2026
Towards an Ontology-Driven Approach to Document Bias (Abstract Reprint)
AAAI 2026technical
Machine learning (ML)-powered systems are capable of reproducing and often amplifying undesired biases embedded in society, emphasizing the importance of operating under practices that enable the study and understanding of the intrinsic characteristics of ML pipelines. This supports the emergence of