Restructuring Epistemic Spaces: The Rise of AI-Integrated Media Creative Ecosystems
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Tran Minh Duc*
Generative Artificial Intelligence (Generative AI) is fundamentally reshaping media workflows by restructuring creative processes and the institutional conditions of knowledge production. While current research has deeply analyzed AI through the lenses of automation, algorithmic governance, and professional ethics, the transformative dimension of academic knowledge construction remains under-explored. This paper argues that the traditional boundaries between academic knowledge production at universities and practical application in businesses are increasingly blurred in the AI era. Instead, modern media knowledge is co-constructed through continuous interactions among universities, technology firms, newsrooms, regulatory bodies, and intelligent AI systems. The study establishes an analytical framework termed the Distributed Epistemic Ecology (DEE), integrating major theories: Practice Theory, Mode 2 Knowledge Production, Experiential Learning, Sociomateriality, and Science and Technology Studies (STS). This theoretical framework is empirically validated through a qualitative case study of the reality television program AI in Action in Vietnam. The findings demonstrate that generative AI redistributes epistemic authority, transforming direct creative practices into spaces for theoretical inquiry and recursive learning. This study contributes a novel theoretical perspective to Media Studies, STS, and Higher Education in the context of comprehensive digital transformation.
Bourdieu, P. (1990). The Logic of Practice. Stanford University Press.
Epstein, Z., Hertzmann, A., Akten, M., Farid, H., Fjeld, J., Frank, M. R., Groh, M., Herman, L., Leach, N., Mahari, R., Pentland, A. “Sandy,” Russakovsky, O., Schroeder, H., & Smith, A. (2023). Art and the science of generative AI. Science, 380(6650), 1110–1111. https://doi.org/10.1126/science.adh4451
Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (2010). The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies. SAGE Publications Ltd. https://doi.org/10.4135/9781446221853
Jasanoff, S. (2004). States of Knowledge: The Co-production of Science and the Social Order. Routledge.
Jose, B., Cleetus, A., Joseph, B., Joseph, L., Jose, B., & John, A. K. (2025). Epistemic authority and generative AI in learning spaces: rethinking knowledge in the algorithmic age. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1647687
Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Prentice-Hall.
Lewis, S. C., Guzman, A. L., Schmidt, T. R., & Lin, B. (2025). Generative AI and its disruptive challenge to journalism: an institutional analysis. Communication and Change, 1(1), 9. https://doi.org/10.1007/s44382-025-00008-x
Munoriyarwa, A., & De-Lima-Santos, M.-F. (2025). Generative AI and the Future of News: Examining AI’s Agency, Power, and Authority. Journalism Practice, 19(10), 2177–2188. https://doi.org/10.1080/17512786.2025.2545448
Orlikowski, W. J. (2007). Sociomaterial Practices: Exploring Technology at Work. Organization Studies, 28(9), 1435–1448. https://doi.org/10.1177/0170840607081138
Peña-Fernández, S., Meso-Ayerdi, K., Larrondo-Ureta, A., & Díaz-Noci, J. (2023). Without journalists, there is no journalism: the social dimension of generative artificial intelligence in the media. El Profesional de La Información. https://doi.org/10.3145/epi.2023.mar.27
Sahebi, S., & Formosa, P. (2025). The AI-mediated communication dilemma: epistemic trust, social media, and the challenge of generative artificial intelligence. Synthese, 205(3), 128. https://doi.org/10.1007/s11229-025-04963-2
Schatzki, T. R. (2002). The Site of the Social. Penn State University Press. https://doi.org/10.1515/9780271023717
Timmermans, S., & Tavory, I. (2012). Theory Construction in Qualitative Research. Sociological Theory, 30(3), 167–186. https://doi.org/10.1177/0735275112457914
