Abstract
This chapter explores contemporary trends in the application of machine learning technologies in music composition and performance contexts. It argues that there is a resurgence of cybernetic approaches to music-making in response to the rapid proliferation of machine learning technologies for artificial media production in recent years. These approaches are contextualised with reference to a history of interactions between cybernetic thought and musical practices, as well as a recent rethinking of cybernetics represented in the work of Yuk Hui and N. Katherine Hayles. It considers the problem of AI slop generators designed and pushed by hegemonic tech giants, paying specific attention to the unethical and irresponsible practices used in their production as well as the algorithmic monoculture perpetuated in their outputs. The chapter then turns to key musical artists at the forefront of the cybernetic resurgence who are engaged in an ethical reappropriation of machine learning techniques away from the big tech giants, before concluding with some suggestions for how an ethically grounded cybernetics of musical machine learning might open a new space of artistic possibility beyond the algorithmic monoculture of AI slop.
| Original language | English |
|---|---|
| Title of host publication | Artificial Media Emerging Trends in Narratives, Education and Creative Practice |
| Editors | Nelson Zagalo, Damián Keller |
| Place of Publication | Cham, Switzerland |
| Pages | 95-113 |
| Number of pages | 18 |
| ISBN (Electronic) | 978-3-031-89037-6 |
| Publication status | Published (in print/issue) - 4 Sept 2025 |
Bibliographical note
Agostinelli, A., Denk, T.I., Borsos, Z., Engel, J., Verzetti, M., Caillon, A., Huang, Q., Jansen, A., Roberts, A., Tagliasacchi, M. and Sharifi, M. (2023). Musiclm: Generating music from text. arXiv preprint arXiv:2301.11325.Anil, R., Borgeaud, S., Alayrac, J.B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A.M., Hauth, A., Millican, K. and Silver, D. (2023). Gemini: A family of highly capable multimodal models. arXiv preprint arXiv:2312.11805, 1.
Antoine Caillon. (n.d.). GitHub - acids-ircam/RAVE: Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder. GitHub. Retrieved July 22, 2024, from https://github.com/acids-ircam/RAVE
Anthropic. (2023, March). Introducing Claude. Anthropic.com. Retrieved July 19, 2024, from https://www.anthropic.com/news/introducing-claude
Barton, T. and Hulbert, A. (2024: in press). Cultivating Sounds: Relational acoustics within the Buchla-Serge paradigm. In: Filimowicz., M. (ed). Routledge Handbook of Sound Design. London: Routledge.
Barry, E. (2024). Is an AI stock bubble looming? That’s the $167 billion question. Market Watch. Retrieved December 18, 2024, from https://www.marketwatch.com/story/is-an-ai-stock-bubble-looming-thats-the-167-billion-question-53a76c00
Beer, S. (1972). The Brain of the Firm. London: John Wiley and Sons Ltd.
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the dangers of stochastic parrots: Can language models be too big?🦜. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610-623).
Berger, V. (2024, June 27). Why major labels are suing AI music startups Udio and Suno for mass copyright infringement. Forbes. https://www.forbes.com/sites/virginieberger/2024/06/27/why-major-labels-are-suing-ai-music-startups-udio-and-suno-for-mass-copyright-infringement/
Braidotti, R. (2012). Afterword: Complexity, materialism, difference. Angelaki, 17(2), 169-176.
Brockman, J. (1992). The first electronic film score- Forbidden Planet: A conversation with Bebe Barron. The Score: The Society of Composers and Lyricists, 7(3), 5.
Canguilhem, G. (1952) Machine et organisme. In La Connaissance de la vie, (pp 124-159). Hachette.
Collins, N. (2008). The analysis of generative music programs. Organised sound, 13(3), 237-248.
Concialdi, G., Koudounas, A., Pastor, E., Di Eugenio, B., & Baralis, E. (2024, April). Ainur: Harmonizing Speed and Quality in Deep Music Generation Through Lyrics-Audio Embeddings. In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1146-1150). IEEE.
Copet, J., Kreuk, F., Gat, I., Remez, T., Kant, D., Synnaeve, G., Yossi, A., & Défossez, A. (2024). Simple and controllable music generation. Advances in Neural Information Processing Systems, 36.
Dhariwal, P., Jun, H., Payne, C., Kim, J. W., Radford, A., & Sutskever, I. (2020). Jukebox: A generative model for music. arXiv preprint arXiv:2005.00341.
Dreyfus, H. L. (1992). What Computers Still Can’t Do: A Critique of Artificial Reason. The MIT Press.
Dua, M., Yadav, R., Mamgai, D., & Brodiya, S. (2020). An improved RNN-LSTM based novel approach for sheet music generation. Procedia Computer Science, 171, 465-474.
Eck, D., & Schmidhuber, J. (2002). A first look at music composition using lstm recurrent neural networks. Istituto Dalle Molle Di Studi Sull Intelligenza Artificiale, 103(4), 48.
Engel, J., Hantrakul, L., Gu, C., & Roberts, A. (2020). DDSP: Differentiable digital signal processing. arXiv preprint arXiv:2001.04643.
Eno, B. (1976). Generating and organizing variety in the Arts. Studio International, 192(984), 279-283.
Evans, Z., Carr, C. J., Taylor, J., Hawley, S. H., & Pons, J. (2024). Fast timing-conditioned latent audio diffusion. arXiv preprint arXiv:2402.04825.
Fiebrink, R., Trueman, D., & Cook, P. R. (2009). A meta-instrument for interactive, on-the-fly machine learning.
Gebru, T., & Torres, É. P. (2024). The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday.
Geoghegan, B. D.(2023) Code: From Information Theory to French Theory. Duke University Press.
Goldman Sachs. (2024). Gen AI: too much spend, too little benefit? In Goldman Sachs. https://www.goldmansachs.com/intelligence/pages/gen-ai-too-much-spend-too-little-benefit.html
Google. (2022, May). Imagen. Retrieved July 19, 2024, from https://imagen.
Research.google
Greenwald, T. (1986). The self-destructing modules behind the revolutionary 1956 soundtrack of Forbidden Planet. Keyboard Magazine, 12, 54-65.
Hayles, K. N. (1999). How we became Posthuman: Virtual bodies in cybernetics, literature, and informatics (1st ed.). University of Chicago Press.
Hayles, N. K. (2024). Detoxifying Cybernetics: From Homeostasis to Autopoiesis and Beyond. In Cybernetics for the 21st Century, Vol. 1: Epistemological Reconstruction. Edited by Yuk Hu (pp. 54-66). Hanart Press.
Hernandez, D. R. (2017). Music in the Age of Communication and Control. University of California, Santa Cruz.
Hinton, P. (2024, March 1). How Hexorcismos’ collaborative project ‘MUTUALISMX’ challenges AI prejudices. Mixmag. Retrieved July 22, 2024, from https://mixmag.net/feature/mutualismx-hexorcismos-ai-artificial-intelligence-interview
Ho, N. (2023). Cybernetic Synthesis and Roland Kayn. [online resource]. Available at: https://nathan.ho.name/posts/cybernetic-synthesis/
Hu, Y., Huber, A., Anumula, J., & Liu, S. C. (2018). Overcoming the vanishing gradient problem in plain recurrent networks. arXiv preprint arXiv:1801.06105.
Huang, Q., Park, D. S., Wang, T., Denk, T. I., Ly, A., Chen, N., ... & Han, W. (2023). Noise2music: Text-conditioned music generation with diffusion models. arXiv preprint arXiv:2302.03917.
Hui, Y. (2024). Machine and Ecology. In Cybernetics for the 21st Century, Vol. 1: Epistemological Reconstruction. Edited by Yuk Hu (pp. 54-66). Hanart Press.
Kayn, R. (1977). Simultan. [3-LP set]. Colosseum (COLOS SM 1473). Liner notes reproduced at: https://kayn.nl/wp-content/uploads/2016/12/Simultan.pdf
Kayn, R. (1984). Tektra [6-LP set]. Colosseum (COLOS SM1479). Liner notes reproduced at: https://kayn.nl/wp-content/uploads/2021/12/tektra_booklet_2021.pdf
Keller, D., Schiavoni, F., & Lazzarini, V. (2019). Ubiquitous music: Perspectives and challenges. Journal of New Music Research, 48(4), 309-315.
Kim, J. W., Salamon, J., Li, P., & Bello, J. P. (2018, April). Crepe: A convolutional representation for pitch estimation. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 161-165). IEEE.
Lakoff, G., & Johnson, M. (1980). Metaphors we live by. University of Chicago press.
Lewis, G. (2021). Co-creation: early steps and future prospects. In Bernard Lubat, Gérard Assayag, Marc Chemillier. Artisticiel/Cyber-Improvisations. Phonofaune, 2021, Dialogiques d'Uzeste.
Lewis, G. E. (2019). Listening for freedom with Arnold Davidson. Critical Inquiry, 45(2), 434-447.
Lewis, G. E. (2000). Too many notes: Computers, complexity and culture in voyager. Leonardo music journal, 10, 33-39.
Lighthill, J. (1973, April). Artificial intelligence: A general survey. In Artificial Intelligence: a paper symposium (pp. 1-21). London: Science Research Council.
Loughran, R., & O’Neill, M. (2016). Generative music evaluation: why do we limit to ‘human’. In Proceedings of the first Conference on Computer Simulation of Musical Creativity (CSMC 2016), Huddersfield, UK.
Lovelock, J. E. (1983). Gaia as seen through the atmosphere. In Biomineralization and Biological Metal Accumulation: Biological and Geological Perspectives Papers presented at the Fourth International Symposium on Biomineralization, Renesse, The Netherlands, June 2–5, 1982 (pp. 15-25). Dordrecht: Springer Netherlands.
Magenta. (2023). Magenta Studio - Ableton Live Plugin. Retrieved July 22, 2024, from https://magenta.tensorflow.org/studio
Maturana, H. R., & Varela, F. J. (1991). Autopoiesis and cognition: The realization of the living (Vol. 42). Springer Science & Business Media.
McCarthy, J. (1996). Defending Al Research: A Collection of Essays and Reviews (Lecture Notes Series). CSLI Publications (p 73, pp45-46).
Midjourney. (2023, Mar). Midjourney. https://www.midjourney.com. Retrieved July 19, 2024, from https://www.midjourney.com
Moises horta Valenzuela. (2019). HEXORCISMOS- a ritual for floral, cybernetic & neuronal intelligences. moiseshorta.audio. https://moiseshorta.audio/obra/hexorcismos-ritual-for-floral-cybernetic-neuronal-intelligences/
Nake, F. (2012). Information aesthetics: An heroic experiment. Journal of Mathematics and the Arts, 6(2-3), 65-75.
Nicoletti, L., & Bass, D. (2023) Humans Are Biased. Generative AI Is Even Worse? Bloomberg https://www.bloomberg.com/graphics/2023-generative-ai-bias/
O'Connell, M. (2018). To be a machine: Adventures among cyborgs, utopians, hackers, and the futurists solving the modest problem of death. Anchor.
Oord, A. V. D., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., ... & Kavukcuoglu, K. (2016). Wavenet: A generative model for raw audio. arXiv preprint arXiv:1609.03499.
Open AI. (2022, November). Introducing ChatGPT. openai.com. Retrieved July 19, 2024, from https://openai.com/index/chatgpt/
OpenAI. (2021, January). Dall-E 2. OpenAI.com. Retrieved July 19, 2024, from
https://openai.com/dall-e-2/
Patteson, T. W. (2012). The time of Roland Kayn’s cybernetic music. Travelling Time, Sonic Acts XIV, 47-67.
Perrigo, B. (2023) OpenAI Used Kenyan Workers on Less Than $2 per Hour to Make ChatGPT Less Toxic, Time. https://time.com/6247678/openai-chatgpt-kenya-workers/
Pickering, A. (2010). The cybernetic brain: Sketches of another future. University of Chicago Press.
Pickles, D. (2016). Cybernetics in music. (Doctoral dissertation, Coventry University).
Pickles, D., & Collis, A. (2016). Cybernetic principles and sonic ecosystems. In 42nd International Computer Music Conference (pp. 529-532). International Computer Music Association.
Pinch, T., & Trocco, F. (2004). Analog days: The invention and impact of the Moog synthesizer. Harvard University Press.
Ren, S., & Wierman, A. (2024) The Uneven Distribution of AI’s Environmental Impacts Harvard Business Review https://hbr.org/2024/07/the-uneven-distribution-of-ais-environmental-impacts
Roberts, A., Engel, J., Raffel, C., Hawthorne, C., & Eck, D. (2018, July). A hierarchical latent vector model for learning long-term structure in music. In International conference on machine learning (pp. 4364-4373). PMLR.
Roddy, S. (2023). Creative Machine-Human Collaboration: Toward a Cybernetic Approach to Artificial Intelligence and Machine Learning Techniques in the Creative Arts. In AI and the Future of Creative Work (pp. 18-35). Routledge.
Roddy, S., & Parmar, R. (2023). AI/ML in the Sonic Arts: Pitfalls and Pathways. Resonance: The Journal of Sound and Culture, 4(4), 399-408.
Sanfilippo, D. (2023). The Aesthetics of Musical Complex Systems. Organised Sound, 28(3), 381-391.
Silliman, D. A. (2023). Transcendent Machine: An Analysis of Éliane Radigue’s ARP 2500 Synthesizer Music (Doctoral dissertation, Princeton University).
Sonology, Institute of (2005). Studio Manual BEA5. [online resource]. Available at: https://sonology.org/wp-content/uploads/2020/01/STUDIO-MANUAL-BEA-5-2005-opt.pdf
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution
image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF
Conference on Computer Vision and Pattern Recognition (pp. 10684–10695).
IEEE, CVF.
Royal Northern College of Music. (2023, January 6). George Lewis Residency | RNCM Musicians and An Enhanced Voyager - Royal Northern College of Music. RNCM. Retrieved July 22, 2024, from https://www.rncm.ac.uk/research/research-activity/research-centres-rncm/prism/prism-news-and-events/george-lewis-residency-rncm-musicians-and-an-enhanced-voyager/
Sagan, L. (1967). On the origin of mitosing cells. Journal of theoretical biology, 14(3), 225-IN6.
Tayeb, Z. (2023, July 20). Stability AI cofounder dumped his entire stake for a mere $100 just months before company hit a $1 billion valuation. Markets Insider. https://markets.businessinsider.com/news/stocks/stability-ai-cofounder-dumped-stake-1-billion-valuation-2023-7
Tazelaar, K. 2021. Ring-modulated Feedback in BEA5. [online video]. Available at: https://sonology.org/aiovg_videos/ring-modulated-feedback-in-bea5/ [last accessed 18th December, 2024]
TechCrunch. (2024, May 13). TechCrunch. Retrieved July 19, 2024, from https://techcrunch.com/2024/05/13/anthropic-is-expanding-to-europe-and-raising-more-money/
Tokui, N. (2024). Surfing human creativity with AI — A user's guide. English Edition.
Turing, A. (2004). Intelligent Machinery.
Ugander, J., & Epstein, Z. (2024). The art of randomness: Sampling and chance in the age of algorithmic reproduction. Harvard Data Science Review, 6(4).
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems, 30.
Vink, J. (2017). s/t [LP/digital release]. Paris, France: GRM: Recollection GRM (REGRM018EXT).
Von Foerster, H. (1984). Observing Systems. Intersystems Publications.
Vyas, A., Shi, B., Le, M., Tjandra, A., Wu, Y. C., Guo, B., Zhang, J., Zhang, X., Adkins, R., Ngan, W., Wang, J., Cruz, I., Akula, B., Akinyemi, A., Ellis, B., Moritz, R., Yungster, Y., Rakotoarison, A., Tan, L., Summers, C., Wood, C., Lane, J., Williamson, M., & Hsu, W. N. (2023). Audiobox: Unified audio generation with natural language prompts. arXiv preprint arXiv:2312.15821.
Whittaker, D., Beer, S., & Eno, B. (2003). Stafford Beer: a personal memoir. Wavestone Press.
Wiener, N. (1948). Cybernetics or control and communication in the animal and the machine. MIT Press.
Wishart, T. (1996). On sonic art (Vol. 12). Psychology Press.
Keywords
- Cybernetic
- Music
- ML
- AI
- AI/ML
- Slop
