Tow Center Guide to Automated Journalism

Executive Summary

In recent years, the use of algorithms to automatically generate news from structured data has shaken up the journalism industry—most especially since the Associated Press, one of the world’s largest and most well-established news organizations, has started to automate the production of its quarterly corporate earnings reports. Once developed, not only can algorithms create thousands of news stories for a particular topic, they also do it more quickly, cheaply, and potentially with fewer errors than any human journalist. Unsurprisingly, then, this development has fueled journalists’ fears that automated content production will eventually eliminate newsroom jobs, while at the same time scholars and practitioners see the technology’s potential to improve news quality. This guide summarizes recent research on the topic and thereby provides an overview of the current state of automated journalism, discusses key questions and potential implications of its adoption, and suggests avenues for future research. Some of the key points can be summarized as follows.

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The Robotic Reporter: Automated journalism and the redefinition of labor, compositional forms, and journalistic authority

Carlson, M. (2015) The Robotic Reporter. Digital Journalism. Vol. 3 , Iss. 3,2015


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.

Jane Smith: Robot journalism

Imagine a news story written and published within three minutes of the event happening. That’s a real scenario described by Emily Bell in her T P Stead Lecture at the British Library last week. I was intrigued by her title “Robot reporters” and went to hear more about “Journalism in the Age of Automation and Big Data.” Bell, who formerly ran Guardian Unlimited and is now director of the Tow Center for Digital Journalism at the University of Columbia in New York, was arguing that journalists need to know about the technologies that help create and distribute their stories. These days that means they need to work alongside software programmers and engineers and understand the algorithms that underlie services that mine big databases and expose news stories—like Google News. In particular, they need to know the biases of the algorithms—because they will have some—and that it is much harder to find out about these than it is with human informants and writers, particularly if the code is commercially confidential—as it is with the Googles and Facebooks of the world.

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