A new study published in Nature Human Behaviour reveals a steady rise in the use of ChatGPT and large language models in scientific writing.
Study tracks word shifts to estimate LLM text growth 2020–2024
Photo Credit: Nature Human Behaviour (2025)
At the launch of ChatGPT during November 2022, industries from speech writing to legal services are using it. This led to a spark in the Large Language Models across the globe. Academics have been keen to speed the writing and publishing procedure. This has naturally started to navigate how systems can lighten the scholarly load. To investigate the effects of ChatGPT on scientific writing, a research team took on the challenge of analyzing over 1.12 million papers and preprints from arXiv, bioRxiv, as well as journals from the Nature portfolio.
As per Phys org, thier findings, which were published in Nature Human Behavior, proposed a novel population-level approach for estimating the increase of LLM-derived text from 2020 to 2024 by tracking minute changes in word frequencies. Their results showed that the most AI-influenced sections of text were abstracts and introductions, whereas description of methods and detailed description of experiments were less impacted, perhaps because LLMs are primarily stronger at summarizing than detailing complex processes.
Gradually, the impact of AI extended into multiple fields of study, with the most notable growth occurring in computer science, which has always been at the intersection of AI. Further analysis of the data revealed some distinct trends.
LLM usage was more pronounced among authors who submitted preprints, likely due to the pressure to publish. Papers issued in a smaller size also tended to show more AI influence. Papers below 5,000 words, as well as those in fiercely contested fields, demonstrated more AI influence.
The way that science is written, and the way that it is shared is going to change for many years to come, and this change is driven by the development of AI. This change places many factors that are crucial for the research community in the limelight, such as originality, transparency, or the preservation of the publishing process in an AI-enhanced world.
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