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

Abstract: 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 a

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch
• Notes: Veröffentlichungsversion ; begutachtet (peer reviewed) ; In: Media and Communication ; 8 (2020) 3 ; 39-49

Classification and Topics

• Classification: Nachrichtenmedien, Journalismus, Verlagswesen

Contributors, Places and Time

• Event: Veröffentlichung
• (where): Mannheim
• (who): SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
• (when): 2020
• Creator: Leppänen, Leo ; Tuulonen, Hanna ; Sirén-Heikel, Stefanie

Further information

• DOI: 10.17645/mac.v8i3.3022
• URN: urn:nbn:de:101:1-2021092110440107950546
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 25.03.2025, 1:50 PM CET