MUSICAL TIME IN ALGORITHMIC AND AI-GENERATED MUSIC: FROM DETERMINISTIC TO EMERGENT TEMPORALITY
MUSICAL TIME IN ALGORITHMIC AND AI-GENERATED MUSIC: FROM DETERMINISTIC TO EMERGENT TEMPORALITY

Summary/Abstract: This article examines musical time in algorithmic composition and AI-generated music, focusing on the shift from deterministic algorithmic models of the twentieth century to emergent generative models of the twenty-first century. Musical temporality is considered as the outcome of computational procedures that organize musical processes through algorithmic and statistical models. The study employs a comparative analytical approach combining theories of musical time, research on algorithmic composition, and studies of artificial intelligence in music. Analysis of works by Lejaren Hiller and Leonard Isaacson, and by Iannis Xenakis shows that twentieth-century algorithmic composition produces a deterministic type of musical time characterized by procedural generation and structural fixity. In contrast, AI-generated music demonstrates an emergent temporality in which temporal structures arise during the generative process through probabilistic and data-driven models. The article proposes a conceptual distinction between deterministic algorithmic time and emergent AI-generative temporality, offering a framework for understanding the transformation of musical time in contemporary digital culture.

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