Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries
This study explores the role of ChatGPT in science-related information retrieval, building on research conducted in 2023. Drawing on online survey data from seven countries—Australia, Denmark, Germany, Israel, South Korea, Taiwan, and the United States—and two data collection points (2023 and 2024), the study highlights ChatGPT’s growing role as an information intermediary, reflecting the rapid diffusion of generative AI (GenAI) in general. While GenAI adoption is a global phenomenon, distinct regional variations emerge in the use of ChatGPT for science-related searches. Additionally, the study finds that a specific subset of the population is more likely to use ChatGPT for science-related information retrieval. Across all countries surveyed, science-information seekers report higher levels of trust in GenAI compared to non-users. They also exhibit a stronger understanding of how (Gen)AI works and, with some notable exceptions, show greater awareness of its epistemic limitations.
Authors
- Anwesha Chakraborty (ORCID: https://orcid.org/0000-0002-1681-870X)
- Esther Greussing (ORCID: https://orcid.org/0000-0001-8655-5119)
- Inbal Klein-Avraham (ORCID: https://orcid.org/0000-0002-2642-5686)
- Monika Taddicken (ORCID: https://orcid.org/0000-0001-6505-3005)
- Michelle Riedlinger (ORCID: https://orcid.org/0000-0003-4402-4824)
- Ayelet Baram‐Tsabari (ORCID: https://orcid.org/0000-0002-8123-5519)
- Hyunjin Song (ORCID: https://orcid.org/0000-0001-7752-3035)
- Becca Beets (ORCID: https://orcid.org/0000-0002-3323-1281)
- Siddharth Kankaria (ORCID: https://orcid.org/0000-0001-9498-2145)
- Dominique Brossard (ORCID: https://orcid.org/0000-0002-9188-8388)
- Lindsey A. Middleton (ORCID: https://orcid.org/0000-0001-9251-2676)
- Antoinette Mary Fage-Butler (ORCID: https://orcid.org/0000-0002-4849-0227)
- Yin‐Yueh Lo (ORCID: https://orcid.org/0009-0007-7436-5415)
- Kristian Hvidtfelt Nielsen (ORCID: https://orcid.org/0000-0002-6192-400X)
- Chun-Ju Huang (ORCID: https://orcid.org/0000-0002-1879-2646)
- Torben Esbo Agergaard
- Lars Guenther (ORCID: https://orcid.org/0000-0001-7760-0416)
- Shakked Dabran‐Zivan (ORCID: https://orcid.org/0000-0002-2331-2571)
- Evelyn Jonas (ORCID: https://orcid.org/0009-0006-1942-4622)
Institutions
- University of Wisconsin–Madison (US)
- University of Urbino (IT)
- Yonsei University (KR)
- University of Maryland, College Park (US)
- Shih Hsin University (TW)
- Technische Universität Braunschweig (DE)
Publication Details
- Journal
- Journal of Science Communication
- Published
- 2025-04-14
- DOI
- https://doi.org/10.22323/2.24020205
- Citations
- 7
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 4.58
Funders
- Wisconsin Alumni Research Foundation
- Aarhus Universitet
- Yonsei University
- Aarhus Universitets Forskningsfond
- National Science and Technology Council