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Human-in-the-Loop (HITL)

What Is Human-in-the-Loop (HITL)? The Simple Definition

A practice that ensures human oversight of an automated system. With human oversight, the observer can pause or adjust the model if the risks it poses are unacceptable.

The Technical Definition Of Human-in-the-Loop (HITL)

Human-in-the-Loop (HITL) is a framework in artificial intelligence and machine learning where human judgment is integrated into the iterative loop of a system’s workflow.

This approach involves a synergistic interaction between human operators and automated algorithms, where humans actively monitor, guide, or make decisions that affect the output or behavior of the AI system.

In HITL systems, humans may intervene to correct errors, provide nuanced feedback, or make complex decisions that the AI is not capable of handling independently, particularly in scenarios where the AI’s decisions carry significant risks or require ethical considerations. This human oversight ensures that the system remains aligned with desired outcomes and values, while also facilitating continuous learning and improvement of the AI model based on human input.

Explain It Like I’m Five

Imagine Human-in-the-Loop (HITL) is like playing a video game with a very smart robot.

The robot plays the game most of the time, but sometimes it’s not sure what to do next, or it might make a mistake. That’s when you, as the player, step in to help. You might press a button to fix a mistake or decide which way the robot should go. This way, the robot gets better at playing because it learns from your choices.

Use It At The Water Cooler

How to use “Human-in-the-Loop” in a sentence at work:

“At our next team meeting, we’ll discuss implementing a Human-in-the-Loop approach to enhance our automated customer service system, ensuring that our staff can step in and provide assistance when the AI encounters complex queries.”

Related Terms

Artificial Intelligence (AI), AEDT (Automated Employment Decisioning Tool), Predictive Models

Additional Resources

New York DFS AI Regulation, What Insurers Need To Know

New York DFS AI Regulation, What Insurers Need To Know

A must-read for insurance professionals. Instead of combing through pages and pages of legislation, this overview highlights everything you need to know. Understand fairness principles, and what is required for regulatory compliance for insurers licensed in New York. Stay informed about the best practices in AI governance to prevent discrimination and ensure transparency in insurance processes.

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