Human–machine co-creation: a complementary cognitive approach to creative character design process using GANs

Recent advances in generative adversarial networks (GANs) applications continue to attract the attention of researchers in different fields. In such a framework, two neural networks compete adversely to generate new visual contents indistinguishable from the original dataset. The objective of this research is to create a complementary co-design process between humans and machines to augment character designers’ abilities in visualizing and creating new characters for multimedia projects such as games and animation. Driven by design cognitive scaffolding, the proposed approach aims to inform the processes of perceiving, knowing, and making. The machine-generated concepts are used as a launching platform for character designers to conceptualize new characters. A labelled dataset of 22,000 characters was developed for this work and deployed using different GANs to evaluate the most suited for the context, followed by mixed methods evaluation for the machine output and human derivations. The discussed results substantiate the value of the proposed co-creation framework and elucidate how the generated concepts are used as cognitive substances that interact with designers’ competencies in a versatile manner to influence the creative processes of conceptualizing novel characters.