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A branch of artificial intelligence that combines human and machine intelligence to create machine learning models. In a traditional HITL approach, humans are actively involved in a feedback loop, where they train, fine-tune, and test algorithms, ensuring that the model improves through human oversight and input. This collaborative process enhances the accuracy and effectiveness of the machine learning system.