Advancing a Material and Epistemological Turn in the Study of AI: A Review and New Directions for Journalism Research

This paper explores how the journalistic scholarship on Artificial Intelligence (AI) has developed over the last decade by providing a qualitative review of the empirical work on AI in journalism, drawing on Anderson’s sociological approaches to the study of computational and algorithmic journalism. While the review shows that the existing six lenses developed based on the sociology of news production have proven helpful in addressing AI as an object of study in journalism, the paper argues that this framework is no longer sufficient to address all the facets of AI. The paper, therefore, advances a material and epistemological turn in the study of AI. This turn is concretised through three analytical sensitivities inspired by the field of Critical AI Studies (CAIS) that aim to augment the existing approaches outlined by Anderson. These sensitivities include (1) attending to the “technical” in socio-technical, (2) studying the methodologies and histories of AI, and (3) unfolding the wider eco-system of AI. The paper concludes with new directions for future research aimed at tackling political, economic, institutional, organisational, cultural, and technological aspects of AI in journalism and future developments in AI, such as Generative AI.