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Gohan Keller 2020

In a recent ad, Apple stresses that "Face ID only stores a mathematical representation of your face on iPhone, not a photo", a claim which interestingly reflects upon the increasing role of 3D imagery within the photographic field. The 3D model is marketed as the more secure identification system – it has yet to be established, if it is more efficient than a fingerprint scan – , yet the company also stresses that the photograph of your face, the intimate token of your identity, has not been used, thus reassuring about privacy issues. Gohan Keller’s project interestingly plays with these two representational systems, between mathematical model and photography, between identification and identity. It makes visible the infra-red light projected by the phone on the face in order to compare the 3D model with the recorded equivalent. But what Gohan shows is the combination of these two, photographed bodies appearing under green dots, correlating the datafication of the body with its photographic image. Photographic portraits have been used in the past, because they supposedly unveiled the character of an individual. Francis Galton’s composite portraits or Cesare Lombroso’s research sought to determine an individual’s traits, identifying the criminal, the prostitute, the poor or the madmen though the interpretation of their face alone. Mathematical representations seem, at a first glance, void of such political implications. But the datafication of the body and its potential uses (surveillance capitalism, coercive police or state use, social credit systems, etc.), with the numerous biases they entail (especially false positive match of minorities, segregation, etc.), calls for a critical inquiry of what Safiya Noble calls (in the context of search engines) algorithms of oppression.

Text by Claus Gunti

Safiya Noble, Algorithms of Oppression, New York, New York University Press, 2018 

Kate Crawford and Trevor Paglen, Training Humans (Quaderno #26), Milan, Fondazione Prada, 2019