Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations
This addresses a societal problem of gender bias in AI systems affecting children's development, but it is a position paper with no empirical results.
The paper argues that search and recommender systems may propagate gender stereotypes in children's products, particularly in educational settings, and proposes a research agenda to investigate this issue.
In this position paper, we argue for the need to investigate if and how gender stereotypes manifest in search and recommender systems.As a starting point, we particularly focus on how these systems may propagate and reinforce gender stereotypes through their results in learning environments, a context where teachers and children in their formative stage regularly interact with these systems. We provide motivating examples supporting our concerns and outline an agenda to support future research addressing the phenomena.