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From Artificial to Extended Intelligence in Music Composition

Published online by Cambridge University Press:  04 March 2020

Artemi-Maria Gioti*
Affiliation:
Institute of Electronic Music and Acoustics (IEM), Graz, Austria

Abstract

This article explores the relationship and disparities between human and computational creativity by addressing the following questions: How well are computational creativity systems currently performing at creative tasks? Could computers outperform human composers? And, if not, is computational creativity a utopia? Automatic composition systems are examined with respect to Boden’s three criteria of creativity (novelty, surprise and value), as well as their assumptions about the nature of creativity. As an alternative to a competitive relationship between human and computational creativity, the article proposes the concept of a distributed human–computer co-creativity, in which computational creativity extends – rather than replaces – human creativity, by expanding the space of creative possibilities.

Type
Articles
Copyright
© Cambridge University Press, 2020

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References

REFERENCES

Ariza, C. 2009. The Interrogator as Critic: The Turing Test and the Evaluation of Generative Music Systems. Computer Music Journal 33(2): 4870.CrossRefGoogle Scholar
Ashby, W. R. 1964. An Introduction to Cybernetics. London: Methuen (orig. pub. Chapman and Hall, 1956).Google Scholar
Bentley, P. J. and Corne, D. W. (eds.) 2002. Creative Evolutionary Systems. London: Academic Press.CrossRefGoogle Scholar
Boden, M. 2004. The Creative Mind: Myths and Mechanisms. London: Routledge.CrossRefGoogle Scholar
Boden, M. 2007. Creativity: How Does It Work? In Krausz, M., Dutton, D. and Bardsley, K. (eds.) The Idea of Creativity. Boston: Brill, 237–50.Google Scholar
Boden, M. 2010. Creativity and Art. Oxford: Oxford University Press.Google Scholar
Bown, O. 2012. Generative and Adaptive Creativity: A Unified Approach to Creativity in Nature, Humans and Machines. In McCormack, J. and d’Inverno, M. (eds.) Computers and Creativity. Berlin and Heidelberg: Springer, 361–81.CrossRefGoogle Scholar
Cage, J. 1952. 4′33″. Leipzig: Edition Peters, score EP6777.Google Scholar
Cage, J. 1960. Variations I. New York: Henmar Press.Google Scholar
Cardew, C. 1967. Treatise. Buffalo, NY: Gallery Upstairs Press.Google Scholar
Cohn, G. 2018. AI Art at Christie’s Sells for $432,500. New York Times, 25 October 25. www.nytimes.com/2018/10/25/arts/design/ai-art-sold-christies.html (accessed 15 May 2019).Google Scholar
Collins, N. 2012. Automatic Composition of Electroacoustic Art Music Utilizing Machine Listening. Computer Music Journal 36(3): 823.CrossRefGoogle Scholar
Cope, D. 1992. Computer Modelling of Musical Intelligence in EMI. Computer Music Journal 16(2): 6983.CrossRefGoogle Scholar
De Jager, H. 1972. Some Sociological Remarks on Innovation in Music. International Review of the Aesthetics and Sociology of Music 3(2): 252–8.CrossRefGoogle Scholar
Dorin, A. and Korb, K. B. 2012. Creativity Refined: Bypassing the Gatekeepers of Appropriateness and Value. In McCormack, J. and d’Inverno, M. (eds.) Computers and Creativity. Berlin and Heidelberg: Springer, 339–60.CrossRefGoogle Scholar
Engelbart, D. C. 1962. Augmenting Human Intellect: A Conceptual Framework. Report AFOSR-3233. Menlo Park, CA: Stanford Research Institute.CrossRefGoogle Scholar
Galanter, P. 2012. Computational Aesthetic Evaluation: Past and Future. In McCormack, J. and d’Inverno, M. (eds.) Computers and Creativity. Berlin and Heidelberg: Springer, 255–94.CrossRefGoogle Scholar
Gioti, A. M. 2017. Machine Listening in Interactive Music Systems: Current State and Future Directions. Proceedings of the 2017 International Computer Music Conference. Shanghai: ICMA, 216–20.Google Scholar
Ito, J. 2016. Extended Intelligence. https://pubpub.ito.com/pub/extended-intelligence (accessed 15 May 2019).CrossRefGoogle Scholar
Jones, D., Brown, A. R. and d’Inverno, M. 2012. The Extended Composer. In McCormack, J. and d’Inverno, M. (eds.) Computers and Creativity. Berlin and Heidelberg: Springer, 175204.CrossRefGoogle Scholar
Latour, B. 2005. Reassembling the Social: An Introduction to Actor-Network Theory. Oxford: Oxford University Press.Google Scholar
Licklider, J. C. R. 1960. Man-Computer Symbiosis. IRE Transactions on Human Factors in Electronics 1: 411.CrossRefGoogle Scholar
Manzelli, R., Thakkar, V., Siahkamari, A. and Kulis, B. 2018. An End to End Model for Automatic Music Generation: Combining Deep Raw and Symbolic Audio Networks. Proceedings of the 6th International Workshop on Musical Metacreation (MUME 2018). http://musicalmetacreation.org/mume2018/proceedings/Manzelli.pdf (accessed 27 November 2019).Google Scholar
Martindale, C. 1999. Biological Bases of Creativity. In Sternberg, R. J. (ed.) Handbook of Creativity. Cambridge: Cambridge University Press, 137–52.Google Scholar
McCormack, J. 2012. Creative Ecosystems. In McCormack, J. and d’Inverno, M. (eds.) Computers and Creativity. Berlin and Heidelberg: Springer, 3960.CrossRefGoogle Scholar
Meyer, L. B. 1983. Innovation, Choice, and the History of Music. Critical Inquiry 9(3): 517–44.CrossRefGoogle Scholar
Michalos, A. C. 1970. Book Review: The Sciences of the Artificial, by Herbert A. Simon. Technology and Culture 11(1): 118–20.CrossRefGoogle Scholar
O’Hear, A. 1995. Art and Technology: An Old Tension. Royal Institute of Philosophy Supplement 38: 143–58.CrossRefGoogle Scholar
Oliveros, P. 1974. Sonic Meditations. Baltimore: Smith Publications,Google Scholar
Reich, S. 1968. Pendulum Music. Vienna: Universal Edition, score UE16155.Google Scholar
Van den Oord, A., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., et al. 2016. WaveNet: A Generative Model for Raw Audio. arXiv preprint arXiv:1609.03499.Google Scholar
Varèse, E. and Wen-Chung, C. 1966. The Liberation of Sound. Perspectives of New Music 5(1): 1119.CrossRefGoogle Scholar
Verbeek, P.-P. 2008. Cyborg Intentionality: Rethinking the Phenomenology of Human-Technology Relations. Phenomenology and the Cognitive Sciences 7(3): 387–95.CrossRefGoogle Scholar
Xu, D, Wang, Y. and Bhattacharya, S. 2010. Thinking Beyond Means-Ends Analysis: The Role of Impulse-driven Human Creativity in the Design of Artificially Intelligent Systems. In Hart, D. N. and Gregor, S. D. (eds.) Information Systems Foundations: The Role of Design Science. Canberra: ANU E Press, 213–32.Google Scholar