This article investigates how musicians engage with generative AI, reframing creativity as a negotiated space between human intention and machinic inference. Focusing on SUNO, a consumer-facing AI music platform, and based on interviews and focus groups with Milan-based musicians and record producers, the study combines post-phenomenology, actor-network theory, and STS perspectives in an empirically grounded analysis. It identifies three dynamics shaping emerging «algorithmic art worlds»: «algorithmic intimacy» captures estrangement-through-proximity, as musicians interpret opaque systems and experience creativity as both authored and alienated; «algorithmic conformity» shows how outputs default to Western aesthetics, constraining experimentation and reinforcing cultural hierarchies; «institutional unease» addresses disrupted evaluative frameworks, as musicians confront limits of authorship, legitimacy, and value in AI-mediated creation. Beyond technical capabilities, findings reveal how AI both enables and constrains creativity through reliance on structured datasets, underscoring the importance of embodied knowledge for cultural innovation and raising questions of diversity and institutional transformation.
AI and Creative Practice: Negotiating Agency, Diversity and Innovation in Algorithmic Cultural Production. A Study of SUNO
Massimiliano Raffa
2025-01-01
Abstract
This article investigates how musicians engage with generative AI, reframing creativity as a negotiated space between human intention and machinic inference. Focusing on SUNO, a consumer-facing AI music platform, and based on interviews and focus groups with Milan-based musicians and record producers, the study combines post-phenomenology, actor-network theory, and STS perspectives in an empirically grounded analysis. It identifies three dynamics shaping emerging «algorithmic art worlds»: «algorithmic intimacy» captures estrangement-through-proximity, as musicians interpret opaque systems and experience creativity as both authored and alienated; «algorithmic conformity» shows how outputs default to Western aesthetics, constraining experimentation and reinforcing cultural hierarchies; «institutional unease» addresses disrupted evaluative frameworks, as musicians confront limits of authorship, legitimacy, and value in AI-mediated creation. Beyond technical capabilities, findings reveal how AI both enables and constrains creativity through reliance on structured datasets, underscoring the importance of embodied knowledge for cultural innovation and raising questions of diversity and institutional transformation.
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