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Do streaming algorithms contribute to inequality in music?

Women and gender minorities might be getting less exposure.

Algorithms represent invisible forces shaping human lives, often without us realizing it. They shape whether people get credit loans, get accepted into prestigious universities, or how expensive their house or car insurance is.

Habits of media consumption and listening to music are no exception to this rule. Taste and preferences are shaped by invisible and complex rules on which recommendation engines of music streaming platforms are built. This might lead to joyful discoveries of incredible music, such as when a mysterious algorithm helped Japanese ambient music to resurface on the YouTube platform. 

However, there’s a dark side to relying on algorithmic music recommendations. According to a short research paper ‘Break the Loop: Gender Imbalance in Music Recommenders’ first published this Spring as a conference proceedings, the female and gender minorities are being less recommended on various streaming platforms than their male counterparts. Researchers discovered that “users had to wait until song seven or eight to hear one by a woman” when listening to recommended tracks.

This trend is damaging to both artists and listeners. Artists are gaining less exposure which might lead to less opportunities and financial gains, while listeners are not exposed to diverse music enough.

In the upcoming episode of the IMPAKT TV on 7 October, in collaboration with the Dutch Media Week, we will talk about what’s changed because of algorithms in the music world, and the role streaming services and we the listeners – the consumers – play in all of this. Are we now more free or less free to shape our own taste? We will discuss this with two special guests: Wilbert Mutsaers, head of Spotify Benelux, and Christine Bauer, lecturer on Human-Centered Computing at Utrecht University. 

The event will be live-streamed for free at Planet IMPAKT and is part of the programme of the Dutch Media Week in Hilversum. 


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