Editorial | Open Access
Exploring the Impact of Generative AI on Public Engagement and Information Dynamics
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Abstract: The rapid diffusion of generative AI is transforming the conditions under which public communication and knowledge production take place. As prompt-based systems increasingly operate as communicative actors that generate, translate, and contextualize information, they reconfigure established processes of mediation, the distribution of epistemic authority, and the infrastructures of the public sphere. This editorial situates the thematic issue within communication research on public understanding of science, digital intermediaries, and trust and credibility, and proposes to conceptualize generative AI as a general-purpose technology embedded in evolving knowledge infrastructures. From this perspective, generative AI enables the delegation of core epistemic practices—such as information retrieval, relevance evaluation, and interpretation—to automated systems, thereby reshaping how publics engage with complex and socially consequential knowledge. The contributions to the issue are organized along three analytical dimensions: the socio-cognitive and affective drivers of generative AI use in everyday information practices; the epistemic and cognitive consequences of AI-mediated engagement with complex information; and the transformation of communicative institutions, professional authority, and opinion formation in AI-mediated public discourse. Across diverse theoretical approaches and empirical contexts, the issue advances a multi-level understanding of how generative AI reconfigures relationships between individuals, institutions, and publics. Taken together, the articles position generative AI as a central site for renegotiating expertise, trust, and participation in digital knowledge societies and highlight the need for integrative and comparative research to enable cumulative theorizing about communication under conditions of AI-mediated mediation of complex information.
Keywords: AI; complex information; critical thinking; generative AI; knowledge infrastructures; public engagement
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© Monika Taddicken, Esther Greussing, Evelyn Jonas, Ayelet Baram-Tsabari, Inbal Klein-Avraham. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.