Mitra Azar’s project DoppelGANger consists of a series of interventions in which he disseminates posters of missing persons on the streets of Cuba, Paris, Milan and other cities in the world. The images and texts on these posters are the results of algorithms based on generative adversarial networks (or GAN) – machine learning sytems based on neural networks. After being trained on large datasets of photographs and written data respectively, these algorithms are able to generate photorealistic yet completely fictional portraits and coherent paragraphs from scratch. The work questions the indexical relationship between the seemingly photographic portraits and their referents: it reverses photography’s claim of temporal and spatial accuracy by transforming image processes of capture into a pre-emptive technology whereby pictures of reality are simulated before they might potentially become real. Are these images of missing people waiting for their real counterparts to be ‘found’ in the streets or yet to be born? Are they computational ghosts of machine produced-visions of how humankind should look like or are they digital doppelgangers, proxies of real humans?