About
The face is broken down into measurable landmarks: eyes, nose, mouth—translated into coordinates and bounding boxes through detection, mapping, and categorisation. This reduction reveals datafication in action, where the face becomes a dataset rather than an expression. From this, a “data double” emerges, a version of the self defined by metrics. By exposing this process live, the work highlights how algorithmic identity begins with measurement, transforming personhood into machine-readable code.
Each scanned face is translated into data and archived, contributing to an expanding database that operates beyond the immediate interaction. This reflects how real-world systems like immigration records, Singpass, or Face ID, do not simply verify identity in the moment, but retain and organise this data within vast infrastructures.
Background
I positioned biometric capture as the first step of the project because it reflects how identity is increasingly established within contemporary systems—through verification before participation. This decision was sparked by everyday encounters with technologies such as immigration e-gates, Singpass, and Face ID, where access is granted only after the body has been scanned, measured, and authenticated. In these moments, identity is not something we express, but something the system extracts and confirms.
By foregrounding biometric data, the work emphasises how algorithmic identity begins with the body as raw input. The face becomes a point of entry, translated into data that allows the system to recognise, track, and process the individual. This initial act of capture sets the foundation for all subsequent interactions, framing identity as something first validated by machines before it can be performed or developed. In doing so, the project critiques how participation in digital environments is contingent on submitting to this process of measurement and conversion.