video, 2024

Cycles shows the body in defiance of philosophies and technologies that insist it be a clear, stable, isolated thing. Contemporary surveillance technology tracks our faces, bodies, and attention, singling us out for automated manipulation and control. In contrast, Cycles resists that totalizing gaze through playful misuses of tools that track and predict the body.

These chaotic bodies are the result of a multi-layered process of technological translation, misusing and coercing various body-tracking devices into mesmerizing dysfunction. First, face-detecting augmented reality applications are used on a collection of the artist’s own selfies, face-swapping and rephotographing these images on screens. Then, a custom machine learning model is trained on these distorted faces such that it can produce new faces based on this influence. Another custom ML model is trained to interpret input body images to be constructed out of the faces from the first model. The artist records motion-capture data from a duet performance of herself with a dummy ragdoll and uses this data to animate digital avatars, which then are processed by the ML models.