All Eyez on AI: A Roadmap for Science Communication Research in the Age of Artificial Intelligence

Artificial Intelligence (AI) is profoundly reshaping the field of science communication research. We conducted a literature review of 35 articles published between 2002 and 2024, which reveals that research on AI in science communication is still in its infancy but growing, predominantly concentrated in Western contexts, and methodologically inclined toward quantitative approaches. The field largely focuses on communication about AI and public perceptions of AI rather than analyzing actual engagement with generative AI or its systemic impact on science communication ecosystems. To address these gaps, we propose a research agenda centered on four key areas: (1) communication about AI, (2) communication with AI, (3) the impact of AI on science communication ecosystems, and (4) AI’s influence on science, theoretical and methodological approaches.

Authors

Publication Details

Journal
Journal of Science Communication
Published
2025-04-14
DOI
https://doi.org/10.22323/2.24020401
Citations
6
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
13.70
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article

All Eyez on AI: A Roadmap for Science Communication Research in the Age of Artificial Intelligence

Sabrina Heike Kessler, Sophia Charlotte Volk, Daniela Mahl, Mike S. Schäfer
6 citations
Journal of Science Communication
Big Data and Business Intelligence
13.70
article

All Eyez on AI: A Roadmap for Science Communication Research in the Age of Artificial Intelligence

Sabrina Heike Kessler, Sophia Charlotte Volk, Daniela Mahl, Mike S. Schäfer
article en
6 citations

Abstract

Artificial Intelligence (AI) is profoundly reshaping the field of science communication research. We conducted a literature review of 35 articles published between 2002 and 2024, which reveals that research on AI in science communication is still in its infancy but growing, predominantly concentrated in Western contexts, and methodologically inclined toward quantitative approaches. The field largely focuses on communication about AI and public perceptions of AI rather than analyzing actual engagement with generative AI or its systemic impact on science communication ecosystems. To address these gaps, we propose a research agenda centered on four key areas: (1) communication about AI, (2) communication with AI, (3) the impact of AI on science communication ecosystems, and (4) AI’s influence on science, theoretical and methodological approaches.

Journal of Science CommunicationVol. 24(2)
Openalex Percentile: Top 1%
Big Data and Business Intelligence
13.70
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