Due to its quickly evolving and exploratory nature, providing computational support tools for early design process stages remains a challenge. The main hurdle for any machine-learning approach is to make creative contributions without insisting on systematic explicit feedback, thus distracting design thinking. It is also important to study methods that do not compromise the designer’s agency, allowing designers to work with rather than for an algorithm.

May AI? presents cooperative contextual bandits (CCB) that can learn to propose domain-relevant contributions and adapt their exploration/exploitation strategy. In the context of mood-board making, we developed a CCB for an interactive design ideation tool that suggests inspirational and situationally relevant materials, explores and exploits inspirational materials with the designer, and explains its suggestions to aid reflection.