By generating »technoheritage,« Al-Badri expands on speculative archaeology and decolonial as well as machine learning-based museum practices. A pretrained neural network based on GAN technology (General Adversarial Networks) was trained with 10,000 images from five different museum collections with the largest collections of Mesopotamian, Neo-Sumerian, and Assyrian artefacts. The images were primarily collected through web crawling and scraping, without the institutions’ approval (even though she asked each museum for permission) and just two through their open API. New synthetic images subsequently evolve as a living memory of the images. The generated image is at the same time the artifact itself. Yet materiality is very important, since the input images are images of material objects of our past. If MI is seen as a technology performing and processing our collective memory it makes sense to apply it to the past's cultural big data and generate new images as traces and circulating image worlds. Applying MI to cultural big data supplies other, more speculative and abstract insights on the search for a visual language, form, and pattern of an era within the specific Babylonian spatial context. The input images of these databases carry time and memory themselves (patina, broken pieces, most of them mid- to low-res). The series consists of more than 150 videos.

Al-Badri is a multidisciplinary and conceptual media artist with a German-Iraqi background. Her works are research-based as well as paradisciplinary and as much postcolonial as postdigital. She lives and works in Berlin. She graduated in political science from the Johann Wolfgang Goethe University in Frankfurt/Main and is currently the first artist-in-residence at the Swiss Federal Institute for Technology (EPFL) and its Laboratory for Experimental Museology (eM+). Her practice focuses on the politics and the emancipatory potential of new technologies, such as machine intelligence or data sculpting, non-human agency and transcendence. Al-Badri’s artistic material is a speculative archaeology from fossils to artifacts or performative interventions in museums and other public spaces, that respond to the inherent power structures.

Berlin/Germany – Web Resident »An AI Summer,« 2017