Human Disagreement

Human disagreement, a ubiquitous phenomenon across diverse tasks like visual question answering and semantic textual similarity, is increasingly recognized as a valuable data source rather than mere noise. Current research focuses on understanding the causes and patterns of disagreement, developing methods to model the distribution of human responses (rather than just averages), and incorporating this uncertainty into machine learning models. This work is crucial for improving the accuracy and reliability of AI systems, particularly in applications requiring nuanced understanding of human judgment and subjective interpretation.