Large Language Models for Human-AI Co-Creation of Robotic Dance Performances
Large Language Models for Human-AI Co-Creation of Robotic Dance Performances
Allegra De Filippo, Michela Milano
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
AI, Arts & Creativity. Pages 7627-7635.
https://doi.org/10.24963/ijcai.2024/844
This paper focuses on the potential of Generative Artificial Intelligence (AI), particularly Large Language Models (LLMs), in the still unexplored domain of robotic dance creation. In particular, we assess whether a LLM (GPT-3.5 turbo) can create robotic dance choreographies, and we investigate if the feedback provided by human creators can improve the quality of the output. To this end, we design three prompt engineering techniques for robotic dance creation. In the prompts, we gradually introduce human knowledge through examples and feedback in natural language in order to explore the dynamics of human-AI co-creation. The experimental analysis shows that the capabilities of the LLM can be improved through human collaboration, by producing choreographies with a major artistic impact on the evaluation audience. The findings offer valuable insights into the interplay between human creativity and AI generative models, paving the way for enhanced collaborative frameworks in creative domains.
Keywords:
Application domains: Performances, dance
Methods and resources: AI systems for collaboration and co-creation