Towards a Framework for Human-AI Interaction Patterns in Co-Creative GAN Applications

Abstract
With the rise of Generative Adversarial Networks (GANs), AI has increasingly become a partner to human designers in
co-creating cultural artifacts. While generative models have been applied in various creative tasks across disciplines, a
theoretical foundation for understanding human-GAN collaboration is yet to be developed. Drawing from the mixed-initiative
co-creation community, we propose a preliminary framework to analyze co-creative GAN applications. We identify four
primary interaction patterns: Curating, Exploring, Evolving, and Conditioning. The suggested framework enables us to discuss
the affordances and limitations of the different kind of interactions underlying co-creative GAN applications