Explainable Computational Creativity
This work targets enhancing collaboration between humans and creative AI systems, though it appears incremental as it builds on existing CC concepts without introducing a new paradigm.
The paper addresses the problem of shallow human-system interactions in Computational Creativity by proposing design principles to enable two-way communication, allowing systems to explain their creative processes and decisions for improved co-creation.
Human collaboration with systems within the Computational Creativity (CC) field is often restricted to shallow interactions, where the creative processes, of systems and humans alike, are carried out in isolation, without any (or little) intervention from the user, and without any discussion about how the unfolding decisions are taking place. Fruitful co-creation requires a sustained ongoing interaction that can include discussions of ideas, comparisons to previous/other works, incremental improvements and revisions, etc. For these interactions, communication is an intrinsic factor. This means giving a voice to CC systems and enabling two-way communication channels between them and their users so that they can: explain their processes and decisions, support their ideas so that these are given serious consideration by their creative collaborators, and learn from these discussions to further improve their creative processes. For this, we propose a set of design principles for CC systems that aim at supporting greater co-creation and collaboration with their human collaborators.