How news media frame data risks in their coverage of big data and AI

Abstract

Public discourses have become sensitive to the ethical challenges of big data and artificial intelligence, as scandals about privacy invasion, algorithmic discrimination, and manipulation in digital platforms repeatedly make news headlines. However, it remains largely unexplored how exactly these complex issues are presented to lay audiences and to what extent news reporting-as a window to tech debates-can instil critical data literacy. The present study addresses this research gap and introduces the concept of "data risks". The main goal is to critically investigate how societal and individual harms of data-driven technology find their way into the public sphere and are discussed there. The empirical part applies a mixed methods design that combines qualitative and automated content analyses for charting data risks in news reporting sampled from prominent English-speaking media outlets of global reach. The resulting inventory of data risks includes privacy invasion/surveillance, data bias/algorithmic discrimination, cybersecurity, and information disorder. The study posits data risks as communication challenges, highlights shortcomings in public discussions about the issue, and provides stimuli for (practical) interventions that aim at elucidating how datafication and automation can have harmful effects on citizens.