Summary of Key Points
This news report exposes a startling academic phenomenon: Mahato, a second-year medical student from Nepal, published nearly 120 papers in just two years. Behind this achievement was an international “research production line” established through WhatsApp, which involved breaking down the paper-making process into separate tasks such as topic selection, writing, data analysis, and submission—much like assembling phone cases in a factory. The purpose of this approach was not to pursue knowledge but to quickly produce papers that met the evaluation criteria, with authors’ names often being exchanged for conference attendance rights. The introduction of AI has made this process even more efficient, leading to a surge in “compliant yet useless” research output. This is not just an individual scandal but also a reflection of the imbalance in the global academic evaluation system, serving as a wake-up call for China’s own scientific research reforms.
1. The Research Production Line: Assembling Papers Like Phone Cases
Mahato’s team broke down papers into standardized components. Some members sourced data from public databases (such as those of the CDC in the United States), others wrote the method sections, others polished the language, and still others handled the submission formats. Even conference attendance could be traded for author credits—for example, attending a conference in the U.S. could earn you a co-authorship on a paper.
The efficiency of this system stems from two factors: first, the papers selected were low-barrier and easily replicable (such as systematic reviews or meta-analyses), which did not require a laboratory; by simply changing the disease, gender, or time frame, a “new” paper could be produced using a template. Second, the use of AI has significantly accelerated this process, allowing for the generation of dozens of papers in a single day, with AI handling tasks like writing and charting faster than humans. Essentially, this constitutes an academic “content farm” that produces large quantities of seemingly compliant papers without genuine intellectual contribution.
2. Why Do People Produce Papers So Frantically? The Evaluation System Is the Motivation
Mahato and his colleagues are not fools; they are driven by reality. Papers have become a form of “hard currency” in academia. For instance, medical students from developing countries need a certain number of papers on their resumes to get into hospitals in Europe and America, and in China, the number of SCI-indexed papers was once a key factor in evaluating professional titles and securing funding. When it becomes easier to produce ten short, quick papers than one in-depth study, “paper factories” emerge naturally, just as factories produce goods for sale. They produce papers to meet the demands of the evaluation system.
This industrial chain has existed for a long time; in the past, there were “writing farms” in Kenya and ghostwriting workshops in India. Now, with the help of AI, these have evolved into more sophisticated networks like Mahato’s, with AI reducing costs and expanding the scale of production.
3. “Research Garbage” Is More Hidden Than Fraud: Taking Up Space Without Adding Value
These mass-produced papers are not necessarily fraudulent (the data is not fabricated), but they are “hollow” in that they neither solve real problems nor expand the boundaries of knowledge. For example, using the CDC database with different variables to write ten similar papers is essentially repetitive work.
The impact is significant: According to Nature, over 10,000 papers were retracted worldwide in 2023, but the many unretired “garbage papers” are even more problematic. They take up journal space, making it harder for valuable research to be published, exhaust reviewers’ time, and mislead future researchers into thinking these findings are useful, leading to a waste of resources. This is similar to the problem of junk information on the internet—more of it makes it harder to find meaningful content.
4. AI Is Not the Savior; It’s Just an Accelerator for Paper Factories
Many believe AI will make research more efficient, but Mahato’s example shows that AI has not eliminated paper factories; instead, it has only accelerated their growth. Previously, writing a paper required multiple professionals to search for literature, organize data, and write the text. Now, AI can generate literature reviews, analyze data, and draft papers in one click, allowing a small team to perform what used to require a large factory.
While AI reduces the cost of paper production, it does not enhance the ability to create knowledge. It’s like using machines to produce cups faster, but if the cups are never used, the speed is meaningless.
5. A Warning for China: Stop Obsessing with Paper Quantity
This issue is not just a foreign scandal; it reflects a broader problem in China as well. In the past, we caught up with the total number of papers through a “quantity race,” but now AI has made quantity less valuable. The difference between publishing 100 and 10 papers may simply lie in the use of computational power and templates, rather than the depth of thought.
China’s efforts to move away from the “five-only” criteria (focusing solely on papers and professional titles) and adopt a system based on representative works are aimed at addressing this issue. In the future, what will be truly scarce will not be the ability to write papers but the ability to ask meaningful questions and the courage to solve real problems. If the evaluation system continues to focus on quantity, China may also see more instances of AI-driven paper production, leading to a waste of research resources.
Conclusion: The Soul of Science Cannot Be Lost
The industrial age made goods cheaper, but the AI era has made papers seem less valuable. The essence of science is the exploration of the unknown, not the production of text. Mahato’s story reminds us that the evaluation system should shift from counting papers to assessing their value. Researchers must return to a curiosity-driven approach; otherwise, no matter how many papers are produced, they will be nothing more than useless paper. China has an opportunity to transform its research from a quantity race to a focus on quality, leading to groundbreaking discoveries that can change the world.