Exploring Collaborative Movement Improvisation Towards the Design of LuminAI—a Co-Creative AI Dance Partner
Milka Trajkova, Duri Long, Manoj Deshpande, Andrea E. Knowlton, Brian Magerko
Abstract
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 the interplay between in-the-moment influences between the self, partner, and the environment, 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.