Abstract
The integration of Generative AI into journalistic production represents a critical juncture in the evolution of contemporary media systems. This study, situated at the intersection of digital media studies and the sociology of technology, interrogates Generative AI from the perspective of Actor-Network Theory, inspecting how Generative AI has inserted itself as the new ICT and is quickly moving to achieve the Obligatory Passage Point status as an actant in the media production networks. Currently through with the first phase of data collection, this research employs a mixed-methods approach that combines an experimental design with survey research and qualitative expert interviews. Interviews with media practitioners and journalists provide insight into institutional logics, professional anxieties, and industry framings of technological change. While the second half of the research dealing with audience perception evaluates media texts for credibility, bias, quality, and trust, all achieved through a double blind survey set as an online experiment, capturing broader attitudes toward AI in journalism. This project fills a significant gap in current scholarship by bridging audience reception studies with critical perspectives on algorithmic media and technological mediation. The primary results reveal how much AI has been integrated in workflows and in the network of media production and dissemination. Empirically, by integrating both public and expert voices, the study foregrounds the uneven and fear mongering nature of information surrounding AI use. Theoretically, the research contributes to debates in the sociology of technology by examining AI as a socio-technical actor that has altered institutional practices and audience relations.
Details
Presentation Type
Theme
KEYWORDS
GENERATIVE AI, JOURNALISM, ACTOR NETWORK THEORY, MEDIA SOCIOLOGY, HMC, ICT
