This article explores the new modalities of visibility engendered by new media, with a focus on the social networking site Facebook. Influenced by Foucault’s writings on Panopticism – that is, the architectural structuring of visibility – this article argues for understanding the construction of visibility on Facebook through an architectural framework that pays particular attention to underlying software processes and algorithmic power. Through an analysis of EdgeRank, the algorithm structuring the flow of information and communication on Facebook’s ‘News Feed’, I argue that the regime of visibility constructed imposes a perceived ‘threat of invisibility’ on the part of the participatory subject. As a result, I reverse Foucault’s notion of surveillance as a form of permanent visibility, arguing that participatory subjectivity is not constituted through the imposed threat of an all-seeing vision machine, but by the constant possibility of disappearing and becoming obsolete.
Algorithms are an increasingly important element of internet infrastructure in that they are used to make decisions about everything from mundane music recommendations through to more profound and oftentimes life changing ones such as policing, health care or social benefits. Given algorithmic systems' impact and sometimes harm on people's everyday life, information access and agency, awareness of algorithms has the potential to be a critical issue. We, therefore, ask whether having awareness of algorithms or not corresponds to a new reinforced digital divide. This study examines levels of awareness and attitudes toward algorithms across the population of the highly digitized country of Norway. Our exploratory research finds clear demographic differences regarding levels of algorithms awareness. Furthermore, attitudes to algorithm driven recommendations (e.g., YouTube and Spotify), advertisements and content (e.g., personalized news feeds in social media and online newspaper) are associated with both the level of algorithm awareness and demographic variables. A cluster analysis facilitates an algorithm awareness typology of six groups: the unaware, the uncertain, the affirmative, the neutral, the sceptic and the critical.
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