AI tool identifies 1,000+ predatory journals threatening scientific integrity

Scientists at the University of Colorado Boulder have developed an AI tool that can identify predatory scientific journals—fake publications that charge researchers fees but skip the peer review process. The tool successfully identified over 1,000 illegitimate journals out of nearly 15,200 analyzed, addressing a growing threat to scientific integrity that can spread misinformation for decades.

The big picture: Predatory journals represent a significant threat to scientific credibility, as demonstrated by the infamous 1998 vaccine-autism study published by British doctor Andrew Wakefield that spread harmful misinformation despite appearing in a reputable journal.

How it works: The AI system replicates human analysis by examining multiple indicators of journal legitimacy.
• The tool visits journal websites to review information about authors, their publication history, and institutional affiliations.
• It considers factors like how new the journal is and whether it uses outdated website designs.
• The AI looks for correlations between different signals to determine trustworthiness.

The target: These journals typically prey on younger, inexperienced researchers who may not recognize the warning signs of illegitimate publications.

Why this matters: Professor Daniel Acuna explains that scientific misinformation has far-reaching consequences because “science is a big web of ideas that are all interconnected.”
• “So if one of those ideas is wrong, it’s going to affect an entire sub-part of science and potentially all of science,” Acuna said.
• The labor-intensive process of manually identifying these journals creates a persistent problem, as companies often spawn new fake journals when caught.

What they’re saying: Graduate student Pawin Taechoyotin draws parallels between scientific misinformation and broader online disinformation.
• “It also happens in science as well,” Taechoyotin said. “There are a lot of papers that are retracted five years after it was published or maybe 10 years after it was published.”
• “The reason the retraction could be found is that the results are not relevant or that there was manipulating of results.”

Commercial application: Acuna has launched ReviewerZero.ai, a startup that uses AI to detect various research integrity issues and helps publishers and institutions identify problematic authors and journals.

What’s next: Future research will focus on identifying networks of predatory journals, as Acuna has discovered these operations often involve entire companies and networks of fraudulent authors working together.