Concept Text:
Ilan Manouach’s previous work and research has shown, comics are particularly amenable to programmatic processes. From his early comic book appropriations to the latest book based on the orchestrated work of hundreds of comics artists, each project can be easily described as a set of instructions, in a programmatic fashion that highly resembles the bottom-up algorithmic processes of deep neural nets in machine learning. His current research project Applied Memetic is focused on Generative Adversarial Networks and their ability to generate novel images by emulating the probability distribution of given training datasets. The main motivation is to apply a GAN-derived model, to the generation of sequential comics art. Graphic narratives are not only important in general domains of artistic expression. They are tools whose multimodal expressive communication has become our primary modality in sharing and shaping representation of our worlds. By exploring the potential of AI’s ability to create graphic narratives Applied Memetic is also able to study gradually how human emotions are understood and can be reproduced by an AI within a narrative.The study poses the question whether the human capacity to feel empathy could be programmed and applied to artificial caregivers and companions in the future. For the Web Residency Manouach will be submitting texts and research on the ongoing study in collaboration with curator Denise Araouzou who is currently investigating affective labour in the beauty and healthcare industries.
Applied Memetic: Developing and researching synthetic media content
Image by Ilan Manouach & Denise Araouzou
