Concerns rise as volume of research soars and quality drops
Claudine Gartenberg, an associate professor at the University of Pennsylvania’s Wharton School of Business, spotted a concerning trend last year in her role as a senior editor reviewing papers for publication in the academic journal Organization Science. She soon found her fellow editors were becoming equally troubled.
“It just started to feel different,” she says. “We were getting more submissions, and they felt worse, but we couldn’t quite put a finger on it. We felt something had fundamentally changed. We had a suspicion but didn’t know what it was.”
What they sensed, they believe, was the consequence of artificial intelligence — causing fundamental disruption in universities around the world, not just in learning and teaching, but also in the research carried out by academics.
As the overseers of a prestigious business journal, Gartenberg and her colleagues were able to access its records and this spring published one of the first rigorous studies on how AI is transforming academic publishing. The title says it all: More Versus Better: Artificial Intelligence, Incentives, and the Emerging Crisis in Peer Review.
They argued AI had not only been the driver of a 42 per cent increase in submissions to the journal since 2022, but that its use also explained a significant drop in their quality, assessed by a mix of AI detection and other analysis tools. Alongside this, the quality of comments by peer reviewers assessing whether to publish the papers also fell, marked by a greater focus on the theories the papers relied on rather than the new findings and the data they contained.
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“There’s justifiable excitement about the potential of AI. It unlocks considerable capabilities and is very exciting. It’s creating a big buzz within the field,” she says. “But when you study AI in the wild and the full distribution of what it is producing, the picture is not pretty at all.”
The findings mirror growing concerns across academia for researchers and reviewers…