The Need for Explainability in AI-Based Creativity Support Tools

A long lineage of computer-assisted design tools has established interaction<br/>paradigms that give full control to the designer over the software. Introduction<br/>of Artificial Intelligence (AI) to this creative process leads to a more co-creative<br/>paradigm, with AI taking a more proactive role. Recent generative approaches<br/>based on deep learning have strong potential as an asset creator and co-creator,<br/>however current algorithms are opaque and burden the designer with making sense<br/>of the output. In order for deep learning to become a colleague that designers can<br/>trust and work with, better explainability, controllability, and interactivity is necessary. We highlight current and potential ways in which explainability can inform<br/>human users in creative tasks and call for involving end-users in the development<br/>of both interfaces and underlying algorithms.