Deep Learning the Climate Emergency
2022 | GAN-generated moving image with audio, 07:35
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.
Deep Learning the Climate Emergency, video preview