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

Journal: Public understanding of science (Bristol, England)
Published Date: Jan 31, 2025

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 ( = 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.

Authors

  • Esther Greussing
    Technische Universität Braunschweig, Germany.
  • Lars Guenther
    LMU Munich, Germany.
  • Ayelet Baram-Tsabari
  • Shakked Dabran-Zivan
    Technion-Israel Institute of Technology, Israel.
  • Evelyn Jonas
    Technische Universität Braunschweig, Germany.
  • Inbal Klein-Avraham
    Technion-Israel Institute of Technology, Israel.
  • Monika Taddicken
    Technical University of Braunschweig, Germany.
  • Torben Esbo Agergaard
    Aarhus University, Denmark.
  • Becca Beets
    Department of Life Sciences Communication, University of Wisconsin-Madison, Madison, WI, United States.
  • Dominique Brossard
    University of Wisconsin-Madison, USA.
  • Anwesha Chakraborty
    University of Urbino, Italy.
  • Antoinette Fage-Butler
    Aarhus University, Denmark.
  • Chun-Ju Huang
    National Chung Cheng University, Taiwan.
  • Siddharth Kankaria
    Ashoka University, India.
  • Yin-Yueh Lo
    Shih Hsin University, Taiwan.
  • Kristian H Nielsen
    Aarhus University, Denmark.
  • Michelle Riedlinger
    Queensland University of Technology, Australia.
  • Hyunjin Song

Keywords

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