About

This PhD investigates the capacity of Generative AI (GenAI) for co-creating choreography and identifies its caveats by making visible the gender bias of GenAI through performance. By focussing on the body—a primary site of gender performance—I aim to expose and subvert gender bias in GenAI. The research, on the one hand, explores the utilities of GenAI, recognising its convenience, productivity and speed, but on the other hand, addresses its bias. As the literature has shown, GenAI, whilst often perceived as neutral, reflects and reinforces societal gender inequalities (Noble 2018, Joyce and Cruz 2024, Vallor 2024).

I will explore how to incorporate GenAI as a co-creator in choreographic processes, its influence on the performing body, and test how human dancers can challenge and interact with GenAI through choreographic performance to reveal gender bias. My study experiments with new possibilities for human-machine collaboration. It envisions a new framework for integrating GenAI into choreographic practices, pushing boundaries in the representation of the body in performance.

The research will draw on feminist theories, including critical data studies, critical AI studies (O’Neil 2016, Noble 2018), queer feminism (Butler 1990, Ahmed, 2006), radical feminism (Firestone 1970), and feminist embodiment theory (Grosz 1994), to critique how GenAI reinforces gender norms. It will explore how GenAI through collaboration with the performing body can challenge these norms, and offer new opportunities for equitable, and ethical creative processes.

Through practical applications, for example prompting GenAI to create choreographic scores (highlighting gender) that are then performed, I will expose how GenAI perceives gender, contributing to both the development of GenAI applications in the arts and an understanding of GenAI’s role in society. This PhD will examine how the body in performance, and in collaboration with GenAI, can reframe or resist normative gender expressions.