AI in Music and Sound: Pedagogical Reflections, Post-Structuralist Approaches and Creative Outcomes in Seminar Practice

TL;DR

This paper describes a pedagogical approach to teaching AI in music, combining theoretical reflection and hands-on experimentation to foster technical skills, medium awareness, and critical literacy among students.

Contribution

It introduces a novel paired-études teaching method and design patterns for AI-music education rooted in medium theory and post-structuralist inquiry.

Findings

Students showed increased technical fluency and critical awareness.

The course fostered experimental methods and process-oriented listening.

Design patterns revealed new pedagogical strategies for AI in music.

Abstract

This paper presents a pedagogical and conceptual account of the course AI in Music and Sound: Modalities, Tools and Creative Applications, offered within the Music Informatics and Media Art module of an M.Sc. in Audio Communication. The course engaged students with a range of AI modalities such as symbolic composition, voice synthesis, timbre transfer, neural audio synthesis, and text-to-audio systems, combining theoretical reflection with practice-based experimentation. Its central pedagogical move is a paired-\'etudes design: each modality is approached first through its intended affordances and then through a deliberately reframed or "misused" exercise that surfaces representational limits and alternative behaviours. Framed by medium theory and post-structuralist inquiry, we treated AI as a transmodal conduit-a system that translates and perturbs musical signs across textual, symbolic, timbral and audio domains. Evidence from student work and reflection indicates growth in technical fluency, medium awareness, and critical literacy, alongside the cultivation of experimental method and process-oriented listening. The paper outlines the course architecture, assessment design, and representative projects, and distils a set of design patterns for AI-music pedagogy (eg., prompt-conditioned interplays and semantic destabilisation in text-to-audio; latent space materialism in timbre transfer). It concludes with pedagogical recommendations that integrate creative practice with medium awareness and with cultural-epistemic analysis of AI technologies, preparing students to participate in how AI is understood, developed, and deployed with creative communities.