Facial recognition and other forms of facial AI are increasingly used across policing and border control, smartphones and digital platforms, healthcare and education, and a growing range of everyday environments. In this context, facial AI refers broadly to AI-enabled systems that detect, analyse, or infer information from faces, such as identification/verification, categorisation, emotion/affect inference, attention and behaviour analytics, and other predictive or profiling applications.
This meeting brings together a diverse international group of social sciences and humanities experts–spanning STS, semiotics, art and cultural studies, policy, design, visual culture, and surveillance studies–to discuss a timely and urgent question: what is at stake when facial AI makes the face a key interface for decision-making, governance, and everyday life?
This event explores how machine vision reshapes what counts as being “seen” (and what becomes invisible); how design choices embed power and assumptions; how masks, avatars, and algorithmic “faciality” rework identity and recognition; how surveillance systems reproduce racial and gender inequalities; how computational approaches can help map public controversies; how histories and cultural narratives of AI influence what becomes thinkable or inevitable; and what “responsible” governance could look like in practice.
Guiding questions include: What does it mean to be “seen” by a machine? Who defines what is visible, measurable, and actionable? Which inequalities are amplified and under what conditions? How do surveillance systems become normalised within institutions (schools, campuses, workplaces)? What does a feminist/decolonial approach change in how risk, safety, and “user needs” are defined? What are the alternatives to facial recognition beyond a simple “ban vs allow” framing? How can artistic and creative practices help publics imagine and debate different futures?
