Among the emergent data-centric practices of journalism, none appear to be as potentially disruptive as “automated journalism.” The term denotes algorithmic processes that convert data into narrative news texts with limited to no human intervention beyond the initial programming choices. The growing ability of machine-written news texts portends new possibilities for an expansive terrain of news content far exceeding the production capabilities of human journalists. A case study analysis of the pioneering automated journalism provider Narrative Science and journalists’ published reactions to its services reveals intense competition both to imagine an emergent journalism landscape in which most news content is automated and to define how this situation creates new challenges for journalists. What emerges is a technological drama over the potentials of this emerging news technology concerning issues of the future of journalistic labor, the rigid conformity of news compositional forms, and the normative foundation of journalistic authority. In these ways, this study contends with the emergent practice of automated news content creation both in how it alters the working practices of journalists and how it affects larger understandings of what journalism is and how it ought to operate.

Matt Carlson points out how algorithmic reporting may challenge journalistic authority. His paper includes an account of the formative period for Narrative Science, one of the pioneers in applications for news companies using natural language processing (NLP).


  • Matt Carlson, Department of Communication, St. Louis University.

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Carlson, M. (2015) ‘The Robotic Reporter: Automated journalism and the redefinition of labor, compositional forms, and journalistic authority,’ Digital Journalism, 3:3, 416-431, DOI: 10.1080/21670811.2014.976412