Nora Al-Badri is presenting Babylonian Vision at EPFL Pavilions, the result of her work during the CDH / EPFL Pavilions Artist-in-Residence program. Al-Badri trained a neural network using GAN technology (General Adversarial Networks) to generate new synthetic Babylonian objects based on ancestral ones, thereby taking back and re-possessing cultural datasets from colonial Western museum collections.
The neural network was primed with 10.000k images from five different museums with the largest collections of Mesopotamian, Neo-Sumerian and Assyrian artefacts. The images were for the most part collected through web crawling and scraping, and without the institutions’ approval (even though a request was made to each museum beforehand), with just two through their open API (MET and Cleveland museum).
With Babylonian Vision Nora Al-Badri expands on decolonial and machine learning museum practices by generating emancipatory technoheritage. Her approach invites reflection on loss of context in the presentation and interpretation of heritage objects, and authenticity and the place of original digital works in the cultural landscape.
Using artificial intelligence and the data gathered from these museum collections, Al-Badri has generated digital artefacts that are both indistinguishable from the original objects and far removed from them. While the input images carry time and memory themselves, the new synthetic images created evolve as a living memory of the original material objects of the past.
The EPFL Artist-in-Residence program is administered by the EPFL College of Humanities and implemented by EPFL Pavilions.