Filter by author: Evelyn Jonas

All author's publications are listed below.

3 publications found

Apr 14, 2025 Article

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

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

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.

Volume 24 • Issue 2 • 2025 • Science Communication in the Age of Artificial Intelligence (Science Communication & AI)

Dec 16, 2024 Article

Intermediaries in the limelight: how exposure to trust cues in content about science affects public trust in science

by Lars Guenther, Justin T. Schröder, Anne Reif, Janise Brück, Monika Taddicken, Peter Weingart and Evelyn Jonas

A potential decline in public trust in science has often been linked to digital media environments, which serve as intermediaries of trust by providing cues for why (not) to trust science. This study examines whether exposure to trust cues in content affects public trust in science (across population groups). The study employs a mixed-method design, combining content analysis (“n” = 906) and panel survey data (“n” = 1,030) in Germany. The findings reveal that exposure to trust cues in certain media predicts public trust in science. Variations across trust groups indicate a nuanced nature of trust-assessing processes in digital media environments.

Volume 23 • Issue 09 • 2024 • Special Issue: Public (dis)trust in science in digital media environments

Oct 09, 2024 Article

How to make sense of generative AI as a science communication researcher? A conceptual framework in the context of critical engagement with scientific information

by Inbal Klein-Avraham, Esther Greussing, Monika Taddicken, Shakked Dabran-Zivan, Evelyn Jonas and Ayelet Baram-Tsabari

A guiding theory for a continuous and cohesive discussion regarding generative artificial intelligence (GenAI) in science communication is still unavailable. Here, we propose a framework for characterizing, evaluating, and comparing AI-based information technologies in the context of critical engagement with scientific information in online environments. Hierarchically constructed, the framework observes technological properties, user experience, content presentation, and the context in which the technology is being used. Understandable and applicable for non-experts in AI systems, the framework affords a holistic yet practical assessment of various AI-based information technologies, providing both a reflection aid and a conceptual baseline for scholarly references.

Volume 23 • Issue 06 • 2024