Abstract
The face has long been functions as an index of identity, a surface on to which regimes of race, gender and class are inscribed. Building on Levinas’s ethics of the face and Deleuze & Guattari’s concept of the faciality machine, this paper reconceptualises the digital facial image not as a representation but as an operative site where power acts, affects circulate, and subjectivities are modulated. Historically, physiognomy, and biometric photography reduced faces to legible data, reinforcing colonial and racial hierarchies. Contemporary machine-vision systems recode these biases in algorithmic form. Adopting a practice-based methodology, this research develops creative strategies to disrupt the faciality machine. By engaging with generative AI, particularly the diffusion models, this research explores alternative modes of seeing that prioritise sensation over representation, offering new possibilities for ethical and affective engagements with the digital face to articulate what constitutes an ‘ethical face image’ in the era of AI-generated image. By shifting focus from recognition to sensation, and from documentation to emergence, this research rethinks the politics of the digital face image and its implications for contemporary subjectivity.
Presenters
Yazan NasrallahStudent, PhD Media, Communications and Cultural Studies, Goldsmiths, University of London, London, City of, United Kingdom
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Philosophy, Creative, Technology, Identity, Digital, Face, Image, AI, Aesthetics
