176 citations · 605 across the 32 of their papers we have counts for
7 papers · 1 filter
Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation
Michael D. Ekstrand
Recommender systems research is concerned with many aspects of recommender system behavior and effects than simply its effectiveness, and simulation can be a powerful tool for unco…
Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse
Ngozi Ihemelandu, Michael D. Ekstrand
This paper calls attention to the missing component of the recommender system evaluation process: Statistical Inference. There is active research in several components of the recom…
Estimation of Fair Ranking Metrics with Incomplete Judgments
Ömer Kırnap, Fernando Diaz, Asia Biega +3
There is increasing attention to evaluating the fairness of search system ranking decisions. These metrics often consider the membership of items to particular groups, often identi…
Overview of the TREC 2020 Fair Ranking Track
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand +2
This paper provides an overview of the NIST TREC 2020 Fair Ranking track. For 2020, we again adopted an academic search task, where we have a corpus of academic article abstracts a…
Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations
Amifa Raj, Ashlee Milton, Michael D. Ekstrand
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…
Fairness in Information Access Systems
Michael D. Ekstrand, Anubrata Das, Robin Burke +1
Recommendation, information retrieval, and other information access systems pose unique challenges for investigating and applying the fairness and non-discrimination concepts that…