Drawing with Reframer: Emergence and Control in Co-Creative AI

Abstract

Over the past few years, rapid developments in AI have resulted in new models capable of generating high-quality images and creative artefacts, most of which seek to fully automate the process of creation. In stark contrast, creative professionals rely on iteration—to change their mind, to modify their sketches, and to re-imagine. For that reason, end-to-end generative approaches limit application to real-world design workflows. We present a novel human-AI drawing interface called Reframer, along with a new survey instrument for evaluating co-creative systems. Based on a co-creative drawing model called the Collaborative, Interactive Context-Aware Design Agent (CICADA), Reframer uses CLIP-guided synthesis-by-optimisation to support real-time synchronous drawing with AI. We present two versions of Reframer’s interface, one that prioritises emergence and system agency and the other control and user agency. To begin exploring how these different interaction models might influence the user experience, we also propose the Mixed-Initiative Creativity Support Index (MICSI). MICSI rates co-creative systems along experiential axes relevant to AI co-creation. We administer MICSI and a short qualitative interview to users who engaged with the Reframer variants on two distinct creative tasks. The results show overall broad efficacy of Reframer as a creativity support tool, but MICSI also allows us to begin unpacking the complex interactions between learning effects, task type, visibility, control, and emergent behaviour. We conclude with a discussion of how these findings highlight challenges for future co-creative systems design.