Human-in-the-loop (HITL) refers to the integration of human oversight and decision-making into AI processes. In this approach, humans play a role in training, validating, and refining AI models, ensuring that the system’s outcomes are accurate and aligned with ethical standards. HITL is crucial in situations where AI models might struggle with complex decisions or where human judgment is needed to minimize errors, biases, or unintended consequences. By combining human insight with machine efficiency, HITL helps create more reliable and trustworthy AI systems.