Media Analysis: 200 academic papers in nine months.

Original Article : Using AI, a professor wrote 200 papers this year. Researchers are alarmed.

Publisher: The Washington Post III Author: Todd Wallack III Publication Date: 23rd September 2026

Summary of the original article:

A recent Washington Post article by Todd Wallack examines the unusual case of Nicholas Polson, a statistics professor at the University of Chicago, who has authored or co-authored more than 200 academic papers and a number of books in 2026 – and it’s not even the end of September yet! The volume of output has attracted considerable attention from other academics. Whilst there are no accusations of fraud, many are questioning the role of AI in his work.

Polson has acknowledged using AI to help produce the work, arguing that AI makes a “productive researcher far more productive”. However, he did not disclose to the Washington Post if he had been adequately transparent about his use of AI in the submissions of his papers.

SSRN, the research-sharing platform where Polson posted his papers, has removed 257 of his works and froze the accounts used to submit them. SSRN said the unusual volume of submissions was the more significant concern, rather than the absence of AI disclosures alone.

It is worth noting that SSRN submissions are not peer reviewed.

The article places the reported case within a wider concern about AI increasing the volume of academic research and paper submissions. An interesting graphic included in the reporting shows that, Elsevier (a major academic research publisher) has seen submissions rise from 2.7 million in 2022 to 4.2 millions in 2025. A staggering increase of over 50%. And, if you are wondering what the reason could be....then recall that ChatGBT was launched towards the end of 2022, and draw your own conclusions.

With journal editors already reporting substantial increases in submissions, there is now not just pressure for them to give consideration of AI and its appropriate utilisation in submissions, but also to deal with the sheer numbers of submissions too.

Why it matters for A4-AI (Academics for AI):

Whilst there has been considerable discussion about an academic submitting such a vast amount of academic research in such a short time frame, the significance of this story extends well beyond the academic in question.

The wider picture is that since the release of generative AI, researchers can access a supporting tool that can increase their production rate of academic papers.

However, there is an important distinction between AI-assisted productivity and AI-generated scholarship. Using AI to accelerate literature searches, analyse information or undertake routine research tasks does not necessarily diminish the intellectual contribution of the researcher. It simply speeds up its realisation. But generative AI is not just a mechanism for the researcher to research their thoughts more efficiently, it can be the actual initiator of ‘thought’ and can then carry through that thought to realisation of an academic paper submission. At least, that is the suspicion of some when hundreds of papers are submitted in the space of one year by a single academic.

Whilst Nicholas Polson has demonstrated that AI can increase quantity of production, the question remains if it can do so with appropriate quality? Notably, Polson’s papers were not peer reviewed. If they had been subject to peer review, perhaps his papers would have been filed under “AI Slop”, or perhaps not. Without having his papers subject to peer review, it would be unfair to question the quality of his papers.

But this fact itself raises challenges for academic journal editors....If AI enables researchers to increase their output substantially, the constraint may increasingly move from research production to research evaluation. Journals, editors and peer reviewers could face growing volumes of submissions without a corresponding increase in their capacity to assess them unless, of course, they turn to the use of AI themselves in the review process.

At what point, then, is it all about the AI?

The Polson case therefore raises a broader question for academia: if AI dramatically increases the potential volume of scholarly output, can a publishing system designed around human-scale production and human-scale peer review continue to operate effectively?

Questions for Academia:

• Does AI use for research papers increase the overall quantity of research submissions, but at the risk of an overall decline in quality?

• In the era of generative AI, does the role and value of peer review for research submissions increase?

• What should be the boundaries and transparency on AI usage for research paper submissions?

• What is the justified and effective use of AI in the review process of research paper submissions?

READ THE WASHINGTON POST ARTICLE HERE