Meaning and Human Flourishing in Platform-Mediated Creative Labor ——Assessing Generative AI Music Tools via Mixed Methods

Xie Peng, Francis Michael P. Yambao

Graduate School, Centro Escolar University, Manila, Philippines

Abstract：

This study explores the changes in music creation brought about by generative artificial intelligence (AI) music tools such as Suno and Udio. Although these tools enhance the efficiency of music production, their "low-friction generation" (LFG) may simultaneously transform creators' creative labor and their human flourishing. Using an exploratory sequential mixed-methods design that combines netnography and LLM-assisted text mining of online creator communities (N = 1,815 community comments) with a structured questionnaire survey (N = 180), research finds that the low-friction properties of generative AI significantly decrease creators' sense of meaningful work and induce strong existential alienation (LFG → MW: β = −0.362, p <0.001; LFG → EA: β = 0.503, p <0.001); meaningful work positively predicts human flourishing, whereas existential alienation negatively predicts it (MW → HF: β = 0.34, p <0.001; EA → HF: β = −0.36, p <0.001); and a one-way ANOVA reveals a "backfire effect" of expertise: independent musicians and industry professionals report significantly lower meaningful work and significantly higher existential alienation than amateurs (MW: F (2, 177) = 11.82, p <0.001, ηp² = 0.118; EA: F (2, 177) = 9.88, p <0.001, ηp² =0.100). We conclude that an environment with insufficient creative friction is unlikely to sustain true artistic flourishing, and we argue that technological design and artistic creation should move toward meaning-friendly human–AI co-creation interfaces.

Key Words：

generative AI; creative labor; labor alienation; human flourishing; sociology of music