A special case of machine learning in which a learning algorithm can interactively query a user to obtain the desired outputs at new data points.
Active Learning reduces the cost of data labeling. Instead of having human experts review every document, the system identifies the edge cases it is least certain about and routes only those to people for labeling, which shortens the training loop.
See also Large Language Model, Fine-Tuning and Model Inference.