Irina Tal

Understanding Fairness–Privacy Interactions in Graph Neural Networks: A Literature Review, Taxonomy, and Open Challenges

Graph Neural Networks (GNNs) are increasingly applied to socially consequential tasks, such as disease surveillance on contact graphs, and credit scoring and fraud detection on financial transaction networks. In these settings, biased or unfair predictions can restrict access to opportunities and resources, while priva...