Human in the Loop
What is human in the loop?
Human in the loop refers to a design approach where a human remains actively involved in reviewing, approving, or overseeing AI-generated outputs before they are finalized or delivered, rather than fully automating the process end-to-end. This approach allows AI to augment human capabilities rather than replace them entirely.
The concept applies to both evaluation processes—where humans review AI outputs to monitor quality—and production workflows—where AI assists human work but the human makes final decisions.
When should teams keep humans in the loop?
Keeping a human in the loop is particularly important for tasks where quality, accuracy, or appropriateness matter. For example, in customer service, an AI tool might help a support agent find relevant templates quickly, but the human remains responsible for the actual email content and quality of the response.
The decision depends on the stakes and quality requirements of the task. Teams often start with human-in-the-loop approaches when launching new AI features, then may gradually automate as they gain confidence in the system's reliability. However, for high-stakes decisions or quality-sensitive work, maintaining human oversight provides an essential safeguard.
What are human-in-the-loop evals?
In the context of AI product evaluation, human-in-the-loop evals refer to an evaluation approach where humans actively review traces and outputs to assess product quality. This involves manual inspection and annotation of AI responses as part of the evaluation process.
While human-in-the-loop evals provide valuable quality insights, they're less scalable than automated evals. Teams often use them in early development stages or to validate automated evaluation approaches before relying on them fully.
Learn more:
- Behind the Scenes: Building the Product Talk Interview Coach
- 21 Ways to Use AI at Work (And Build Your AI Product Toolbox)
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