Fair ranking: a critical review, challenges, and future directions
GK Patro, L Porcaro, L Mitchell, Q Zhang… - Proceedings of the …, 2022 - dl.acm.org
Ranking, recommendation, and retrieval systems are widely used in online platforms and
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …
Fairness in information access systems
Recommendation, information retrieval, and other information access systems pose unique
challenges for investigating and applying the fairness and non-discrimination concepts that …
challenges for investigating and applying the fairness and non-discrimination concepts that …
Towards intersectionality in machine learning: Including more identities, handling underrepresentation, and performing evaluation
Research in machine learning fairness has historically considered a single binary
demographic attribute; however, the reality is of course far more complicated. In this work …
demographic attribute; however, the reality is of course far more complicated. In this work …
Reward reports for reinforcement learning
Building systems that are good for society in the face of complex societal effects requires a
dynamic approach. Recent approaches to machine learning (ML) documentation have …
dynamic approach. Recent approaches to machine learning (ML) documentation have …
Preference dynamics under personalized recommendations
S Dean, J Morgenstern - Proceedings of the 23rd ACM Conference on …, 2022 - dl.acm.org
The design of content recommendation systems underpins many online platforms: social
media feeds, online news aggregators, and audio/video hosting websites all choose how …
media feeds, online news aggregators, and audio/video hosting websites all choose how …
Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit
O Papakyriakopoulos, S Engelmann… - Proceedings of the 2023 …, 2023 - dl.acm.org
A significant share of political discourse occurs online on social media platforms.
Policymakers and researchers try to understand the role of social media design in shaping …
Policymakers and researchers try to understand the role of social media design in shaping …
Group fairness for content creators: the role of human and algorithmic biases under popularity-based recommendations
The Creator Economy faces concerning levels of unfairness. Content creators (CCs) publicly
accuse platforms of purposefully reducing the visibility of their content based on protected …
accuse platforms of purposefully reducing the visibility of their content based on protected …
[HTML][HTML] AI alignment: Assessing the global impact of recommender systems
L Bojic - Futures, 2024 - Elsevier
The recent growing concerns surrounding the pervasive adoption of generative AI can be
traced back to the long-standing influence of AI algorithms that have predominantly served …
traced back to the long-standing influence of AI algorithms that have predominantly served …
Introducing lenskit-auto, an experimental automated recommender system (autorecsys) toolkit
LensKit is one of the first and most popular Recommender System libraries. While LensKit
offers a wide variety of features, it does not include any optimization strategies or guidelines …
offers a wide variety of features, it does not include any optimization strategies or guidelines …
Manifestations of xenophobia in AI systems
Xenophobia is one of the key drivers of marginalisation, discrimination, and conflict, yet
many prominent machine learning fairness frameworks fail to comprehensively measure or …
many prominent machine learning fairness frameworks fail to comprehensively measure or …