Artificial Intelligence and Music

The Artificial Intelligence and Music (AIM) working group promotes the collaborative development of a sustainable and interoperable data infrastructure for music research. While new technologies are transforming the field, progress is often hampered by fragmented datasets, limited reuse of models and standards, restricted access to data repositories, and complex ethical and legal issues surrounding data provenance and reuse.

Serving as an observatory and facilitator, AIM addresses these challenges by connecting and catalysing progress across three thematic hubs:

• Responsible Music AI, to foster sustainable practices and ethical reuse of music data for the development of AI models for music;

• Music Human-Computer Interaction (HCI), to support the design of interactive systems to experience, connect and explore music (data) in new ways;

• Musical Heritage, to facilitate the creation, interconnection, and analysis of digital music archives from tangible and intangible assets.

Our mission is to create a collaborative and interdisciplinary platform to build this shared infrastructure, sharing the know-how and experience from previous projects while aligning with current initiatives.

To achieve this, AIM identifies critical gaps in the research landscape. We develop community-driven repositories and best practices to support the creation and re-engineering of music collections, with a particular focus on empowering practitioners and stakeholders who may lack technical expertise. We focus on (meta)data models and tools that enable the implementation of FAIR principles in music research, thereby enhancing the accessibility, interoperability, and reusability of music data.