Freezing out: Legacy media's shaping of AI as a cold controversy

BIG DATA & SOCIETY(2023)

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Abstract
Mainstream coverage of artificial intelligence often appears to emphasise the technologies' benefit and economic potential over its growing downsides. How does a technology poised to be so disruptive become so uncritically embraced? Why is it, simply put, that artificial intelligence's representations in legacy media do not normally convey the controversialities otherwise found in research or policy debates? We introduce the concept of 'freezing out' to describe processes of translation that cool down debates over the merits of technology. Freezing out looks at the other side of controversy studies to study the production of uncontroversies or cold controversies rather than hot topics and debates. We use the coverage of artificial intelligence in Canadian national news outlets to analyse how controversiality becomes 'frozen out'. Since Canadian academics won the prestigious ImageNet prize in 2012 introducing the modern turn toward machine learning approaches, Canada has promoted itself as a global leader. Using in-depth interviews with Francophone and Anglophone journalists as well as topic modelling on data collected from five major newspapers, we find that routine news making processes between journalists, experts, entrepreneurs, and governments build, maintain, and promote Canada's artificial intelligence ecosystem. Freezing out contributes to a broader interest in how heterogeneous actors traverse their domain of expertise across policy, media, and research circles to cool down artificial intelligence controversies.
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Key words
AI,media,translation,controversy,journalism,political economy,STS,techno-entrepreneurialism
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