Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries

Esther Greussing; Lars Guenther; Ayelet Baram-Tsabari; Shakked Dabran-Zivan; Evelyn Jonas; Inbal Klein-Avraham; Monika Taddicken; Torben Esbo Agergaard; Becca Beets; Dominique Brossard; Anwesha Chakraborty; Antoinette Fage-Butler; Chun-Ju Huang; Siddharth Kankaria; Yin-Yueh Lo; Lindsey Middleton; Kristian Hvidtfelt Nielsen; Michelle Riedlinger; Hyunjin Song

doi:10.22323/2.24020205

Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries

Esther Greussing, Lars Guenther, Ayelet Baram-Tsabari, Shakked Dabran-Zivan, Evelyn Jonas, Inbal Klein-Avraham, Monika Taddicken, Torben Esbo Agergaard, Becca Beets, Dominique Brossard, Anwesha Chakraborty, Antoinette Fage-Butler, Chun-Ju Huang, Siddharth Kankaria, Yin-Yueh Lo, Lindsey Middleton, Kristian Hvidtfelt Nielsen, Michelle Riedlinger, Hyunjin Song

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

Abstract

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). 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.

Originalsprog	Engelsk
Artikelnummer	A05
Tidsskrift	Journal of Science Communication
Vol/bind	24
Nummer	2
Sider (fra-til)	A05-A05
ISSN	1824-2049
DOI	https://doi.org/10.22323/2.24020205
Status	Udgivet - 2025

Adgang til dokumentet

10.22323/2.24020205Licens: CC BY-NC-ND

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Link to publication in Scopus

Citationsformater

Greussing, E., Guenther, L., Baram-Tsabari, A., Dabran-Zivan, S., Jonas, E., Klein-Avraham, I., Taddicken, M., Agergaard, T. E., Beets, B., Brossard, D., Chakraborty, A., Fage-Butler, A., Huang, C.-J., Kankaria, S., Lo, Y.-Y., Middleton, L., Nielsen, K. H., Riedlinger, M., & Song, H. (2025). Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries. Journal of Science Communication, 24(2), A05-A05. Artikel A05. https://doi.org/10.22323/2.24020205

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title = "Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries",

abstract = "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). 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.",

keywords = "AI tools in science communication, Digital science communication, Public engagement with science and technology",

author = "Esther Greussing and Lars Guenther and Ayelet Baram-Tsabari and Shakked Dabran-Zivan and Evelyn Jonas and Inbal Klein-Avraham and Monika Taddicken and Agergaard, {Torben Esbo} and Becca Beets and Dominique Brossard and Anwesha Chakraborty and Antoinette Fage-Butler and Chun-Ju Huang and Siddharth Kankaria and Yin-Yueh Lo and Lindsey Middleton and Nielsen, {Kristian Hvidtfelt} and Michelle Riedlinger and Hyunjin Song",

year = "2025",

doi = "10.22323/2.24020205",

language = "English",

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pages = "A05--A05",

journal = "Journal of Science Communication",

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Greussing, E, Guenther, L, Baram-Tsabari, A, Dabran-Zivan, S, Jonas, E, Klein-Avraham, I, Taddicken, M, Agergaard, TE, Beets, B, Brossard, D, Chakraborty, A, Fage-Butler, A, Huang, C-J, Kankaria, S, Lo, Y-Y, Middleton, L, Nielsen, KH, Riedlinger, M & Song, H 2025, 'Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries', Journal of Science Communication, bind 24, nr. 2, A05, s. A05-A05. https://doi.org/10.22323/2.24020205

Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries. / Greussing, Esther; Guenther, Lars; Baram-Tsabari, Ayelet et al.
I: Journal of Science Communication, Bind 24, Nr. 2, A05, 2025, s. A05-A05.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

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T1 - Exploring temporal and cross-national patterns: The use of generative AI in science-related information retrieval across seven countries

AU - Greussing, Esther

AU - Guenther, Lars

AU - Baram-Tsabari, Ayelet

AU - Dabran-Zivan, Shakked

AU - Jonas, Evelyn

AU - Klein-Avraham, Inbal

AU - Taddicken, Monika

AU - Agergaard, Torben Esbo

AU - Beets, Becca

AU - Brossard, Dominique

AU - Chakraborty, Anwesha

AU - Fage-Butler, Antoinette

AU - Huang, Chun-Ju

AU - Kankaria, Siddharth

AU - Lo, Yin-Yueh

AU - Middleton, Lindsey

AU - Nielsen, Kristian Hvidtfelt

AU - Riedlinger, Michelle

AU - Song, Hyunjin

PY - 2025

Y1 - 2025

N2 - 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). 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.

AB - 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). 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.

KW - AI tools in science communication

KW - Digital science communication

KW - Public engagement with science and technology

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U2 - 10.22323/2.24020205

DO - 10.22323/2.24020205

M3 - Journal article

SN - 1824-2049

VL - 24

SP - A05-A05

JO - Journal of Science Communication

JF - Journal of Science Communication

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