Sensual Noise (2023)

Sensual Noise is an animated series of censored AI-generated images from Stable Diffusion. Automated content moderation systems blur images deemed inappropriate, but the mechanism of determining sensitive content is often inscrutable to humans. While collecting a series of images for the prompt “Gaussian Noise” — a prompt which generates abstract images as a result (or representation) of rendering errors, I noticed that many of these images of pure noise were nonetheless flagged as containing sensitive content.

Collecting these images, and further prompting the model with “Gaussian Noise, Human Sensuality,” created a new dataset of censored abstract images. Sensitive Noise compiles these images into a silent video work, with each frame interpolated into the next. It is clear that these images represent nothing (though some suggest more than others) — nonetheless, they are “suggestive” to the machine. The knowledge that these contain forbidden scenes of human sensuality prompts the viewer into seeking the sensual element of these images. Perhaps in series, they become suggestive: the colors, contours and shapes form a collective visualization of data connected to prompts for sensuality in LAION, the text-image pairing model behind Stable Diffusion. Perhaps they are suggestive simply because we aim to see them through the eyes of the content moderation systems’ categorization.

Sensual Noise is part of a series of AI generated artworks in which I attempt to work with “Artificial Impossibility.” These are pictures that contemporary AI image generation tools cannot create, either because of technical constraints (such as rendering errors, i.e., human hands or Gaussian noise), content moderation (blurred images), absences in the dataset, or the conceptual limitations of visualization itself.

Notably, many of these impossible images relate to renderings of human experiences: the realm of senses beyond the visual, especially touch, explores the lack of embodied experience within “artificial intelligence” systems.