ABSTRACT
This chapter considers the face as data by way of four contemporary cases that express some of the desires, anxieties, challenges, and politics we face when conceptualizing face as data. It begins with British artist Gillian Wearing’s recent “deepfake” video exhibition, in which she mapped her face to a series of random bodies (Beer, 2018), where special attention is paid to Goffman’s arguments regarding “face-work” as the social glue to which personal trust and political order adheres. Continuing the thread of face as social image and artistic currency, the second case this chapter explores involves Google Art: a wildly popular phone application that compares selfies uploaded by users to museum portraits in Google Art’s database (Held, 2018). Here, the chapter considers how Google Art encourages users to circulate face-data as cultural and social capital, extending Goffman’s thoughts on face-work to include “immaterial labor” on the internet. The third and fourth cases explored in this chapter explore how notions of face-as-data affect and apply to individuals living with the neurological condition of Autism. This section begins with a project at Duke University that purports to diagnose Autism in children by showing them videos on a smartphone and recording their facial reactions (Bates, 2018). It then moves to consider a series of phone apps designed to teach facial recognition: a skill that many members of Autistic community reporting finding difficult or impossible. The chapter ends by exploring the possible value of considering the face as both a unique and singular entity tied to the self, and substitutable and communal set of data in the service of what Jodi Dean terms “selfie communism.”
