Are We Facing a New Dark Age for Public Health Data?

"Could Chinese science meaningfully advance over the long run given that an estimated one-third of papers were thought to include fabricated or falsified data? Smugly, I thought that this was a uniquely Chinese problem related to a politicized academic system that excessively emphasized number and prestige of publications, even paying scientists and their institutions large cash bonuses for papers in esteemed journals."

"At the time, one of my duties was serving as the chief research integrity officer (RIO) for a large children's medical center. Trained by the NIH Office of Research Integrity, I was involved in all of the medical center's alleged research misconduct investigations for over a decade. Although some of the scientific fraud cases I investigated were eye-opening to be sure, I never once felt as if the integrity of U.S. science as a whole was in jeopardy."

Quality of science depends on the integrity and availability of underlying data. Two major threats imperil scientific data: artificial intelligence can fabricate convincing fraudulent datasets, and essential long-running public-domain datasets are being removed from access. Evidence indicates AI-generated data can pass close forensic scrutiny (Hua, 2025). Institutional incentives and publication pressures can exacerbate susceptibility to falsified results. Historical confidence in peer review and research oversight is now challenged by these twin risks, undermining reproducibility, transparency, and long-term credibility of scientific findings.

Read at Psychology Today