AI-generated research papers are overwhelming peer review

"Published in 2017, the paper had assessed the accuracy of a particular type of statistical analysis on epidemiological data and had received a respectable few dozen citations in other research papers over the years, but now it was being referenced every few days, hundreds of times, placing it among the most cited papers of his career."

"Like the original, they were analyzing the Global Burden of Disease study, a publicly available dataset compiled by the Institute for Health Metrics and Evaluation at the University of Washington. But they were using the dataset to churn out a seemingly endless supply of predictions: about the future likelihood of stroke among adults over 20 years old, of testicular cancer among young adults, of falls among elderly people in China, of colorectal cancer among people who eat minimal whole grains, of disease X among population Y, and so on."

"Searching on GitHub for code that would be used to do this sort of analysis, Degen followed some links and wound up on the Chinese social media site Bilibili, where he discovered a Guangzhou-based company touting tutorials on how to produce publishable research in under two hours using its software tools and AI writing assistance."

"These studies were not very good. Researchers who analyzed a subset of studies about headaches found they were rife with errors and misrepresentations. But they were also not as flagrantly wrong as AI-generated papers of the recent past, making them more difficult to filter out."

A 2017 study assessing the accuracy of a statistical analysis on epidemiological data began receiving citations every few days, reaching hundreds and becoming one of the most cited works in its author’s career. The citing papers shared a common pattern: they used the Global Burden of Disease dataset and generated large numbers of predictions for many diseases, populations, and risk factors. The work was traced to code and tutorials that promoted producing publishable research quickly using software tools and AI writing assistance. A subset of related studies showed frequent errors and misrepresentations, though they were not as obviously wrong as earlier AI-generated papers, making them harder to detect and filter.

Read at The Verge