The Normalizing Machine is an interactive installation presented as an experimental research in machine-learning. It aims to identify and analyze the image of social normalcy. Each participant is asked to point out who looks most normal from a line up of previously recorded participants. The machine analyzes the participant decisions and adds them to its’ aggregated algorithmic image of normalcy.
Two scientists whose fingerprints are plastered all over contemporary culture inform the work. In the late 1800s the French forensics pioneer Alphonse Bertillon, the father of the mugshot, developed “Le Portrait Parle” (the speaking portrait) a system for standardizing, indexing and categorizing the human face. His statistical system was never meant to criminalize the face but it was later widely adopted by both the Eugenics movement and by the Nazis to do exactly that.
Half a century later, British Mathematician, Alan Turing laid the foundation to computing and artificial intelligence. Turing was concerned about the fate of a child-machine, singled out among the other normal children. Despite being one of the unsung heroes of WW2 who cracked the Nazi Enigma code, in the early 50’s he was convicted of homosexuality, was chemically castrated and later took his own life. Turing hoped AI would transcend the kind of systemic bias that criminalized his own deviation from the norms.
The installation visualizes how machine learning automates and amplifies Bertillon’s speaking portraits. As today’s systematic discrimination is aggregated and conveniently hidden behind a seemingly objective black box.
while logically second,
is existentially first.
Georges Canguilhem, The Normal and the Pathological, 1966.
Additionally, watch the video documentation from an early edition of the work titled The Turing Normalizing Machine (2012)
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