Abstract
The availability of data feeds, the demand for news on digital devices, and advances in algorithms are helping to make automated journalism more prevalent. This article extends the literature on the subject by analysing professional journalists’ experiences with, and opinions about, the technology. Uniquely, the participants were drawn from a range of news organizations—including the BBC, CNN, and Thomson Reuters—and had first-hand experience working with robo-writing software provided by one of the leading technology suppliers. The results reveal journalists’ judgements on the limitations of automation, including the nature of its sources and the sensitivity of its “nose for news”. Nonetheless, journalists believe that automated journalism will become more common, increasing the depth, breadth, specificity, and immediacy of information available. While some news organizations and consumers may benefit, such changes raise ethical and societal issues and, counter-intuitively perhaps, may increase the need for skills—news judgement, curiosity, and scepticism—that human journalists embody.
Item Type: | Journal article |
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Keywords: | algorithmic journalism, automated journalism, computational journalism, journalism ethics, media economics, news production, professional skills, robot journalism |
Faculties: | Social Sciences > Department of Communications and Media (IfKW) |
Subjects: | 000 Computer science, information and general works > 000 Computer science, knowledge, and systems 000 Computer science, information and general works > 004 Data processing computer science 000 Computer science, information and general works > 070 News media, journalism and publishing 300 Social sciences > 300 Social sciences, sociology and anthropology 300 Social sciences > 330 Economics 300 Social sciences > 380 Commerce, communications and transportation 600 Technology > 600 Technology 800 Literature > 800 Literature, rhetoric and criticism |
URN: | urn:nbn:de:bvb:19-epub-39177-1 |
ISSN: | 2167-0811 |
Language: | English |
Item ID: | 39177 |
Date Deposited: | 21. Jun 2017 06:08 |
Last Modified: | 15. Dec 2020 09:28 |