The Shift Towards Preprints in AI Policy Research: A Comparative Study of Preprint Trends in the U.S., Europe, and South Korea

Open Science

This preprint examines the impact of global events (COVID-19, ChatGPT) on preprint citation trends in AI policy research across the U.S., Europe, and South Korea. It operates within the open science paradigm, which promotes transparency and accessibility in research dissemination. The study analyzes bibliometric data to assess how these events influenced the shift towards preprints, comparing regional differences in adoption patterns. This work contributes to the existing body of knowledge within the open science paradigm by providing empirical evidence of how global disruptions interact with local research cultures and institutional practices. While it acknowledges the potential risks associated with preprints, such as the lack of formal peer review, the study primarily focuses on analyzing citation trends within established scholarly publications. This focus suggests the research is primarily engaged in normal science, refining and extending existing knowledge within the accepted open science framework rather than proposing radical shifts or challenging fundamental assumptions. However, given the relative novelty of preprints as a legitimate form of scholarly communication, particularly in the policy context, elements of 'Model Drift' could also be considered. The rapid adoption of preprints, driven by the urgency of global events and the fast-paced nature of AI research, might suggest a drift from traditional peer-reviewed publishing models. This drift, however, doesn't necessarily represent a crisis or revolution, but rather an adaptation within the broader open science movement. Therefore, the classification of 'Normal Science' is most appropriate, with 'Model Drift' as a secondary consideration reflecting the evolving dynamics of scholarly communication.