AI in Computational Arts, Music and Games research group focuses on exploring the novel aesthetics and affordances of Machine Learning (ML) and Artificial Intelligence (AI) within artistic applications.
We conduct research into+with+through algorithmic approaches such as deep generative models, supervised, unsupervised, and reinforcement learning, evolutionary approaches, multi-agent systems, and natural language processing. The artistic applications include musical and audiovisual performances, interactive installations, game art, augmented and virtual reality, video art, art with robotics, and bio-art. Artistic concepts and specific applications guide our technological and algorithmic choices, rather than independent disciplinary silos. We position this interdisciplinary approach under an encompassing term, Computational Arts.
Conventional Machine Learning and Artificial Intelligence emphasize gestalt–which is the end-product–and optimization while addressing questions such as: which architecture performs better or faster? How do we generate high-quality content such as image/video/audio/music? While these questions and gestalt are relevant with their significant contributions to society as the matters of fact, investigations into the AI technology creation processes, actors, and stakeholders can benefit societal discourses towards matters of concerns. Artistic realms provide opportunities to investigate AI technology both as their technology facts of new artistic opportunities in greater autonomy, and as their societal and cultural matters of concern.
The perspectives from third-wave feminism combined with methodologies from Science Technology Studies and philosophy of technology can create bridges that connect matters of facts such as accuracy, efficiency, optimization, reliability, and explainability; to matters of concerns such as ethics, inclusivity, sustainability, accessibility, and privacy. A better future with technologies of greater autonomy, can only be achieved with interdisciplinary perspectives. With artistic imagination in technology-making, informed by care-fully troubling processes, we pursue novel interdisciplinary research in artistic applications of Machine Learning and AI.
The group is led by Kıvanç Tatar. More information about the research group can be found on the external research group page.
