131 citations · 132 across the 6 of their papers we have counts for
6 papers
Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systems
Yongsu Ahn, Quinn K Wolter, Jonilyn Dick +2
Recommender systems have become integral to digital experiences, shaping user interactions and preferences across various platforms. Despite their widespread use, these systems oft…
Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems
Yongsu Ahn, Yu-Ru Lin
Despite the benefits of personalizing items and information tailored to users' needs, it has been found that recommender systems tend to introduce biases that favor popular items o…
HungerGist: An Interpretable Predictive Model for Food Insecurity
Yongsu Ahn, Muheng Yan, Yu-Ru Lin +1
The escalating food insecurity in Africa, caused by factors such as war, climate change, and poverty, demonstrates the critical need for advanced early warning systems. Traditional…
VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions
Xian Teng, Yongsu Ahn, Yu-Ru Lin
Big data and machine learning tools have jointly empowered humans in making data-driven decisions. However, many of them capture empirical associations that might be spurious due t…
ESCAPE: Countering Systematic Errors from Machine's Blind Spots via Interactive Visual Analysis
Yongsu Ahn, Yu-Ru Lin, Panpan Xu +1
Classification models learn to generalize the associations between data samples and their target classes. However, researchers have increasingly observed that machine learning prac…
FairSight: Visual Analytics for Fairness in Decision Making
Yongsu Ahn, Yu-Ru Lin
Data-driven decision making related to individuals has become increasingly pervasive, but the issue concerning the potential discrimination has been raised by recent studies. In re…