AI ‘generating fake research data on industrial scale’, warns sleuth - Research Professional News

Microbiologist and research integrity sleuth Elisabeth Bik has warned that generative artificial intelligence is likely behind the creation of fake data in academic papers on an industrial scale. The warning was reported by Research Professional News on June 9, 2026. The scale of the problem is described as 'industrial,' indicating that large numbers of papers may contain fabricated data across various fields. The report uses the exact phrase 'industrial scale' to characterize the phenomenon.

Bik's concern focuses on how generative AI can produce convincing fake datasets that mimic real experimental results. This undermines the integrity of scientific research, as fraudulent papers can be generated faster than they can be detected by human reviewers. The phenomenon poses challenges for the peer-review process, which often relies on manual verification of data. Bik, described as a 'sleuth' in the article, has a history of identifying research misconduct.

The warning adds to growing concerns about the misuse of generative AI in academic contexts. Bik's finding, as reported, underscores the need for the scientific community to develop new methods to detect fabricated data. The issue is likely to intensify as generative AI models become more widely used by researchers looking to cut corners. The industrial-scale nature of the problem suggests that universities, publishers, and funding bodies will need to collaborate on solutions. The development comes amid broader debates about AI's impact on scientific integrity.