CCMSAI 2026

Current discussions of artificial intelligence in music often focus on AI-generated artifacts and whether machines can compose autonomously. This paper shifts attention from finished outputs to the broader creative workflow, asking how generative AI can participate in audiovisual composition without directly generating the final score. Through two practice-based case studies, this paper examines AI across conceptual development, prompt mediation, material generation, research, evaluation, and reflection. In the first case, conversational AI supported concept and prompt development, while an image-to-video system produced visual material that required substantial human editing before independently composed music was added. The second case examines a Dunhuang-inspired dance film in which AI supported cultural research, theoretical inquiry, and audiovisual ideation, while verification, composition, orchestration, synchronization, and aesthetic judgment remained human-directed. Drawing on human–AI co-creativity research, Vilém Flusser’s theory of technical apparatuses and play, and Michel Chion’s and Nicholas Cook’s theories of audiovisual relations, the paper proposes a shifting-role co-creative workflow. It argues that AI can shape composition before a single note is written, while artistic judgment, cultural responsibility, and final creative accountability remain human.

This paper examines AI-generated music as a twenty-first-century form of propaganda, analyzing how synthetic songs shape collective identity and political belonging without top-down institutional control. Focusing on the viral AI-generated song “We Are Charlie Kirk” and its accompanying YouTube video, I trace how AI tools construct an in-group world of Christian nationalist imagery, drawing on ethnomusicological and media theory frameworks alongside historical precedents in fascist radio broadcasting, Nazi martyrdom songs, and Cold War-era country music and Hollywood film. Using reverse-prompt research on the commercial platform Suno, I show how a simple prompt can generate a fully realized martyrdom ballad, revealing the racialized and class-coded assumptions embedded in AI music generation. I further show how ironic remixes and covers of the Kirk song, rather than subverting its message, extend its circulation and reinforce in-group and out-group dynamics. A comparative case study of Iranian-produced AI Lego-animation videos targeting American audiences demonstrates how the same techniques can be weaponized from outside a political community. Together, these cases suggest that AI music generation has collapsed the cost of producing emotionally persuasive, identity-forming media, enabling a decentralized form of participatory mythmaking that parallels, and extends, twentieth-century propaganda infrastructures.

This article reflects on “Duo Squared” and “Mirage,” two improvisational works that pair human musicians with AI-generated versions of themselves. Both works use Somax2, an interactive music system that recombines analyzed slices of audio corpora in response to live performers. Their bespoke corpora are drawn from the H2H Music Improv Dataset, specifically recordings of the participating musicians improvising together. Consequently, the systems reproduce not only each performer’s characteristic sounds and gestures, but also musical responses originally created in dialogue with a particular partner. Through practice-based reflection, the authors examine whether musical AI should resemble human collaborators, generate unfamiliar behavior, or operate as a reflective tool through which improvisers can interrogate their own creative practices. Performance experiences reveal moments in which distinctions between human and AI partners become difficult to hear, complicating perceived boundaries between performer, corpus, and system. The article argues that the value of bespoke-corpus improvisation lies not solely in successful human imitation, but in its capacity to expose what musicians recognize, expect, and value in interaction. It concludes by identifying further questions concerning corpus temporality, creative advancement, and the social dimensions that may be lost when AI substitutes for human collaborators.