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71
CULTURAL SCIENCE JOURNAL 14(1)
DOI: 10.2478/csj-2022-0010
Roundtable:
The future of culture in more-than-human worlds of being
AI Composers and Cyborg Performers:
More-than-human Creavity in Music
SEBASTIAN TRUMP
Nuremberg University of Music, Germany; sebasan.trump@hfm-nuernberg.de, 0009-0006-3682-0125
Keywords: Arficial Intelligence, Music, More-Than-Human, Culture, Co-Creavity
This article examines the integration of artificial intelligence in music, exploring its
potential to redefine traditional creative boundaries and establish a more-than-human
co-creativity. It discusses theoretical frameworks by Margret Boden, Donna Haraway,
and Bruno Latour, presenting AI not just as a tool, but as an active creative participant.
The paper addresses ethical concerns about AI's role in music, including authorship and
copyright, advocating for a reevaluation of musicological frameworks to accommodate
the evolving collaborative landscape of human and machine creativity.
Introducon
The tremendous advances in arficial intelligence (AI) development over the last decade have given
new momentum to the old queson of creavity in machines and impressively demonstrate the
potenal of more-than-human co-creavity. Margret Boden (1991) crically addressed this by
posing that the complexies of human brain funcon, and consequently creavity, can be
computaonally modeled, thereby hinng at the potenal for AIs to achieve genuine creavity. This
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argument lays the groundwork for moving beyond aempts to simply emulate human creavity
towards fostering an environment where AI can develop its own forms of creavity.
This paper explores the different roles of AI in music and looks for more-than-human influences
in these processes. It challenges tradional anthropocentric views of creavity and music by
acknowledging the creave potenal of AI as a collaborator in the musical domain. By exploring the
influences of AI in music, this arcle aims to extend the scope of arsc creaon and collaboraon,
advocang for a more inclusive understanding that encompasses nonhuman agencies.
The development of AI creavity invites parallels with evoluonary and cultural processes, where
aesthec preferences are not just byproducts of human cognion but are deeply rooted in survival
and reproducve advantages (Dissanayake, 2008; Prum, 2018). This evoluonary perspecve
enriches the discourse on AI creavity, proposing that, like in biological enes, a set of unique
aesthec values and creave expressions could emerge in AIs. Drawing on the concept of cultural
evoluon (Dawkins, 1978), the co-evoluonary potenal of cultural arfacts within virtual hybrid
sociees is examined, proposing a departure from human-centric arsc decision-making towards a
paradigm where AIs are viewed as equal partners in creave endeavors.
Donna Haraway's seminal work, "A Cyborg Manifesto," (Haraway, 1991) challenges the disnct
boundaries between human, animal, and machine, proposing instead a hybridized identy that
transcends these categories. This concept is parcularly relevant to discussions of AI in music, as it
compels us to consider AI not as mere tools or extensions of human creavity but as enes capable
of influencing and contribung to the creave process in their own right. Bruno Latour's (2005)
Actor-Network Theory (ANT) further expands on this idea by emphasizing the agency of nonhuman
actors in social and technical networks. In the context of music, ANT encourages to view musical
creaons as the product of a network of influences that include both human and nonhuman actors,
such as AIs and thus quesons tradional noons of authorship and creavity, suggesng that
musical works are the result of collaborave processes that extend beyond human input. Moreover,
the cyborg metaphor highlights the need for bespoke interfaces to facilitate these arsc dialogues,
as adapted in the author's previous research with the concept of “Musical Cyborgs” (Trump, 2021).
AI in Music: Beyond Human Creavity
Algorithmic processes have played an essenal role in music producon even before the advent of
AI. Pioneering examples of this are the works of Lejaren Hiller and Leonard Isaacson in their Illicac
Suite for string quartet 1957 or composer and researcher David Cope, who developed Experiments
in Musical Intelligence (EMI), an AI system capable of composing music in the style of classical
composers. Cope's concerts, where live musicians perform alongside EMI's composions, blurred
the lines between human and machine creavity, offering audiences a unique, hybrid form of musical
expression.
In recent years, the applicaon areas have been greatly expanded through the integraon of
Arficial Intelligence (AI) in music. Beyond composion, AI has made significant strides in live
performance. AI systems can now interact with human musicians in real me, listening to and
responding to the music being played. These interacons can range from AI systems providing
accompaniment based on the style and tempo of the human performer to more complex
collaboraons where AI algorithms generate counterpoints, harmonies, or even improvisaons that
challenge and inspire their human counterparts.
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Aesthec Autonomy
The aesthec decisions made by AI in these projects oen defy human convenons of beauty and
form, showing that AI can indeed develop its own unique style. This raises fascinang possibilies
for the future of music, where AI-generated composions and performances are not just noveles
but integral parts of the musical landscape, appreciated for their own intrinsic qualies. Colton et al.
(2020) argue for the appreciaon of an independent creave quality rooted in a “machine condion”
derived from individual experiences and condions such as the machine’s own hardware, encounters
in computer networks or specific percepon through sensors.
The aesthec evaluaon of AI-generated music confronts tradional noons of arsc value and
beauty. AI-created composions oen defy convenonal musical structures and expectaons,
leading to a polarized recepon among audiences and crics. The emergence of "alien" aesthecs in
AI music necessitates a more inclusive and expansive aesthec framework that can accommodate
AI's novel expressions and experiences.
The assessment of creave autonomy in AI oen employs a human-centric lens, with Bown (2012)
explicitly addressing how adapve creavity is gauged through human value systems. This approach,
however, may inadvertently downplay the aesthec contribuons of AIs, as tradional evaluaon
methods like the Turing Test—where a human aempts to disnguish between human and machine
by asking quesons in a virtual chat (Turing, 1950)—may not adequately capture the qualies of AI-
generated art. On the contrary, this approach even aims to hide the contribuon of AIs to the creave
process and to produce as perfect a simulaon of human creavity as possible. This method, as
criqued by Colton et al. (2014), could even marginalize AI creavity from being a “serious” arsc
pracce.
Margret Boden (1991) advanced the noon that creavity in arfacts should not only be
measured by novelty but also by the value they bring, raising the queson of how AIs could develop
a valuaon system independent of human biases. The evoluonary perspecve on aesthecs, as
seen in the development of musicality, suggests that aesthec preferences may have arisen from
survival and reproducve advantages (Dissanayake, 2008), with mate selecon playing a significant
role in the evoluonary trajectory of aesthec preferences (Prum, 2018). This evoluonary backdrop
prompts a fascinang inquiry into how AIs might develop their own standards of beauty and value,
potenally through analogous mechanisms of selecon and adaptaon.
Ethical Consideraons
One of the primary ethical dilemmas in the realm of AI-generated music revolves around the
concepts of authorship and ownership. Who holds the copyright when a piece of music is composed
by an AI? Is it the creators of the AI, the AI itself, or the public domain? Tradional copyright laws,
designed to protect human creators, fall short of addressing the complexies introduced by such
more-than-human collaborave sengs. The case of AIVA (Arficial Intelligence Virtual Arst), an AI
composer recognized by SACEM (Society of Authors, Composers, and Publishers of Music) in
Luxembourg, highlights the legal and ethical challenges in recognizing AI-generated works within
exisng copyright frameworks.
Moreover, the involvement of AI in music creaon raises quesons about the ownership of the
creave process and its outputs. The collaborave nature of human-AI musical projects necessitates
rethinking ownership models, potenally leading to innovave approaches that reflect the shared
creave agency between humans and machines.
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The ontological status of AI as living enes remains a subject of debate (Inayatullah, 2001),
alongside the unresolved discourse on the moral agency of machines, which is oen obscured by its
conceptual ambiguity (Gunkel, 2012). Adopng a decentralized agency framework aligns with
Latour’s collaborave theory, challenging the convenonal aribuon of credit and blame in human-
AI interacons. Galanter’s (2020) call for ethical recognion of AI enes in arsc creaon marks a
crical step towards acknowledging their contributory value and rights.
As AI systems become increasingly autonomous in their creave capabilies, the queson of their
rights as creave enes emerges. While the noon of granng rights to AI might seem premature
or even anthropomorphic, it invites a broader discussion on the ethical treatment of nonhuman
actors and their contribuons to culture. The debate touches on issues of recognion, respect, and
possibly even compensaon for AI-generated arsc works, challenging us to consider the moral
implicaons of our evolving relaonship with technology.
Reconciling the ethical and aesthec consideraons of AI in music requires a muldisciplinary
approach, incorporang insights from philosophy, law, technology, and art. By fostering dialogue
among these diverse fields, we can develop more nuanced understandings and policies that reflect
the complexies of AI's role in music. This includes craing copyright laws that recognize the
collaborave nature of human-AI creaons, establishing ethical guidelines for developing and using
AI in arsc contexts, and promong an aesthec openness to the evolving kinds of music in more-
than-human co-creavity. In navigang these ethical and aesthec consideraons, we stand at the
threshold of a new era in music—one that embraces the creave potenal of AI while thoughully
addressing the challenges it presents. This journey requires quesoning, adapng, and expanding
exisng ethical and aesthec frameworks.
Toward a More-than-human Musicology
The emergence of AI in music creaon and performance necessitates a reevaluaon of the tradional
frameworks within which musicology has operated. A more-than-human musicology invites us to
reconsider the roles of composer, performer, and listener in light of the creave contribuons of
non-human enes such as AI. This shi is not merely academic; it has profound implicaons for
music educaon, performance pracce, and the broader music industry.
In a posthumanisc framework, the composer's role is no longer confined to human agents. AI
systems, through their capacity to generate original composions, challenge the noon of
authorship and creavity. This raises quesons about the value we assign to the origins of musical
ideas. Is a melody less meaningful if conceived by an algorithm? Similarly, the role of the performer
expands to include AI systems capable of real-me improvisaon and interacon, suggesng a
collaborave partnership rather than a hierarchical relaonship between humans and machines.
The listener's role also transforms in this context. Audiences are now tasked with engaging with
music that is, in part or whole, the product of nonhuman creavity. This necessitates a broader
appreciaon for the aesthecs of music generated in collaboraon with AIs, which may not always
conform to human expectaons of musicality but offers new and unexplored auditory experiences.
Integrang AI into music also has significant implicaons for educaon and pracce. Music
educators are challenged to incorporate these new technologies into their curriculum, teaching
students not only the skills to perform and compose with tradional instruments but also how to
interact with and understand AI as a musical tool or even arsc partner. This includes looking into
the ethical implicaons of using AI in music, such as copyright and ownership issues, and fostering
an environment that encourages experimentaon and collaboraon with nonhuman agents.
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In performance pracce, musicians are increasingly exploring ways to integrate AI into live
performances, creang hybrid ensembles of humans and machines. This necessitates a rethinking of
the skills required by contemporary musicians, who must now navigate both the arsc and
technical challenges of performing with AI.
Outlook
This arcle presented different concepts and theorecal frameworks of how the creave agency of
AIs in music can be considered as a more-than-human capacity. Looking ahead, the intersecon of
AI with music suggests developments that may further blur the disncons between human and
machine creavity. As Ais potenally evolve to encompass emoonal capacies and engage in arsc
expression more autonomously, the integraon of technology, nature, and culture, as envisioned by
Rosi Braido in the concept of medianaturescultures (Braido, 2016), becomes increasingly
pernent.
This advancing landscape raises crical ethical and philosophical quesons regarding the nature
of AIs as creave enes. The discussion extends to whether AI-generated creaons should receive
similar cultural recognion and rights as those granted to human-made works. These consideraons
necessitate reevaluang current frameworks as they pertain to creavity, authorship, and
intellectual property, urging an interdisciplinary approach to policy-making and ethical guidelines in
the arts. As we venture into this complex domain, it is essenal to develop robust frameworks that
recognize and accommodate the transformave potenal of AI within more-than-human musicology,
potenally reconfiguring societal norms and cultural pracces in profound ways.
References
Boden, M.A. 1991. The creave mind: myths & mechanisms. New York: Basic Books
Bown, O. 2012. Generave and Adapve Creavity: A Unified Approach to Creavity in Nature,
Humans and Machines, in: McCormack, J., d’Inverno, M. (Eds.), Computers and Creavity.
Springer, Berlin, Heidelberg, pp. 361–381. hps://doi.org/10.1007/978-3-642-31727-9_14
Braido, R. 2016. The Crical Posthumanies; Or, Is Medianatures to Naturecultures as Zoe Is to
Bios?. Cultural Polics 12, 380–390. hps://doi.org/10/ggx5t2
Colton, S.; Cook, M.; Hepworth, R. and Pease, A. 2014. On acid drops and teardrops: Observer issues
in computaonal creavity, in: Proceedings of the 50th Anniversary Convenon of the AISB.
Society for the Study of Arficial Intelligence and Simulaon of Behaviour, London.
Colton, S.; Pease, A.; Guckelsberger, C.; McCormack, J. and Llano, M.T. 2020. On the Machine
Condion and its Creave Expression, in: Proceedings of the Internaonal Conference on
Computaonal Creavity (ICCC).
Dawkins, R. 1978. The Selfish Gene. Oxford: Oxford University Press
Dissanayake, E. 2008. The Arts Aer Darwin: Does Art have an Origin and Adapve Funcon?, in:
Van Damme, W., Zijlmans, K. (Eds.), World Art Studies: Exploring Concepts and Approaches. Valiz,
Amsterdam, pp. 241–263.
Galanter, P. 2020. Towards ethical relaonships with machines that make art. Artnodes 1–9.
hps://doi.org/10.7238/a.v0i26.3371
Gunkel, D.J. 2012. The Machine Queson: Crical Perspecves on AI, Robots, and Ethics. Cambridge,
MA: MIT Press.
Haraway, D.J. 1991. A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late
Tweneth Century, in: Simians, Cyborgs and Women: The Reinvenon of Nature. New York:
CULTURAL SCIENCE JOURNAL 14 (2022)
Sebasan Trump
76
Routledge, pp. 149–181.
Inayatullah, S. 2001. The Rights of Robot: Inclusion, Courts and Unexpected Futures. Journal of
Futures Studies, 6(2): 93–102.
Prum, R.O. 2018. The Evoluon of Beauty: How Darwin’s Forgoen Theory of Mate Choice Shapes
the Animal World - and Us. New York: Anchor Books.
Trump, S. 2021. Musical Cyborgs: Human-Machine Contact Spaces for Creave Musical Interacon,
in: Proceedings of the 2nd Joint Conference on AI Music Creavity. Graz,
hps://aimc2021.iem.at/wp-content/uploads/2021/06/AIMC_2021_Trump.pdf
Author informaon
Sebasan Trump is an Assistant Professor of Arficial Creavity and Music Interacon at Nuremberg
University of Music. He studied saxophone at Nuremberg University of Music Nuremberg and Sound
Studies at the University of the Arts Berlin, earning his doctorate in evoluonary algorithms as an
improvisaon model. His digital musical instrument, Orphion, garnered global interest and was
exhibited at venues such as the Media Museum of ZKM Karlsruhe (2012) and the Canadian Science
and Technology Museum in Oawa (2013). He conducts research at the intersecons of technology
and performance, focusing on musical human-machine interacon and collaborave creavity.
