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    Human in the Loop (HITL)

    Human in the loop (HITL) is a process in which human experts actively contribute to the development and training of an artificial intelligence (AI) solution.

    What Is Human in the Loop (HITL)?

    AI technologies learn and grow based on the data they’re fed. Put in bad data, and you get bad outputs. Human in the loop (HITL) is the process of optimizing machine learning technology by ensuring human experts are actively involved in the curating, reviewing, and annotating data for AI. HITL is inherently an iterative process. Human agents input data into the AI, then the AI analyzes and learns from that data to serve up relevant outputs. Then, human experts review the outputs and adjust datasets to optimize results. This feedback loop provides oversight and interaction that benefits both parties: Humans can ensure the accuracy of AI models and results, while AI can receive better-quality data to learn from. HITL is a more expansive version of active learning, as it encompasses various feedback systems, yet it achieves similar results: better inputs and better outputs.

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