There’s sloppy science, and there’s AI slop science.
In an ironic twist of fate, beleaguered AI researchers are warning that the field is being choked by a deluge of shoddy academic papers written with large language models, making it harder than ever for high quality work to be discovered and stand out.
Part of the problem is that AI research has surged in popularity. The more people who jump on the wagon, the more some are trying to speedrun an academic reputation by churning out dozens — and sometimes even hundreds — of papers a year, giving the entire pursuit a bad name.
In an interview with The Guardian, professor of computer science at UC Berkeley Hany Farid called the state of affairs a “frenzy.” With so much slop rising to the top, he says he now advises his students not to enter the field.
“So many young people want to get into AI,” Farid told The Guardian. “It’s just a mess. You can’t keep up, you can’t publish, you can’t do good work, you can’t be thoughtful.”
Farid stirred debate over the topic by calling out the output of an AI researcher named Kevin Zhu, who claims to have published 113 papers on AI this year.
“I can’t carefully read 100 technical papers a year,” Farid wrote in a LinkedIn post last month, “so imagine my surprise when I learned about one author who claims to have participated in the research and writing of over 100 technical papers in a year.”
Zhu, who recently received his bachelor’s in computer science at UC Berkeley — the same place that Farid teaches —launched an AI researcher program aimed at high schoolers and college students called Algoverse. Many of its participants are coauthors on Zhu’s papers, The Guardian noted. Each student pays $3,325 for a 12-week online course, during which they’re expected to submit work to AI conferences.
One of those conferences is NeurIPS, which is considered to be one of the big three conferences in a field that was once obscure but is now the center of attention as AI commands immense investment and social cachet. In 2020 it fielded less than 10,000 papers, according to The Guardian. This year, that number has jumped to over 21,500, a trend shared by other major AI conferences. The explosion has been so extreme that NeurIPS is now relying on PhD students to help review its flood of submissions.
The overwhelming volume is thanks to people like Zhu: 89 of his over a century of papers are being presented at NeurIPS this week.
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