AI-GENERATED FOLK MUSIC AND ITS CULTURAL RELEVANCE

Abstract

Artificial Intelligence (AI) has rapidly become a means to create music similar to the traditional cultural forms, but its impact on folk music as a form of art that is developed through oral tradition, community identity, and ritual sense has not been properly studied. The cultural relevance of AI-generated folk music, technical performance, and ethical implications of the technology will be explored in this paper in three folk traditions: Irish reels and jigs, Indian Garba/Lavani, and West African drumming. With the help of transformers, diffusion, and GAN-based models trained on culturally diverse samples, the study compares the outputs by using melodic, rhythmic, timbral, and cultural coherence metrics and additional community and expert evaluation. Findings indicate that AI can be used successfully in notation-friendly and structurally regular traditions and is weak in microtonality, expressive ornamentation, and rhythmic interaction of an ensemble. An important gap in perception is revealed: the listeners who listen to the music produced by AI have a more positive attitude to it, but those who belong to the traditions see cultural and stylistic mistakes. Ethical risks such as cultural misrepresentation, ownership and sensitivity in sacred material increase in highly culturally deprived traditions. The paper claims that AI can facilitate conservation and creative reuse in the event of ethical design, involvement in community, and culturally aware data. It ends by suggesting an ethically correct AI integration model that is culturally sensitive in folk music systems.