{"id":1224,"date":"2026-06-22T16:18:39","date_gmt":"2026-06-22T13:18:39","guid":{"rendered":"https:\/\/www.al-manafeth.com\/?p=1224"},"modified":"2026-06-22T16:33:37","modified_gmt":"2026-06-22T13:33:37","slug":"redefining-creativity-the-impact-of-artificial-intelligence-on-music-composition-and-production","status":"publish","type":"post","link":"https:\/\/www.al-manafeth.com\/?p=1224","title":{"rendered":"Redefining Creativity: The Impact of Artificial Intelligence on Music, Composition, and Production"},"content":{"rendered":"

Redefining Creativity: The Impact of Artificial Intelligence on Music, Composition, and Production<\/strong><\/p>\n

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Dr. Marie Abou Jaoude[1]<\/a><\/strong><\/p>\n

Lynn Zaghloul<\/strong>[2]<\/strong><\/a><\/p>\n

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\u00a0<\/strong>Abstract<\/strong>
\nThis study examines how artificial intelligence (AI) is reshaping musical creativity across composition, production, and audience perception. Drawing on cognitive science, neuroscience, classical theories of creativity, and design thinking, the research investigates whether AI functions primarily as a technical extension of human creativity or as an emerging creative collaborator. Using a mixed-methods design that combines surveys, listening experiments, and semi-structured interviews with 100 participants aged 18 to 50, the study reveals a complex and evolving relationship between human and algorithmic creativity. While participants recognize AI\u2019s effectiveness in melody generation, production support, and personalized recommendation, emotional depth, intentional originality, and authentic artistic expression remain strongly associated with human agency. Interviews with professional musicians further indicate that AI is valued as a source of inspiration and efficiency rather than as a replacement for human creativity, alongside persistent concerns regarding authorship and professional identity. Overall, the findings suggest that AI does not displace musical creativity but rather reconfigures it as a hybrid process in which human intuition and algorithmic generation interact. This hybrid model challenges traditional definitions of musical creativity and highlights the relevance of design studies for understanding creative practices in human\u2013AI systems.<\/p>\n

Keywords:<\/strong> Artificial intelligence; musical creativity; composition and production; design thinking; human\u2013AI interaction; audience perception.<\/p>\n

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Introduction<\/h2>\n

Music has long functioned as a central mode of human expression, mediating emotion, identity, memory, and culture. Across history, technological developments, from notation systems and mechanical instruments to recording technologies and digital audio workstations, have continually reshaped musical practices without fundamentally displacing human creativity. In recent years, however, artificial intelligence (AI) has introduced a qualitatively different shift. Contemporary AI systems are no longer limited to assisting production or distribution; they increasingly participate in generative processes traditionally associated with human composition, raising profound questions about creativity, authorship, and artistic agency.<\/p>\n

AI-driven music systems, such as Google\u2019s Magenta, OpenAI\u2019s MuseNet, and AIVA, \u00a0are now capable of generating melodies, harmonies, arrangements, and even full compositions across multiple genres (Google Magenta Team, 2016; OpenAI, 2019; AIVA Technologies, 2016). These developments challenge long-standing assumptions that creativity is an exclusively human capacity grounded in intention, emotion, and lived experience. As machine-learning models analyze vast musical datasets and produce stylistically coherent outputs, the boundaries between tool, collaborator, and creative agent become increasingly blurred. This transformation raises a fundamental question: How should musical creativity be understood in contexts where human and algorithmic processes are deeply intertwined<\/strong>?<\/strong><\/p>\n

While existing scholarship has explored AI\u2019s technical capabilities in music composition and production, less attention has been paid to how creativity itself is being redefined through human\u2013AI interaction. In particular, there is a need to examine how musicians and listeners conceptualize creativity in AI-assisted music, how they evaluate emotional authenticity and originality, and how these perceptions relate to broader theoretical models of musical creativity. Addressing these issues requires moving beyond purely technological assessments toward an interdisciplinary framework that integrates creativity theory, sociocultural perspectives, and empirical inquiry.<\/p>\n

Accordingly, this study adopts an empirically informed conceptual approach<\/strong> to investigate how artificial intelligence is reshaping musical creativity in the realms of composition, production, and listening practices. Rather than asking whether AI can be creative in a human sense, the study examines how creativity is redistributed across hybrid systems involving human intention, algorithmic generation, and cultural interpretation. Empirical data are used not to measure creativity as an isolated variable, but to interrogate and refine existing theoretical understandings of creativity in music.<\/p>\n

The central research question guiding this study is: How is musical creativity being redefined through human\u2013AI interaction in music composition and production?<\/strong><\/p>\n

To address this question, the study explores four sub-questions:<\/p>\n

    \n
  1. How do audiences and professional musicians conceptualize creativity in AI-assisted music?<\/li>\n
  2. To what extent is AI perceived as a technical tool, a creative collaborator, or an autonomous agent?<\/li>\n
  3. Which dimensions of musical creativity (emotional, technical, aesthetic, and social) are perceived as most affected by AI involvement?<\/li>\n
  4. How do these perceptions challenge or extend human-centered theories of musical creativity?<\/li>\n<\/ol>\n

    The study employs a mixed-methods design combining surveys, a listening experiment, and semi-structured interviews with musicians and listeners. By situating empirical findings within contemporary theories of creativity, AI, and design thinking, the research contributes to ongoing debates about hybrid creativity and the evolving relationship between humans and intelligent technologies in artistic domains. A literature review will be the main pillar to answer these questions.<\/p>\n

    1. Musical Creativity in the Age of Artificial Intelligence: Theoretical Perspectives<\/h2>\n

    This chapter will examine classical and contemporary theories of musical creativity, and consider how these frameworks intersect with recent developments in AI. This theoretical inquiry is central to understanding how AI reshapes creative agency, authorship, and meaning within contemporary musical practices.<\/p>\n

    1.1 Musical Creativity as Plural and Situated<\/h3>\n

    Contemporary research increasingly conceptualizes musical creativity as a plural, situated, and socially embedded phenomenon rather than a singular cognitive trait. Burnard\u2019s influential framework of musical creativities<\/em> emphasizes that creativity manifests differently across contexts, practices, and cultural settings, encompassing professional composition, improvisation, everyday music-making, listening, and technological mediation (Burnard, 2012, pp.3-7). From this perspective, creativity is not limited to the act of composing original works but includes interpretive, curatorial, and experiential dimensions.<\/p>\n

    This plural understanding is particularly relevant in digital environments where listeners actively engage with music through playlists, recommendation systems, and interactive platforms. Such practices complicate traditional distinctions between creator and consumer, suggesting that creativity may emerge across a network of actions involving selection, recombination, and interpretation. In the context of AI-generated music, these dynamics invite reconsideration of where creativity is located and how it is recognized.<\/p>\n

    1.2 Human-Centered Models of Musical Creativity<\/h3>\n

    Classical theories of creativity have largely emphasized human cognition, intentionality, and emotional engagement. Boden\u2019s model of creativity (1998, pp. 347-350), which distinguishes combinational, exploratory, and transformational creativity, has been particularly influential in framing creative processes as operations within conceptual spaces. In music, such processes are closely linked to cognitive expectations, emotional resonance, and embodied performance.<\/p>\n

    Psychological and neuroscientific research further reinforces the human-centered view of creativity. Studies in the psychology of music highlight the role of affect, memory, anticipation, and reward in musical experience, while neuroscientific research associates musical creativity with distributed neural networks involved in prediction, emotion, and motor coordination (Daikoku, 2025; Villarreal et al., 2013). These perspectives underscore the deeply embodied and affective nature of musical creativity, often positioning it as inseparable from lived human experience.<\/p>\n

    William Forde Thompson (2014, pp.28-29) notes that creativity in music arises from complex interactions between cognitive processing (expectations, schemas) and emotional responses. This provides a comprehensive framework situating creativity within the psychology of music perception and affect. Daniel Levitin (2006, pp.185-195) further argued that musical creativity emerges from the interplay of memory, expectation, and pleasure, with music engaging brain networks responsible for prediction and reward. Such models foreground creativity as an embodied and affective process, raising critical questions about how creativity should be understood when musical outputs are generated or mediated by non-human systems.<\/strong><\/p>\n

    However, the emergence of AI-generated music places pressure on strictly human-centered models. When listeners perceive algorithmically generated music as coherent, aesthetically engaging, or emotionally evocative, questions arise as to whether creativity should be defined by internal experience, observable output, or cultural interpretation.<\/p>\n

    1.3 Artificial Intelligence and Computational Creativity in Music<\/h3>\n

    The growing field of computational creativity explores the extent to which machines can produce outputs that are novel and valuable within a given domain. In music, AI systems based on deep learning architectures have demonstrated remarkable capacity for generating stylistically consistent compositions by learning statistical patterns from large datasets (Colton et al., 2011). Reviews of AI-based music composition highlight both technical advances and conceptual limitations, particularly regarding originality, intentionality, and emotional depth.<\/p>\n

    Importantly, recent scholarship suggests a shift away from asking whether AI is creative toward examining how creativity emerges through hybrid systems<\/strong>. AI-generated music is increasingly understood as the product of interactions between human design choices, training data, algorithmic processes, and cultural frameworks of evaluation. From this perspective, AI does not replace human creativity but participates in its reconfiguration.<\/p>\n

    1.4 Post-Human and Distributed Creativity<\/h3>\n

    Post-human and sociomaterial theories offer further tools for understanding creativity in AI-mediated contexts. Scholars working in this tradition argue that creativity is distributed across networks of humans, technologies, cultural norms, and institutions. Actor\u2013Network Theory, in particular, conceptualizes non-human entities as actants<\/em> that shape outcomes without possessing intention or consciousness (Latour, 2005, pp. 10-11; Suchman, 2007, pp.238-239).<\/p>\n

    In music, this approach has been used to examine how technologies mediate creative practice, authorship, and aesthetic values. Applying this lens to AI suggests that creativity may be understood as an emergent property of human\u2013machine assemblages rather than as an attribute of a single agent. This perspective aligns with recent discussions of co-creation, shared authorship, and hybrid agency in both music and design studies (Galanter, 2012; Boden & Edmonds, 2009).<\/p>\n

    1.5 Conceptual Framework<\/h3>\n

    Drawing on these perspectives, the present study conceptualizes musical creativity as a multidimensional construct<\/strong> comprising:<\/p>\n