A review on fairness in machine learning
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
Feedback loop and bias amplification in recommender systems
Recommendation algorithms are known to suffer from popularity bias; a few popular items
are recommended frequently while the majority of other items are ignored. These …
are recommended frequently while the majority of other items are ignored. These …
Managing popularity bias in recommender systems with personalized re-ranking
Many recommender systems suffer from popularity bias: popular items are recommended
frequently while less popular, niche products, are recommended rarely or not at all …
frequently while less popular, niche products, are recommended rarely or not at all …
Controlling fairness and bias in dynamic learning-to-rank
Rankings are the primary interface through which many online platforms match users to
items (eg news, products, music, video). In these two-sided markets, not only the users draw …
items (eg news, products, music, video). In these two-sided markets, not only the users draw …
The unfairness of popularity bias in recommendation
Recommender systems are known to suffer from the popularity bias problem: popular (ie
frequently rated) items get a lot of exposure while less popular ones are under-represented …
frequently rated) items get a lot of exposure while less popular ones are under-represented …
Algorithmic fairness
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …
Measuring the business value of recommender systems
Recommender Systems are nowadays successfully used by all major web sites—from e-
commerce to social media—to filter content and make suggestions in a personalized way …
commerce to social media—to filter content and make suggestions in a personalized way …
Beyond-accuracy: a review on diversity, serendipity, and fairness in recommender systems based on graph neural networks
By providing personalized suggestions to users, recommender systems have become
essential to numerous online platforms. Collaborative filtering, particularly graph-based …
essential to numerous online platforms. Collaborative filtering, particularly graph-based …
Questioning racial and gender bias in AI-based recommendations: Do espoused national cultural values matter?
One realm of AI, recommender systems have attracted significant research attention due to
concerns about its devastating effects to society's most vulnerable and marginalised …
concerns about its devastating effects to society's most vulnerable and marginalised …
What are you optimizing for? aligning recommender systems with human values
We describe cases where real recommender systems were modified in the service of
various human values such as diversity, fairness, well-being, time well spent, and factual …
various human values such as diversity, fairness, well-being, time well spent, and factual …