Benjamin Skuse set out to test whether AI-generated research could pass for the real thing. Science has a spam problem, and the spam filter is getting clogged up. Academic publishing is reportedly drowning in what has come to be called AI slop: low-quality, mass-produced content generated with AI. By 2025, an estimated 57 percent of published academic articles showed detectable evidence of large language model (LLM) influence, up from 12 percent in 2023. Over 12 percent of Nature Communications reviews were found to be completely AI-generated in 2025.
Because only one in 40 papers showing statistical evidence of AI usage in 2025 formally disclosed it, these figures likely underestimate LLM involvement. Evidence of AI use does not necessarily mean a paper is slop, but some estimates suggest hundreds of thousands of fake, often AI-generated, publications are produced annually. IEEE's research-integrity manager Amanda Sulicz warned that AI slop is completely eroding trust in science.
To test how easy it is to create a convincing fake paper, Skuse decided to "vibe-research" a made-up paper by prompting LLMs to generate hypotheses, code and text with minimal human input. He asked Jenny Mahoney, managing editor of the open-access journal IEEE Access, whether her journal could withstand an attempt to sneak the paper past its defenses. IEEE agreed.
The experiment had two parts. First, whether someone with no special AI expertise could use free, off-the-shelf tools to generate a convincing paper describing research that was never performed. Second, what happens when more advanced AI systems conduct the underlying research itself. The project offers a window into how AI automation is transforming scientific discovery and forcing publishers to rethink the academic publishing system.
Source: Hacker News · Summarized by HeadlinesBriefing