Human-in-the-Loop (HITL) is a critical approach in AI development where human feedback is integrated into the training, testing, and fine-tuning processes of machine learning models. Especially in complex or high-stakes applications, HITL ensures higher accuracy, ethical alignment, and contextual relevance by involving human judgment at key stages. In the era of Generative AI, HITL helps mitigate biases, refine outputs, and maintain quality control. For companies like Macgence, HITL enhances data annotation and model performance, making AI systems more robust, reliable, and trustworthy. It bridges the gap between human expertise and machine efficiency in real-world AI solutions.

https://macgence.com/blog/...