Abstract
Analysing how news media portray A.I. reveals what interpretative frameworks around the technology circulate in public discourses. This allows for critical reflections on the making of meaning in prevalent narratives about A.I. and its impact. While research on the public perception of datafication and automation is growing, only a few studies investigate news framing practices. The present study connects to this nascent research area by charting A.I. news frames in four interna- tionally renowned media outlets: The New York Times, The Guardian, Wired, and Gizmodo. The main goals are to identify dominant emphasis frames in AI news reporting over the past decade, to explore whether certain A.I. frames are associated with specific data risks (surveillance, data bias, cyber-war/cyber-crime, and information disorder), and what journalists and experts contribute to the media discourse. An automated content analysis serves for inductive frame detection (N = 3098), identification of risk references (dictionary-based), and network analysis of news writers. The results show how A.I.’s ubiq- uity emerged rapidly in the mid-2010s, and that the news discourse became more critical over time. It is further argued that A.I. news reporting is an important factor in building critical data literacy among lay audiences.
Original language | English |
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Pages (from-to) | 437–451 |
Number of pages | 15 |
Journal | AI and Society |
Volume | 39 |
Issue number | 2 |
Early online date | 23 Jun 2022 |
DOIs | |
Publication status | Published - 2024 |
Bibliographical note
Funding Information:This study was partially funded by the Dutch Research Council (NWO).
Publisher Copyright:
© 2022, The Author(s).
Keywords
- Artificial intelligence
- Automated content analysis
- Data literacy
- Data risk
- News framing