Reclaiming the Humanities in AI-Generated Music: Language, Identity, and Social Media Circulation in Folk and Rock Traditions
DOI:
10.70211/ltsm.3026-7196.423Published:
2026-06-12Downloads
Abstract
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.
Keywords:
AI-Generated Music Language And Identity Social Media Human-Computer Interaction Folk Music Rock Music Digital AuthenticityReferences
[1] Y. Zhao, M. Yang, Y. Lin, X. Zhang, F. Shi, Z. Wang, J. Ding, and H. Ning, “AI-enabled text-to-music generation: A comprehensive review of methods, frameworks, and future directions,” Electronics, vol. 14, no. 6, Art. no. 1197, 2025. https://doi.org/10.3390/electronics14061197
[2] Y. Zhu, J. Baca, B. Rekabdar, and R. Rawassizadeh, “A survey of AI music generation tools and models,” arXiv:2308.12982, 2023. https://doi.org/10.48550/arXiv.2308.12982
[3] W. C. Choi, C. I. Chang, and H. F. Choi, “Suno AI: Opportunities and challenges of AI-generated music and lyrics in secondary music education,” in Proc. 2025 8th Artificial Intelligence and Cloud Computing Conference (AICCC ’25), 2026, pp. 281–292. https://doi.org/10.1145/3789982.3790019
[4] B. L. T. Sturm and O. Ben-Tal, “Folk the algorithms: (Mis)applying artificial intelligence to folk music,” in Handbook of Artificial Intelligence for Music, E. R. Miranda, Ed. Cham, Switzerland: Springer, 2021, pp. 423–454. https://doi.org/10.1007/978-3-030-72116-9_16
[5] R. Prey, “Nothing personal: Algorithmic individuation on music streaming platforms,” Media, Culture & Society, vol. 40, no. 7, pp. 1086–1100, 2018. https://doi.org/10.1177/0163443717745147
[6] R. Prey, “Locating power in platformization: Music streaming playlists and curatorial power,” Social Media + Society, vol. 6, no. 2, 2020. https://doi.org/10.1177/2056305120933291
[7] A. E. Marwick and d. boyd, “I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience,” New Media & Society, vol. 13, no. 1, pp. 114–133, 2011. https://doi.org/10.1177/1461444810365313
[8] J. Androutsopoulos, “Networked multilingualism: Some language practices on Facebook and their implications,” International Journal of Bilingualism, vol. 19, no. 2, pp. 185–205, 2015. https://doi.org/10.1177/1367006913489198
[9] M. Zappavigna, “Searchable talk: The linguistic functions of hashtags,” Social Semiotics, vol. 25, no. 3, pp. 274–291, 2015. https://doi.org/10.1080/10350330.2014.996948
[10] J. Edlom, “Authenticity and digital popular music brands,” in Popular Music, Technology, and the Changing Media Ecosystem, T. Tofalvy and E. Barna, Eds. Cham, Switzerland: Springer, 2020, pp. 129–145. https://doi.org/10.1007/978-3-030-44659-8_8
[11] R. C. Valverde, “Online musicking for humanity: The role of imagined listening and the moral economies of music sharing on social media,” Popular Music, vol. 41, no. 2, pp. 194–215, 2022. https://doi.org/10.1017/S0261143022000034
[12] T. Gillespie, “The politics of platforms,” New Media & Society, vol. 12, no. 3, pp. 347–364, 2010. https://doi.org/10.1177/1461444809342738
[13] A. Buick, “Copyright and AI training data—Transparency to the rescue?,” Journal of Intellectual Property Law & Practice, vol. 20, no. 3, pp. 182–192, Mar. 2025. https://doi.org/10.1093/jiplp/jpae102
[14] S. Jacques and M. Flynn, “Protecting human creativity in AI-generated music with the introduction of an AI-royalty fund,” GRUR International, vol. 73, no. 12, pp. 1137–1149, Dec. 2024. https://doi.org/10.1093/grurint/ikae134
[15] J. Deng, S. Zhang, and J. Ma, “Computational copyright: Towards a royalty model for music generative AI,” arXiv:2312.06646, 2023. https://doi.org/10.48550/arXiv.2312.06646
[16] K. Lee, A. F. Cooper, and J. Grimmelmann, “Talkin’ ’bout AI generation: Copyright and the generative-AI supply chain,” arXiv:2309.08133, 2023. https://doi.org/10.2139/ssrn.4523551
[17] E. Kanhov, “Innovation, data colonialism and ethics: Critical reflections on music technology,” Journal of New Music Research, 2024. https://doi.org/10.1080/09298215.2024.2442359
[18] J. de Berardinis, L. Porcaro, A. Meroño-Peñuela, A. Cangelosi, and T. Buckley, “Towards responsible AI music: An investigation of trustworthy features for creative systems,” arXiv:2506.07454, 2025. https://doi.org/10.48550/arXiv.2506.07454
[19] R. S. Denisoff, “Folk-rock: Folk music, protest, or commercialism?,” Journal of Popular Culture, vol. 3, no. 2, pp. 214–230, 1969. https://doi.org/10.1111/j.0022-3840.1969.0302_214.x
[20] R. S. Denisoff, Great Day Coming: Folk Music and the American Left. Urbana, IL, USA: University of Illinois Press, 1971.
[21] A. Moore, “Authenticity as authentication,” Popular Music, vol. 21, no. 2, pp. 209–223, May 2002. https://doi.org/10.1017/S0261143002002131
[22] D. van der Schyff, A. Schiavio, A. Walton, V. Velardo, and A. Chemero, “Musical creativity and the embodied mind: Exploring the possibilities of 4E cognition and dynamical systems theory,” Music & Science, vol. 2, 2018. https://doi.org/10.1177/2059204318792319
[23] A. Schiavio and M. Benedek, “Dimensions of musical creativity,” Frontiers in Neuroscience, vol. 14, Art. no. 578932, 2020. https://doi.org/10.3389/fnins.2020.578932
[24] P.-J. Maes, “Sensorimotor grounding of musical embodiment and the role of prediction: A review,” Frontiers in Psychology, vol. 7, Art. no. 308, 2016. https://doi.org/10.3389/fpsyg.2016.00308
[25] W. Guthrie, “This Land Is Your Land,” Dust Bowl Ballads, Folkways Records, 1940.
[26] Library of Congress, “Bury Me Not on the Lone Prairie,” 1880. [Online]. Available: https://www.loc.gov/item/ihas.20015552/
[27] Library of Congress, “La Cucaracha,” 1915. [Online]. Available: https://www.loc.gov/item/ihas.20015551/
[28] Nirvana, “Smells Like Teen Spirit,” Nevermind, DGC Records, 1991.
[29] Public Enemy, “Fight the Power,” Fear of a Black Planet, Def Jam Recordings, 1989.
[30] B. Dylan, “Like a Rolling Stone,” Highway 61 Revisited, Columbia Records, 1965.
[31] B. Springsteen, “Born in the U.S.A.,” Born in the U.S.A., Columbia Records, 1984.
[32] B. Springsteen, “Streets of Minneapolis,” Columbia Records, 2026.
[33] D. Walker, “Khe Sanh,” performed by Cold Chisel, WEA, 1978.
[34] S. Cooke, “A Change Is Gonna Come,” Ain’t That Good News, RCA Victor, 1964.
[35] J. Denver, B. Danoff, and T. Nivert, “Take Me Home, Country Roads,” Poems, Prayers and Promises, RCA Victor, 1971.
[36] D. Dill and M. Tillis, “Detroit City,” Detroit City and Other Hits by Bobby Bare, RCA Victor, 1963.
[37] E. MacColl, “Dirty Old Town,” Rum Sodomy & the Lash, performed by The Pogues, Stiff Records, 1985; originally written 1949.
[38] A. Lomax, Ed., “Shenandoah,” in The Oxford Book of American Folk Songs. Oxford, U.K.: Oxford University Press, 1963.
[39] Yi minority traditional, “Ashi,” traditional song, Sichuan, China.
[40] L. W. Odeke and A. K. Kirui, “Reclaiming the sonic archive: AI, data sovereignty, and the future of Mijikenda music,” Journal of Visual and Performing Arts, vol. 3, no. 1, pp. 53–62, 2025. https://doi.org/10.58721/jvpa.v3i1.1516
[41] L. Cheng, “The impact of generative AI on school music education: Challenges and recommendations,” Arts Education Policy Review, 2025. https://doi.org/10.1080/10632913.2025.2451373
[42] M. A. Rahman, Z. I. A. Hakim, N. H. Sarker, B. Paul, and S. A. Fattah, “SONICS: Synthetic or not-identifying counterfeit songs,” arXiv:2408.14080, 2024. https://doi.org/10.48550/arXiv.2408.14080
[43] D. Afchar, G. Meseguer-Brocal, K. Akesbi, and R. Hennequin, “A Fourier explanation of AI-music artifacts,” arXiv:2506.19108, 2025. https://doi.org/10.48550/arXiv.2506.19108
Author Biography
Mark H. Levine, Minzu University of China
School of Foreign Studies
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Copyright (c) 2026 Mark H. Levine
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