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Abstract
This case study takes a brief look at commercial operations with automated news in the United States as well as five European countries to explore how the logic of journalism has been interpreted and translated into software and how industry experts anticipate the future. The empirical material consists of 31 qualitative research interviews with data journalists, news managers, computer scientists, academics and industry experts that inhabit and reproduce this new ecosystem of computation, journalism and statistics. Theoretically the study is inspired by a social constructionist perspective, arguing that social action is a central element in technological development: there are many forms of friction that creates barriers to increased automation. It would be naive to think that the development of learning algorithms will not lead to more advanced forms of automated news, however, journalists have shown a strong capacity for adaptation and mitigation of new technology. The paper turns the usual discussion about job losses on its head and asks “Why are there still so many jobs in journalism after decades of newsroom automation?” We argue that journalism as ideology, understanding how journalists give meaning to their work, probably will be a strong mitigating effect also in the future.