Breaking from realism: exploring the potential of glitch in AI-generated dance
Benedikte Wallace, Kristian Nymoen, Jim Tørresen, Charles Martín
Abstract
What role does deviation from realism play in the potential for generative artificial intelligence (AI) as a creative tool?A deep case-study was performed to explore interactions with AI-generated dance sequences as an inspiration source in dance composition and improvization.We present a simple interface created in collaboration with an experienced dancer for browsing AI-generated dance.By including glitches, the physics-breaking mistakes often encountered in AI-generated artefacts, we examine their affordances and possible use cases through sessions with the dancer.Through a process of reflexive thematic analysis, we identified that generative AI can engage a dancer through surprise, inspiring a transformation from abstract to physical movements.Our work challenges existing notions of the importance of realism in dance generation models, exemplifies the importance of close collaboration with practitioners in evaluating AI-generated artefacts and proposes glitch as a potential use case for dance ideation as it encourages dancers to embody unfamiliar movement qualities and break from ingrained patterns.