Unlearning Gender

Computer vision. With Jelena Mönch.

Exhibited in Ars Electronica Festival 2023: Who owns the truth? & Quantified Perspectives: Rethinking Data Narratives - University of Luxembourg

2023

Words build reality. The machines of vision deployed in our contemporary encapsulate, label and categorise bodies through words. Which bodies are being recognised and which are not in the algorithmic eyes? The vision machines deployed in our contemporaneity encapsulate, labels and categorises bodies through words. Which bodies are being recognised and which are not being recognised from algorithmic eyes? Machine vision classifies bodies that fit into a binary worldview of gender, and those subjectivities that are not able to conform become invisible to its schemas .

<

[Un]learning Gender is a project that speculates with alternative modes of categorisation as a strategy of resistance to algorithmic-binary standardisation. Through the symbolic hacking of the computer vision interface, the project aims to escape gender and break away from project aims to escape gender and break with the technosocial binarisms embedded in technology. in technology. With this algorithmic essay we have developed small micro-actions that disrupt this characteristic and defined visuality. Because words shape realities. Our strategy was to create, from the edge, "many divergent, even antagonistic, descriptions of the world and the divergent, even antagonistic, descriptions of the world and the people who inhabit it" in order to ward off the temptation to fix "imposed temptations to fix "imposed consensual realities".

How can the aesthetics of neutrality embedded in computer vision be dismantled?