Exploring Communicative AI: Reflections from a Swedish Newsroom
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| Název: | Exploring Communicative AI: Reflections from a Swedish Newsroom |
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| Autoři: | Stenbom, Agnes, Wiggberg, Mattias, Norlund, Tobias, 1991 |
| Zdroj: | Digital Journalism. 11(9):1622-1640 |
| Témata: | machine learning, search engine optimization, human-machine communication, communicative AI, natural language generation, Computational journalism |
| Popis: | This article contributes to the emerging field of research on computational journalism with a practical illustration of an attempt to utilize Machine Learning to generate Search Engine Optimized headlines in a major Swedish newsroom. By using its technical results as a springboard for reflections among internal stakeholders, the experiment serves as a catalyzing innovation revealing deliberations on computational approaches in journalism in general and communicative Artificial Intelligence (AI) in specific. The study concludes with three ideas to support decision makers involved in evaluating potential use cases for communicative AI in journalism. |
| Popis souboru: | electronic |
| Přístupová URL adresa: | https://research.chalmers.se/publication/527692 https://research.chalmers.se/publication/527692/file/527692_Fulltext.pdf |
| Databáze: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | This article contributes to the emerging field of research on computational journalism with a practical illustration of an attempt to utilize Machine Learning to generate Search Engine Optimized headlines in a major Swedish newsroom. By using its technical results as a springboard for reflections among internal stakeholders, the experiment serves as a catalyzing innovation revealing deliberations on computational approaches in journalism in general and communicative Artificial Intelligence (AI) in specific. The study concludes with three ideas to support decision makers involved in evaluating potential use cases for communicative AI in journalism. |
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| ISSN: | 21670811 2167082X |
| DOI: | 10.1080/21670811.2021.2007781 |