Washington, DC 20057
United States
Georgetown University
Algorithmic fairness, Individual fairness, Ethics of AI, Incommensurable values
Explainability, Interpretability, XAI, Understanding, Idealization
Algorithmic Fairness, Algorithmic Bias, Fair Machine Learning, Group Fairness, Ethics of Artificial Intelligence
Rawlsian Fair equality of opportunity, Bayesian Networks, Aspirational Data