AI-assisted writing and the reorganization of scientific knowledge
2026-04-15 • Digital Libraries
Digital Libraries
AI summaryⓘ
The authors studied how much generative AI like ChatGPT is used in scientific papers and how it relates to new ideas and mixing of knowledge from different fields. They found that before 2023, AI use was weakly linked or even negatively linked to breakthroughs, but after 2023, AI was linked to more disruptive science within the same authors and fields. However, despite this disruption, AI did not lead to a wider mix of knowledge from different fields. This suggests that AI might help create new combinations of ideas, but mostly from a narrower set of sources rather than broadening the scientific search widely.
Generative AIChatGPTScientific writingDisruptionKnowledge recombinationCitation networksCross-field citationAI-assisted writingLarge Language ModelsScientific innovation
Authors
Erjia Yan, Chaoqun Ni
Abstract
Generative AI systems such as ChatGPT are increasingly used in scientific writing, yet their broader implications for the organization of scientific knowledge remain unclear. We examine whether AI-assisted writing intensity, measured as the share of text in a paper that is predicted to exhibit features consistent with LLM-generated text, is associated with scientific disruption and knowledge recombination. Using approximately two million full-text research articles published between 2021 and 2024 and linked to citation networks, we document a sharp temporal pattern beginning in 2023. Before 2023, higher AI-assisted writing intensity is weakly or negatively associated with disruption; after 2023, the association becomes positive in within-author, within-field analyses. Over the same period, the positive association between AI-assisted writing intensity and cross-field citation breadth weakens substantially, and the negative association with citation concentration attenuates. Thus, the post-2023 increase in disruption is not accompanied by broader knowledge sourcing. These patterns suggest that generative AI is associated with more disruptive citation structures without a corresponding expansion in cross-field recombination. Rather than simply broadening the search space of science, AI-assisted writing may be associated with new forms of recombination built from relatively narrower knowledge inputs.