Project overview
ZAGHAREED is a research-creation project by Hanna Zhu that uses generative AI to extend a human dance performance beyond the physical body and recorded frame. Rather than treating movement as a prompt to be replaced, the project approaches the dancer’s embodied expression as the source of the work’s visual and cultural direction.
The project asks whether generative systems can participate in movement art without flattening the qualities that make a dance situated: effort, affect, memory, rhythm and cultural intention.
Research question
How can generative AI extend human movement into images that have never existed while remaining accountable to the body and culture from which the movement begins?
Human–AI co-creation
The creative process begins with human movement and artistic intent. Generative systems are used as interpretive collaborators, producing transformations and visual continuations that are evaluated through the maker’s embodied and aesthetic judgement.
This positions AI neither as an autonomous author nor as a neutral tool. It becomes part of an iterative relationship in which the human performer retains responsibility for framing, selection, meaning and cultural context.
Why the work matters
Many generative movement systems optimise for visual plausibility or technical control. ZAGHAREED shifts attention toward embodied affect and cultural specificity: whether the result feels connected to the movement practice that generated it, not simply whether it looks convincing.
Presentation and recognition
The project was accepted by the Interactive Film & Media Journal’s research-creation programme under the title ZAGHAREED: Extending Human Dance into the Yet-To-Be-Known with Generative AI.