Regimes of recognition on algorithmic media

This article examines ways in which people are seen, recognised, and made to matter by social media platforms. Drawing on Louise Amoore’s notion of ‘regimes of recognition’, I argue that social media platforms can be conceptualised as increasingly powerful arbiters of recognisability, determining the conditions of possibility of how people are seen and come to matter. Through an analysis of Twitter’s saliency detection algorithm, which automatically crops images uploaded to the platform, the article highlights how social media platforms participate in producing novel modes of recognisability, that is, conditions by which people are rendered visible and invisible within or by the platform. Moreover, the article highlights how regimes of recognition on algorithmic media shape people’s parameters of attention and perception more generally through what I call the automatic production of ‘consistent’ lines of sight. Ultimately, the article seeks to highlight how the notion of recognition is increasingly arbitrated in and through algorithmic media and how this is fraught with political issues and tension. As such, there is an ongoing need to critically examine the power of social media to render people visible and invisible.