Music metadata circulates through a standardized interconnection of databases among different stakeholders in the industry for a multitude of uses and functions, among which stands out the identification of works and copyright management. Today, Gender Metadata is not mandatory, there is no gender metadata in the industry and this has huge impact: without gender metadata, automated systems perpetuate existing biases and inequalities, impacting factors such as representation, compensation, and opportunities for female and gender diverse artists and creators, contributing to the amplification of gender biases within automated data processes and AI music recommendation applications.
We want to move forward towards the ideation of a data architecture that will include gender data. This is what we will be taklking about: the research we are conducting and the MUSIC GENDER METADATA.