Music recommendation algorithms that are unfair to women artists

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Nowadays more and more people are listening to music on streaming apps – by early 2020, 400 million people were subscribed to one. These platforms use algorithms to recommend music based on listening habits. Recommended songs can appear in new playlists or they can start playing automatically when another playlist is finished.

But what algorithms recommend isn’t always right. In a new study, we have shown that a widely used recommendation algorithm is more likely to choose music from male artists than from female artists. In response, we found a simple way to give more visibility to female artists.

The representation of women and gender minorities in the music industry is extremely low. About 23% of the 2019 Billboard 100 artists were women or gender minorities. Women make up 20% or less of recorded composers and songwriters, while 98% of works performed by large orchestras are by male composers.

This bias is also present in streaming services. A few female “superstars” dominate among the most popular artists, but most female and mixed artists are in the lower popularity levels. While the problem extends beyond the music industry, online music platforms and their algorithms that recommend music – called recommenders – play an important role.


Read more: Music streaming: Listening to playlists lowers the income of small artists


Our study

While previous studies have repeatedly asked consumers for their opinion, musical artists, those who provide the content, are seldom aware.

We wanted to highlight the artists. We asked musicians for their thoughts on what would make online music platforms more fair. When they said that the gender imbalance was a major problem, we decided to study it in more detail.

Our analysis of the listening behavior of around 330,000 users over nine years showed a clear picture – only 25% of artists ever listened to were female. When we tested the algorithm, we found that on average the first recommended lead was male, with the next six. Users had to wait until the seventh or eighth song to hear one from a female.

Apps like Spotify use algorithms to find recommendations.
Credit: Fixelgraphy