Introduction

How do recommendation algorithms produce new inequalities, or reinforce existing ones? It was with this question in mind that the Algo_Rhythms project was created, whose goal is to understand how algorithmic recommendations produced by music streaming platforms influence and are influenced by structural inequalities. This first edition was conducted by InternetLab with the support of Knowledge Equity Fund from Wikimedia Foundation. Here, based on a presentation of the general context of the discussions around algorithms and their impacts on society, we collected data, simulated uses of Deezer and Spotify and offered the public the possibility of doing their own search to find out:

1. i) After the first click on a song of your choice, which artists would be recommended to you;
2. ii) Which of these artists are white, black or indigenous? Which are women or men? Which are cis or transgender?
3. iii) Which of these artists have biographies on Wikipedia? And what is the relation of social markers of race, gender and sexuality and the greater or lesser presence of artists on Wiki?

The three questions raised above open up different possibilities of answers, crossing debates that are overlapped, but not directly connected. Debates about the formation of taste, the influences of streaming platforms, people’s modes of consumption and structural inequalities – such as those permeated by gender, race, ethnicity, territory and sexuality – intersect, but are not usually considered together. This is our goal: to unite debates once held in different spaces, thus making it possible to identify new horizons of research and discussion.

Knowledge Equity Fund

In 2020, the Knowledge Equity Fund was created to provide grants to external organizations that support knowledge equity by tackling racial injustices that limit access to and participation in free knowledge. This pilot initiative is part of the Wikimedia Foundation’s strategic direction, with Equity of Knowledge being one of the main pillars to achieve the vision by 2030. The fund invests in organizations working to address inequality and racial bias around the world, with the aim of aim of creating a more inclusive and representative future for free knowledge.

Learn more at: meta.wikimedia.org/wiki/Knowledge_Equity_Fund

Research team: Fernanda K. Martins, Alessandra Gomes, Stephanie Lima, Alice Lana
Communication: João
Collaboration: Francisco Brito Cruz, Mariana Valente