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Recent neural generation systems have demonstrated the potential forprocedurally generating game content, images, stories, and more. However, mostneural generation algorithms are "uncontrolled" in the sense that the user haslittle say in creative decisions beyond the initial prompt specification.Co-creative, mixed-initiative systems require user-centric means of influencingthe algorithm, especially when users are unlikely to have machine learningexpertise. The key to co-creative systems is the ability to communicate ideasand intent from the user to the agent, as well as from the agent to the user.Key questions in co-creative AI include: How can users express their creativeintentions? How can creative AI systems communicate their beliefs, explaintheir moves, or instruct users to act on their behalf? When should creative AIsystems take initiative? The answer to such questions and more will enable usto develop better co-creative systems that make humans more capable ofexpressing their creative intents. We introduce CREATIVE-WAND, a customizableframework for investigating co-creative mixed-initiative generation.CREATIVE-WAND enables plug-and-play injection of generative models andhuman-agent communication channels into a chat-based interface. It provides anumber of dimensions along which an AI generator and humans can communicateduring the co-creative process. We illustrate the CREATIVE-WAND framework byusing it to study one dimension of co-creative communication-global versuslocal creative intent specification by the user-in the context of storytelling.

Creative Wand: A System to Study Effects of Communications in Co-Creative Settings