Deep Learning the Climate Emergency, screened on the digital facade of Federation Square, Melbourne, Australia

Deep Learning the Climate Emergency uses photography and machine learning to (re)generate the aesthetic patterning of ecological collapse. For this work, I was interested to see if familiar images of the climate emergency, ones that have perhaps lost their potency through repetition, could be reconfigured into a new affective experience. The moving image artwork was made with generative adversarial networks (GANs) trained on image-based datasets depicting the effects of a heating planet: wildfire, bleached coral, drought, melting glaciers, and suns through smoke-filled skies. Refracted through the prism of machine learning, the video is a rendering of the shapes and textures of the climate emergency.