- The open-access journal boom has fueled predatory publishers exploiting researchers with fees while skipping real peer review.
- An AI tool trained on 14,500 journals flagged over 1,000 suspicious publications but has a 24% false positive rate.
- Fake science is surging, with a 2025 study warning that paper mills are doubling fraudulent research output every 1.5 years.
- Predatory journals threaten public trust, distorting medical guidelines and policy decisions while wasting taxpayer funds.
- AI detection tools could be misused to censor legitimate but controversial research, raising concerns over truth control.
The explosion of open-access journals has democratized scientific research, but it has also given rise to a shadow industry of predatory publishers that exploit authors with publishing fees while offering little to no legitimate peer review. Now, researchers have developed an AI tool to detect these shady journals—but its 24% false positive rate means human experts are still essential.
Who’s behind it? A team of computational scientists, led by Daniel Acuña of the University of Colorado Boulder, trained an AI model on more than 14,500 journals—12,869 high-quality ones and 2,536 that had been removed from the Directory of Open Access Journals (DOAJ) for violating ethical guidelines. The AI then analyzed nearly 94,000 open-access journals, flagging more than 1,000 previously unknown suspect publications.
The problem with predatory journals
The open-access model was supposed to make research freely available to everyone, breaking down paywalls that restrict knowledge. But as the system grew, so did the number of journals that prioritize profit over scientific integrity. These “questionable” journals often promise rapid publication with little to no peer review, charging authors hefty fees while producing low-quality—or even fraudulent—research.
A 2025 study in PNAS found that the number of fake papers churned out by “paper mills” is doubling every 1.5 years, threatening to flood academia with junk science. “If these trends are not stopped, science is going to be destroyed,” warned Luís A. Nunes Amaral, a data scientist at Northwestern University.
Hellbound and Down 