A network of sham academic journals has published more than a hundred likely AI-generated papers in recent months, in some cases attributing the work to real professors at leading universities without their knowledge. The episode highlights how cheaply produced, machine-written manuscripts can masquerade as legitimate scholarship and exploit weaknesses in the publishing ecosystem. Academics say the impersonations risk reputational harm, pollute citation databases and search results, and complicate hiring, promotion and grant reviews that rely on publication records. The incidents underscore pressure on publishers, indexers and universities to tighten identity verification and provenance checks, such as requiring stronger ORCID validation, digital signatures and clearer disclosure rules for AI use. While the scale of the operation remains unclear, researchers warn that low-cost generative tools make such schemes easier to run and harder to detect, raising broader questions about how the scientific record will be vetted in an era of automated text. The controversy adds urgency to efforts to bolster trust and traceability in research.
Related articles:
— Predatory publishing
— Scientific misconduct
— Academic authorship
— ORCID
