Generative AI in Audio Education: Process-Centred Teaching for a Product-Centred World.

Ronan M. Generative AI in Audio Education: Process-Centred Teaching for a Product-Centred World. In: Convention Paper. Audio Engineering Society; 2025. Paper 10224. Available from: https://aes.org/publications/elibrary-page/?id=22906

@inproceedings{Ronan2025_22906,
  author = {Ronan, Malachy},
  title = {{Generative AI in Audio Education: Process-Centred Teaching for a Product-Centred World.}},
  note = {Paper 10224},
  year = {2025},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22906}
}

TY  - CPAPER
TI  - Generative AI in Audio Education: Process-Centred Teaching for a Product-Centred World.
AU  - Ronan, Malachy
M1  - Paper 10224
PY  - 2025
DA  - 2025/05/12
UR  - https://aes.org/publications/elibrary-page/?id=22906
PB  - Audio Engineering Society
LA  - en
AB  - Artificial intelligence (AI) tools are transforming the way music is being produced. The rate of development is expeditious, and the associated metamorphosis of audio education is abrupt. Higher-level education is largely built around the objectives of knowledge transmission and skills development, evidenced by the emphasis on learning in the cognitive domain in University programmes. But the cohort of skills that music producers will require in five years time is unclear, making skills-based curriculum planning challenging. This study investigates the integration of generative AI (GAI) tools into a music production module using a speculative design approach. Most integrations enhanced or transformed tasks, highlighting a shift from traditional production methods. Survey results showed limited student engagement with GAI tools and concerns about creativity, ethics, and the devaluation of process. While acknowledging the time-saving and iterative benefits of GAI tools, students emphasised the continued importance of foundational skills. The study highlights the pedagogical potential of GAI to support inquiry-based learning approaches, while also noting the risk of knowledge gaps if AI tools are over-relied upon. The study recommends a shift toward process-centred education, with curricula that incorporate authentic assessment, interdisciplinary learning, and critical engagement with AI to prepare graduates for evolving industry roles.
ER  -