Human-in-the-loop

Topic

Human-in-the-loop (HITL) is a model and process that integrates human interaction, judgment, and feedback into automated systems, simulations, or artificial intelligence workflows. It is widely utilized in machine learning to improve model training and accuracy, in modeling and simulation taxonomies, and in the supervision of autonomous systems. By combining human intelligence with machine efficiency, HITL aims to optimize decision-making and handle complex edge cases that automated systems cannot resolve alone.