My new article "Discoverability and Algorithmic Recommendations in Video Streaming Platforms:Algorithmic Gender and Race Bias as a Canadian Broadcast Policy Concern" with Fizza Kulvi, Faiza Hirji, Manveetha Muddaluru, Emmanuel Appiah, Leandra Greenfield, Erica Rzepeci, and Christine Quail recently came out.
Our article examines discoverability and algorithmic recommendation systems in video streaming systems like Netflix or YouTube. We were particularly interested in looking at gender and race bias in algorithmic recommenders, and how concerns about those biases were seen:
1) by creators, policymakers, and industry members, and
2) by parliamentarians in debates about Canada's Online Streaming Act.
We found that while algorithmic video streaming recommenders are often portrayed as neutral and as responding to users' interests by parliamentarians and video streaming platforms, our interview participants - and research on recommendation systems - are far more skeptical.
