Reclaiming the Humanities in AI-Generated Music: Language, Identity, and Social Media Circulation in Folk and Rock Traditions - Mark H. Levine (WISE Pendidikan Indonesia, 2026)
Generative artificial intelligence (AI) has transformed music production from a specialist studio practice into a prompt-based, platform-mediated activity in which songs, lyrics, voices, and genre markers can be produced almost instantly. This article repositions the debate about AI music within the intersection of language, technology, and social media by examining folk and rock music as communicative traditions rather than merely sonic products. Using a qualitative critical-hermeneutic design, the study analyzes selected folk, rock, and protest songs together with scholarship on text-to-music generation, platformization, digital authenticity, copyright, and embodied creativity. The analysis shows that AI music is not only a technological issue but also a linguistic and communicative one: prompts translate human intention into machine output, lyrics encode social memory, synthetic voices simulate identity, and streaming/social-media platforms recode authenticity through visibility metrics and algorithmic circulation. Four findings are developed: AI simulates stylistic language without situated experience; folk and rock operate as traditions of memory, resistance, and identity; social media transforms musical authenticity into a platform performance; and ethical AI music requires human-centered design, consent-based training, provenance labeling, and critical digital literacy. The article contributes a human-first framework for studying AI-generated music as a language-technology-social media phenomenon while preserving the humanities dimensions of agency, voice, embodiment, and cultural memory.