Ross Andersen writes:

On a frigid Norwegian afternoon earlier this month, Dan Quintana, a psychology professor at the University of Oslo, decided to stay in and complete a tedious task that he had been putting off for weeks. An editor from a well-known journal in his field had asked him to review a paper that they were considering for publication. It seemed like a straightforward piece of science. Nothing set off any alarm bells, until Quintana looked at the references and saw his own name. The citation of his work looked correct—it contained a plausible title and included authors whom he’d worked with in the past—but the paper it referred to did not exist.

Every day, on Bluesky and LinkedIn, Quintana had seen academics posting about finding these “phantom citations” in scientific papers. (The initial version of the Trump administration’s “MAHA Report” on children’s health, released last spring, contained more than half a dozen of them.) But until Quintana found a fake “Quintana” paper cited in a journal he was refereeing, he’d figured that the problem was limited to publications with lower standards. “When it happens at a journal that you respect, you realize how widespread this problem is,” he told me.

For more than a century, scientific journals have been the pipes through which knowledge of the natural world flows into our culture. Now they’re being clogged with AI slop.

Scientific publishing has always had its plumbing problems. Even before ChatGPT, journal editors struggled to control the quantity and quality of submitted work. Alex Csiszar, a historian of science at Harvard, told me that he has found letters from editors going all the way back to the early 19th century in which they complain about receiving unmanageable volumes of manuscripts. This glut was part of the reason that peer review arose in the first place. Editors would ease their workload by sending articles to outside experts. When journals proliferated during the Cold War spike in science funding, this practice first became widespread. Today it’s nearly universal.

But the editors and unpaid reviewers who act as guardians of the scientific literature are newly besieged. Almost immediately after large language models went mainstream, manuscripts started pouring into journal inboxes in unprecedented numbers. Some portion of this effect can be chalked up to AI’s ability to juice productivity, especially among non-English-speaking scientists who need help presenting their research. But ChatGPT and its ilk are also being used to give fraudulent or shoddy work a new veneer of plausibility, according to Mandy Hill, the managing director of academic publishing at Cambridge University Press & Assessment. That makes the task of sorting wheat from chaff much more time-consuming for editors and referees, and also more technically difficult. “From here on, it’s going to be a constant arms race,” Hill told me. [Continue reading…]