Co-creation in embodied contexts is central to the human experience but is often lacking in our interactions with computers. We seek to develop a better understanding of embodied human co-creativity to inform the human-centered design of machines that can co-create with us. In this paper, we ask: What characterizes dancers’ experiences of embodied dyadic interaction in movement improvisation? To answer this, we ran focus groups with 24 university dance students and conducted a thematic analysis of their responses. We synthesize our findings in an interconnected model of improvisational dance inputs where movement choices are shaped by interplays such as in-the-moment influences between the self, partner, and the environment as well as a set of generative strategies and heuristics for a successful collaboration. We present a set of design recommendations for LuminAI, a co-creative AI dance partner. Our contributions can inform the design of AI in embodied co-creative domains.
https://doi.org/10.1145/3613904.3642677
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