> Related Topics: Privacy and Surveillance, Ethical Computing and Practice
Author: Leslie Kaelbling, Serena Booth, Marion Boulicault, Dheekshita Kumar, Rodrigo Ochigame
Keywords: machine learning; bias and fairness in machine learning; data bias; model bias
Resources:
Lab 1: Good Hypotheses: Beyond Accuracies (PDF)
Lab 2: Fairness in ML “How do we evaluate fairness of a model?” (PDF)
Lab 5: Social Utility “Benefits and Drawbacks of Intentionally Biasing a Model” (PDF)
Lab 9: Word Embeddings “Challenges with Word Embeddings in the Wild” (PDF)
