Science publisher Springer Nature has developed two new AI tools to detect fake research and duplicate images in scientific papers, helping to protect the integrity of published studies.
The growing number of cases of fake research is already putting a strain on the scientific publishing industry, according to Springer Nature. Following a pilot phase, the publisher is now rolling out two AI tools to identify papers with AI-generated fake content and problematic images - both red flags for research integrity issues.
The first tool, called "Geppetto," detects AI-generated content, a telltale sign of "paper mills" producing fake research papers. The tool divides the paper into sections and uses its own algorithms to check the consistency of the text in each section.
The tool then scores each section based on the likelihood that the text is AI-generated. A high score triggers a manual review by Springer Nature staff. According to Springer Nature, the tool has already identified hundreds of fake papers before publication.
The publisher hasn't provided details on how the tool works. Known AI content detectors have proven to be unreliable. OpenAI even had to pull its own detector.
The second tool, SnappShot, is an AI-based image integrity analysis tool. It's currently being used to analyze PDFs of gel and blot images to look for duplicates - another well-known integrity issue in the industry. The tool will be extended to other image types and integrity issues to speed up the review of papers.
Both tools only flag papers that need manual assessment, according to Springer Nature. The publisher has more tools in development.
Chris Graf, Director of Research Integrity at Springer Nature, said the publishing industry faces a determined and malicious threat from paper mills or bad actors submitting fake papers with fabricated data, which could seriously undermine trust in science. Investigating and remediating these problems is time-consuming and resource-intensive, Graf said.
