The perception and use of generative AI for science-related information search: Insights from a cross-national study

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; Kristian Hvidtfelt Nielsen; Michelle Riedlinger; Hyunjin Song

doi:10.1177/09636625241308493

The perception and use of generative AI for science-related information search: Insights from a cross-national study

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, Kristian Hvidtfelt Nielsen, Michelle Riedlinger, Hyunjin Song

^*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Abstract

Publicly accessible large language models like ChatGPT are emerging as novel information intermediaries, enabling easy access to a wide range of science-related information. This study presents survey data from seven countries (N = 4320) obtained in July and August 2023, focusing on the perception and use of GenAI for science-related information search. Despite the novelty of ChatGPT, a sizable proportion of respondents already reported using it to access science-related information. In addition, the study explores how these users perceive ChatGPT compared with traditional types of information intermediaries (e.g. Google Search), their knowledge of, and trust in GenAI, compared with nonusers as well as compared with those who use ChatGPT for other purposes. Overall, this study provides insights into the perception and use of GenAI at an early stage of adoption, advancing our understanding of how this emerging technology shapes public understanding of science issues as an information intermediary.

Original language	English
Journal	Public Understanding of Science
ISSN	0963-6625
DOIs	https://doi.org/10.1177/09636625241308493
Publication status	E-pub / Early view - 31 Jan 2025

Keywords

artificial intelligence
cross-national research
information search
survey

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10.1177/09636625241308493

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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., Ju Huang, C., Kankaria, S., Lo, Y.-Y., Nielsen, K. H., Riedlinger, M., & Song, H. (2025). The perception and use of generative AI for science-related information search: Insights from a cross-national study. Public Understanding of Science. Advance online publication. https://doi.org/10.1177/09636625241308493

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title = "The perception and use of generative AI for science-related information search: Insights from a cross-national study",

abstract = "Publicly accessible large language models like ChatGPT are emerging as novel information intermediaries, enabling easy access to a wide range of science-related information. This study presents survey data from seven countries (N = 4320) obtained in July and August 2023, focusing on the perception and use of GenAI for science-related information search. Despite the novelty of ChatGPT, a sizable proportion of respondents already reported using it to access science-related information. In addition, the study explores how these users perceive ChatGPT compared with traditional types of information intermediaries (e.g. Google Search), their knowledge of, and trust in GenAI, compared with nonusers as well as compared with those who use ChatGPT for other purposes. Overall, this study provides insights into the perception and use of GenAI at an early stage of adoption, advancing our understanding of how this emerging technology shapes public understanding of science issues as an information intermediary.",

keywords = "artificial intelligence, cross-national research, information search, survey",

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 {Ju Huang}, Chun and Siddharth Kankaria and Yin-Yueh Lo and Nielsen, {Kristian Hvidtfelt} and Michelle Riedlinger and Hyunjin Song",

year = "2025",

month = jan,

day = "31",

doi = "10.1177/09636625241308493",

language = "English",

journal = "Public Understanding of Science",

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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, Ju Huang, C, Kankaria, S, Lo, Y-Y, Nielsen, KH, Riedlinger, M & Song, H 2025, 'The perception and use of generative AI for science-related information search: Insights from a cross-national study', Public Understanding of Science. https://doi.org/10.1177/09636625241308493

The perception and use of generative AI for science-related information search: Insights from a cross-national study. / Greussing, Esther; Guenther, Lars; Baram-Tsabari, Ayelet et al.
In: Public Understanding of Science, 31.01.2025.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

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T1 - The perception and use of generative AI for science-related information search: Insights from a cross-national study

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 - Ju Huang, Chun

AU - Kankaria, Siddharth

AU - Lo, Yin-Yueh

AU - Nielsen, Kristian Hvidtfelt

AU - Riedlinger, Michelle

AU - Song, Hyunjin

PY - 2025/1/31

Y1 - 2025/1/31

N2 - Publicly accessible large language models like ChatGPT are emerging as novel information intermediaries, enabling easy access to a wide range of science-related information. This study presents survey data from seven countries (N = 4320) obtained in July and August 2023, focusing on the perception and use of GenAI for science-related information search. Despite the novelty of ChatGPT, a sizable proportion of respondents already reported using it to access science-related information. In addition, the study explores how these users perceive ChatGPT compared with traditional types of information intermediaries (e.g. Google Search), their knowledge of, and trust in GenAI, compared with nonusers as well as compared with those who use ChatGPT for other purposes. Overall, this study provides insights into the perception and use of GenAI at an early stage of adoption, advancing our understanding of how this emerging technology shapes public understanding of science issues as an information intermediary.

AB - Publicly accessible large language models like ChatGPT are emerging as novel information intermediaries, enabling easy access to a wide range of science-related information. This study presents survey data from seven countries (N = 4320) obtained in July and August 2023, focusing on the perception and use of GenAI for science-related information search. Despite the novelty of ChatGPT, a sizable proportion of respondents already reported using it to access science-related information. In addition, the study explores how these users perceive ChatGPT compared with traditional types of information intermediaries (e.g. Google Search), their knowledge of, and trust in GenAI, compared with nonusers as well as compared with those who use ChatGPT for other purposes. Overall, this study provides insights into the perception and use of GenAI at an early stage of adoption, advancing our understanding of how this emerging technology shapes public understanding of science issues as an information intermediary.

KW - artificial intelligence

KW - cross-national research

KW - information search

KW - survey

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U2 - 10.1177/09636625241308493

DO - 10.1177/09636625241308493

M3 - Journal article

C2 - 39891412

SN - 0963-6625

JO - Public Understanding of Science

JF - Public Understanding of Science

ER -

The perception and use of generative AI for science-related information search: Insights from a cross-national study

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Keywords

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