Reinterpreted Spaces An AI-Printmaking Collaboration

We present an examination of organic spaces through print, book making, data, and machine learning. Artists created a book that explored the idea of organic and machine-made interpretations of a place that were generate using 3 different processes: a generative adversarial network, traditional printmaking and a camera. The artists found the results unexpected, discussing how the AI-generated image changed and complicated their understanding and constructed narrative about the original image and space. This caused them to think outside the box with over half of the students changing their print matrix and/or ink choices after seeing their AI-generated image. This supported the learning objective for students to collaborate with technology that is uninhibited by perspective or expectation, adapting and responding productively and creatively within a new framework. With the newfound accessibility to AI-generated images we encourage art teachers to explore how it fits into their curriculum.