Fairness for niche users and providers: algorithmic choice and profile portability

• URL: http://arxiv.org/abs/2509.22660v1
• Date: Thu, 28 Aug 2025 07:38:59 GMT
• Title: Fairness for niche users and providers: algorithmic choice and profile portability
• Authors: Elizabeth McKinnie, Anas Buhayh, Clement Canel, Robin Burke,
• Abstract summary: We study the impact of algorithmic pluralism on the recommendation ecosystem.<n>Prior work has shown that niche consumers and (especially) niche providers benefit from algorithmic choice.<n>We explore how different policies regarding the handling of user profiles interact with fairness outcomes for consumers and providers.
• Score: 0.7711381100220001
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Ensuring fair outcomes for multiple stakeholders in recommender systems has been studied mostly in terms of algorithmic interventions: building new models with better fairness properties, or using reranking to improve outcomes from an existing algorithm. What has rarely been studied is structural changes in the recommendation ecosystem itself. Our work explores the fairness impact of algorithmic pluralism, the idea that the recommendation algorithm is decoupled from the platform through which users access content, enabling user choice in algorithms. Prior work using a simulation approach has shown that niche consumers and (especially) niche providers benefit from algorithmic choice. In this paper, we use simulation to explore the question of profile portability, to understand how different policies regarding the handling of user profiles interact with fairness outcomes for consumers and providers.

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