2019
multi-channel video installation, recipe inkjet prints, vinyl wallpaper, backlit film on backlit displays
Recipe for Disaster explores automation in technology, specifically through machine learning and recurrent neural networks, as they process and reinterpret one of humanity’s most inherent essentials, food. Employing a recurrent neural network—a form of machine learning—and a dataset of over 800 internet-sourced recipes, the project creates a video, photographic, and installation-based portrayal of five AI-generated “recipes.” Each recipe is brought to life through how-to style videos that mimic popular social media tropes and photographs of the resulting dishes, revealing disjointed creations that straddle the line between familiar consumer culture imagery and surreal outputs of machine logic. The project is displayed on an array of screens and screen-like structures, inviting viewers into a reflection on digital media consumption.
Recipe for Disaster serves as a critique of the gradual erosion of human agency within algorithmic systems, while also highlighting food as a fundamentally human experience. As machine learning models become more entwined in daily technologies, this project mirrors the ways these systems shape and distort information, culture, and behavior. The results prompt viewers to consider the limits of machine-generated predictions and question how these hidden complexities affect media literacy, visual interpretation, and cultural development.
multi-channel video installation, recipe inkjet prints, vinyl wallpaper, backlit film on backlit displays
Recipe for Disaster explores automation in technology, specifically through machine learning and recurrent neural networks, as they process and reinterpret one of humanity’s most inherent essentials, food. Employing a recurrent neural network—a form of machine learning—and a dataset of over 800 internet-sourced recipes, the project creates a video, photographic, and installation-based portrayal of five AI-generated “recipes.” Each recipe is brought to life through how-to style videos that mimic popular social media tropes and photographs of the resulting dishes, revealing disjointed creations that straddle the line between familiar consumer culture imagery and surreal outputs of machine logic. The project is displayed on an array of screens and screen-like structures, inviting viewers into a reflection on digital media consumption.
Recipe for Disaster serves as a critique of the gradual erosion of human agency within algorithmic systems, while also highlighting food as a fundamentally human experience. As machine learning models become more entwined in daily technologies, this project mirrors the ways these systems shape and distort information, culture, and behavior. The results prompt viewers to consider the limits of machine-generated predictions and question how these hidden complexities affect media literacy, visual interpretation, and cultural development.
Recipe for Disaster The Cookbook
(50 editions)
This book has been published on occassion for the exhibition Recipe for Disaster