartenberg•2026
Sharique HasanAlex Murray
Top 1% · 99th Percentile
40 citations · History and Philosophy of Science

TLDR

New writing tools have made more papers and reviews appear, but the writing and variety of ideas have worsened. Unless universities and journals change how they reward work, the system may favor producing more work instead of producing better work.

Summary

1 Study Aim

The authors examine how artificial intelligence (AI), computer systems that generate or analyze content, is changing journal submissions and peer review. They ask whether AI, combined with publish-or-perish incentives (pressure to produce many publications), is increasing output while reducing quality. The study avoids deciding which uses of AI are appropriate because adoption is still new. The research asks whether academic publishing is becoming busier without becoming better.

2 Study Design

The study analyzes 6,957 initial submissions and 10,389 textual reviews at Organization Science from 2021 through 2026. The authors compare writing quality in submissions and reviews associated with AI-generated writing against human-generated writing. They also examine topical diversity, meaning the range of subjects discussed in reviews. Conversations with editors across scientific fields provide broader context, although the authors do not claim these observations represent every journal. The researchers compared thousands of papers and reviews before and after AI tools became widely available.

3 Findings

The study reports a 42% increase in submission volume after ChatGPT’s release in late 2022, alongside declining writing quality. The authors estimate that AI-generated writing explains nearly all of these changes. AI-generated reviews also became more common, showed lower writing quality, and covered a narrower range of topics than human-generated reviews. Editor conversations suggest similar pressures across disciplines. The authors argue that current tools and publish-or-perish incentives are pushing research toward more output rather than better work. They recommend adapting institutions and reward systems if AI is to support innovation. More papers and reviews are being produced, but the overall system may be losing quality and variety.

Abstract

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 has risen 42% since the late 2022 release of ChatGPT, while writing quality has declined. The rise in AI-generated writing accounts for nearly all of these trends. AI-generated writing in reviews has also increased, and is characterized by lower writing quality and less topical diversity than human-generated writing. We are, to our knowledge, the first journal to report these early impacts of AI in the review process. Conversations with editors across scientific disciplines, however, suggest that what we observe is not limited to our journal or to the social sciences. At this early stage of AI adoption, we cannot make a normative assessment about appropriate or ideal levels of AI usage. We can, however, conclude that the current state of AI tools, amplified by existing publish-or-perish incentives, appears to be pushing the system toward an equilibrium of more rather than better research. Reaching an equilibrium in which AI serves as a critical engine of innovation will require that our institutions and the incentive structures they create adapt. Funding: S. Hasan used research funding from Duke University’s Fuqua School of Business. C. Gartenberg used research funding from University of Pennsylvania’s Wharton School. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2026.ed.v37.n3 .

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