Human-in-the-loop is a branch of AI that brings together AI and human intelligence to create machine learning (ML) models. It’s when humans are involved with setting up the systems, tuning and testing the model. This improves decision-making, and an actioning of the decisions it suggests. The tuning and testing stage is what makes AI systems smarter, more robust and more accurate through use.

With human-in-the-loop machine learning, businesses can enhance and expand their capabilities with trustworthy AI systems whilst humans set and control the level of automation. Simpler, less critical tasks can be fully automated, and more complex decisions can operate under close human supervision.

One of the key problems is that machine learning can take time to achieve a certain level of accuracy. It needs to process lots of training data to learn over time how to make decisions, potentially delaying businesses that are adopting it for the first time.

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