Human in the Loop (HITL)

Human-in-the-loop (HITL) machine learning is a collaborative approach that integrates human input and expertise into the lifecycle of machine learning (ML) and artificial intelligence systems. Humans actively participate in the training, evaluation, or operation of ML models, providing valuable guidance, feedback, and annotations. Through this collaboration, HITL aims to enhance the accuracy, reliability, and adaptability of ML systems, harnessing the unique capabilities of both humans and machines.