Abstract
Background:This article provides a comprehensive picture of automated news’ usage—understood here as the auto-generation of journalistic text through software and algorithms, with no human intervention in-between except for the initial programming at 18 news organisations in Europe, North America and Australia, following a strategic sample inspired by Hallin and Mancini’s (2004) media system typology.Methods:To describe the many ways it is implemented, I rely on Actor-network theory (ANT) so as to distinguish situations where somethingmoreis added to automated news systems from those where initial intent is kept and where the software does what it is supposed to do. Semi-structured interviews with editorial staff, executives and technologists were conducted remotely and elements of a netnography were also carried out.Results:Overall, my findings show that the main transformations—ortranslations—of automated news systems deal with alternate data sources (e.g., news organisations’ internal feeds, crowdsourced material), new affordances that are specifically built for journalists (e.g., in-house self-editing tools, notification streams) and output other than text (e.g., automated audio summaries for voice assistants). Conclusions: Although these changes lead to greater journalistic professionalisation, they could also make news organisations become too dependent on Big Tech companies for data acquisition and dissemination of automated news products, thus making platforms gain the upper hand in future developments of these systems.
Funder
Horizon 2020 Framework Programme