85 citations · 98 across the 4 of their papers we have counts for
4 papers
RecSys Fairness Metrics: Many to Use But Which One To Choose?
Jessie J. Smith, Lex Beattie
In recent years, recommendation and ranking systems have become increasingly popular on digital platforms. However, previous work has highlighted how personalized systems might lea…
Fairness and Transparency in Recommendation: The Users' Perspective
Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus +2
Though recommender systems are defined by personalization, recent work has shown the importance of additional, beyond-accuracy objectives, such as fairness. Because users often exp…
Exploring User Opinions of Fairness in Recommender Systems
Jessie Smith, Nasim Sonboli, Casey Fiesler +1
Algorithmic fairness for artificial intelligence has become increasingly relevant as these systems become more pervasive in society. One realm of AI, recommender systems, presents…
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems
Masoud Mansoury, Himan Abdollahpouri, Jessie Smith +3
The proliferation of personalized recommendation technologies has raised concerns about discrepancies in their recommendation performance across different genders, age groups, and…