Accepted Papers
Flexible Interpretability through Optimizable Counterfactual Explanations for Tree Ensembles
Ana Lucic, Harrie Oosterhuis, Hinda Haned and Maarten de Rijke
Evaluating Off-Policy Evaluation: Sensitivity and Robustness
Yuta Saito, Takuma Udagawa, Haruka Kiyohara, Kazuki Mogi, Yusuke Narita and Kei Tateno
Representational Harms in Image Tagging
Jared Katzman, Solon Barocas, Su Lin Blodgett, Kristen Laird, Morgan Klaus Scheuerman and Hanna Wallach
Independent Ethical Assessment of Text Classification Models: A Hate Speech Detection Case Study
Amitoj Singh, Jingshu Chen, Lihao Zhang, Amin Rasekh, Ilana Golbin and Anand Rao
Intersectional Bias in Causal Language Models
Liam Magee, Lida Ghahremanlou, Karen Soldatic and Shanthi Robertson
Enabling Flexible Downstream Fairness With Geometric Repair
Jessica Dai, Kweku Kwegyir-Aggrey, Keegan Hines and John Dickerson
Identifying Biased Subgroups in Ranking and Classification
Eliana Pastor, Luca de Alfaro and Elena Baralis
Evaluating Gender Bias in Hindi-English Machine Translation
Gauri Gupta, Krithika Ramesh and Sanjay Singh
Fairness for Text Classification Tasks with Identity Information Data Augmentation Methods
Mohit Wadhwa, Mohan Bhambhani, Ashvini Jindal, Uma Sawant and Ram Madhavan
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability
SĂlvia Casacuberta, Esra Suel and Seth Flaxman
An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness
Moninder Singh, Gevorg Ghalachyan, Kush Varshney and Reginald Bryant
Measurement as governance in and for responsible AI
Abigail Jacobs
Monitoring fairness in machine learning models that predict patient mortality in the ICU
Tempest van Schaik, Xinggang Liu, Louis Atallah and Omar Badawi
Registration Information: At least one author per submission is required to register for KDD (either full conference or workshops only) and attend the workshop.