Episode 184: Artist Gender Representation in Music Streaming
Update: 2020-11-18
Description
Our guest this week is Avriel Epps Darling, researcher, entrepreneur and artist, and currently, a PhD student at Harvard's Graduate School of Education, seeking to make meaningful impact through researching how online, machine learning-driven ecologies influence youth of colour as they construct and affirm racialized and gendered identities.
Avriel has received numerous awards and honours including an invitation from the U.S. Department of Education to present her work for Congress as well as recognition as part of the top 10% of undergraduate social scientists in the world. Today, her research, in partnership with organizations such as Spotify and Snap Inc, focuses on the intersection of algorithmic bias in content recommendation systems, and racial identity development.
Topics explored included:
• Can you share more about your current research focus to start with?
• In your paper on Artist Gender Representation in Music Streaming, your findings show that about 1 in 5 streams go to female artists. How have music recommendations influenced this?
• What is the role of streaming services for challenging inequities by spotlighting underrepresented artists in their recommendations?
• Can you share more about your findings when researching the relationship between the proportion of female artists streamed on programmed playlists and the proportion of female artists listened to organically. And how this is impacted by the user gender and age?
• Can you share more on the challenges of gender labelling?
the challenges of gender labelling?
• What are the next steps for this research area?
• Has your background influenced your academic research?
• What advice would you give to anyone looking to get into a career in AI currently?
Inspired to explore further? View our upcoming event on Ethics & Social Responsibility here.
You can connect with Avriel via LinkedIn and Twitter.
Avriel has received numerous awards and honours including an invitation from the U.S. Department of Education to present her work for Congress as well as recognition as part of the top 10% of undergraduate social scientists in the world. Today, her research, in partnership with organizations such as Spotify and Snap Inc, focuses on the intersection of algorithmic bias in content recommendation systems, and racial identity development.
Topics explored included:
• Can you share more about your current research focus to start with?
• In your paper on Artist Gender Representation in Music Streaming, your findings show that about 1 in 5 streams go to female artists. How have music recommendations influenced this?
• What is the role of streaming services for challenging inequities by spotlighting underrepresented artists in their recommendations?
• Can you share more about your findings when researching the relationship between the proportion of female artists streamed on programmed playlists and the proportion of female artists listened to organically. And how this is impacted by the user gender and age?
• Can you share more on the challenges of gender labelling?
the challenges of gender labelling?
• What are the next steps for this research area?
• Has your background influenced your academic research?
• What advice would you give to anyone looking to get into a career in AI currently?
Inspired to explore further? View our upcoming event on Ethics & Social Responsibility here.
You can connect with Avriel via LinkedIn and Twitter.
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