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Human-in-the-loop (HITL) in artificial intelligence (AI) and machine learning (ML) is a collaborative approach that incorporates human expertise into the development and operation of ML systems. This integration aims to improve the accuracy, reliability, and adaptability of models by leveraging human input throughout the ML lifecycle.
The article discusses the challenges of bridging the gap between advanced AI tools and the everyday experiences of users who may not fully understand their potential. The author reflects on their own journey from skepticism to realization of AI's capabilities, emphasizing the importance of meeting users where they are in their workflows. - Many people struggle to grasp the benefits of new tools, often feeling disconnected from the advancements being showcased. - The author acknowledges their re...