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Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens

  • Nicholas DiakopoulosEmail author
Chapter
First Online:
Part of the Studies in Big Data book series (SBD, volume 32)

Abstract

As the news media adopts opaque algorithmic components into the production of news information it raises the question of how to maintain an accountable media system. One practical mechanism that can help expose the journalistic process, algorithmic or otherwise, is transparency. Algorithmic transparency can help to enable media accountability but is in its infancy and must be studied to understand how it can be employed in a productive and meaningful way in light of concerns over user experience, costs, manipulation, and privacy or legal issues. This chapter explores the application of an algorithmic transparency model that enumerates a range of possible information to disclose about algorithms in use in the news media. It applies this model as both a constructive tool, for guiding transparency around a news bot, and as a critical tool for questioning and evaluating the disclosures around a computational news product and a journalistic investigation involving statistical inferences. These case studies demonstrate the utility of the transparency model but also expose areas for future research.

Keywords

Information Disclosure News Article Transparency Information Editorial Decision Transparency Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

CAR

Computer-assisted reporting

NPR

National Public Radio

RTDNA

Radio Television Digital News Association

SPJ

Society for Professional Journalists

SRF

Schweizer Radio und Fernsehen

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Philip Merrill College of Journalism, University of MarylandCollege ParkUSA

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