Generative AI-Assisted Chinese Classical Dance Choreography: Originality Definition and Subjectivity Game

Generative AI technology is reshaping the creative ecology of Chinese classical dance choreography and raising new questions concerning originality definition and creative subjectivity. Focusing on the reconstruction of originality standards and the interaction between human intention and algorithmic generation, this paper systematically analyzes the technical paths and practical status of generative AI-assisted classical dance choreography. Qualitative coding results from 12 expert interviews are integrated into the analysis, and a “three-dimensional originality evaluation model” and a “human-machine collaborative subjectivity balance framework” are constructed. The study finds that the originality of AI-assisted classical dance choreography should consider the novelty of technical generation, the uniqueness of cultural expression, and the autonomy of choreographic intention. The subjectivity game follows an evolutionary logic of technical instrumentalization, human-machine collaboration, and subject co-evolution. In the digital age, social empathy remains central to human artistic creation, while generative AI approaches this core through affective computing. A creative paradigm of humanistic guidance and technological empowerment is therefore proposed to support inheritance and innovation in classical dance choreography.