Categorising Electronic Music

Abstract

When seemingly automated technologies display biases usually defined as discriminatory human behaviours, these tendencies are referred to collectively as ‘sociotechnical bias’. In this article, I explore facets of racial and gendered sociotechnical bias apparent in the musical categorisation strategies of the database Répertoire International de Littérature Musicale Abstracts of Musical Literature (1967–present only)—or RILM. The article shows how concerns about sociotechnical transparency raised in the digital humanities and computer science are also embedded in musical technologies to advocate for greater awareness and action regarding implicit biases currently operating in musical spheres. The article finds that shared technology among many kinds of electronic music facilitates a kind of musical ‘code-switching’ across genres that, if attuned to appropriately in database administration and keyword designations, would minimise racializing and gendering biases in electronic music categorisation.

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