Automated Journalism as a Source of and a Diagnostic Device for Bias in Reporting

In this article we consider automated journalism from the perspective of bias in news text. We describe how systems for automated journalism could be biased in terms of both the information content and the lexical choices in the text, and what mechanisms allow human biases to affect automated journalism even if the data the system operates on is considered neutral. Hence, we sketch out three distinct scenarios differentiated by the technical transparency of the systems and the level of cooperation of the system operator, affecting the choice of methods for investigating bias. We identify methods for diagnostics in each of the scenarios and note that one of the scenarios is largely identical to investigating bias in non-automatically produced texts. As a solution to this last scenario, we suggest the construction of a simple news generation system, which could enable a type of analysis-by-proxy. Instead of analyzing the system, to which the access is limited, one would generate an approximation of the system which can be accessed and analyzed freely. If successful, this method could also be applied to analysis of human-written texts. This would make automated journalism not only a target of bias diagnostics, but also a diagnostic device for identifying bias in human-written news.Peer reviewe

At the crossroads of logics: Automating newswork with artificial intelligence : (Re)defining journalistic logics from the perspective of technologists

As artificial intelligence (AI) technologies become more ubiquitous for streamlining and optimizing work, they are entering fields representing organizational logics at odds with the efficiency logic of automation. One such field is journalism, an industry defined by a logic enacted through professional norms, practices, and values. This paper examines the experience of technologists developing and employing natural language generation (NLG) in news organizations, looking at how they situate themselves and their technology in relation to newswork. Drawing on institutional logics, a theoretical framework from organizational theory, we show how technologists shape their logic for building these emerging technologies based on a theory of rationalizing news organizations, a frame of optimizing newswork, and a narrative of news organizations misinterpreting the technology. Our interviews reveal technologists mitigating tensions with journalistic logic and newswork by labeling stories generated by their systems as nonjournalistic content, seeing their technology as a solution for improving journalism, enabling newswork to move away from routine tasks. We also find that as technologists interact with news organizations, they assimilate elements from journalistic logic beneficial for benchmarking their technology for more lucrative industries.Peer reviewe

Unboxing news automation : Exploring imagined affordances of automation in news journalism

News automation is an emerging field within journalism, with the potential to transform newswork. Increasing access to data, combined with developing technology, will allow further inquiries into automated journalism. Producing news text using NLG (natural language generation) is currently largely undertaken in specific, predictable news domains, such as sports or finance. This interdisciplinary study investigates how elite media representatives from Finland, Europe and the US imagine the affordances of this emerging technology for their organization. Our analysis shows how the affordances of news automation are imagined as providing efficiency, increasing output and aiding in reallocating resources to pursue quality journalism. The affordances are, however, constrained by such factors as access to structured data, the quality of automation and a lack of relevant skills. In its current form, automated text generation is seen as providing only limited benefits to news organizations that are already imagining further possibilities of automation.Peer reviewe

News Automation : The rewards, risks and realities of 'machine journalism'

nonPeerReviewe