Artificial Intelligence and the Rewriting of Musical Memory: A Cognitive Perspective

The intersection of artificial intelligence (AI) and music is redefining the construction, preservation, and perception of musical memory. This study investigates how AI-generated compositions interact with human cognition and reshape our understanding of cultural continuity in music. Anchored in cognitive musicology and memory theory, it adopts a qualitative-computational framework to explore how algorithmic systems simulate and reinterpret traditional musical structures. Focusing on the Ottoman-Turkish makam tradition as a case study, the research compares AI-generated pieces with historically grounded compositions, analyzing their melodic contours, modal progressions, and formal architectures. The methodology combines structural music analysis, listener response studies, and computational profiling of AI models. Findings indicate that while AI can effectively reproduce surface-level features of traditional music, it often lacks the nuanced emotional and cultural depth embedded in human compositions. Listener responses reveal cognitive dissonance when AI-generated works deviate subtly from familiar modal logics, highlighting the complex interplay between form, memory, and authenticity. The study also engages with broader theoretical discourses in digital aesthetics and posthumanism, arguing that AI’s role in music extends beyond imitation. It positions AI as a co-author in the evolving ecology of musical memory an entity capable of both continuity and disruption. By articulating a model of hybrid authorship and distributed memory, the study challenges traditional notions of creativity, heritage, and authorship in the digital age. This research contributes to interdisciplinary discussions on the future of cultural heritage, offering critical insights into how emerging technologies reshape the way we remember, transmit, and reinterpret music.