Human-in-the-Loop
What is Human-in-the-Loop?
Human-in-the-Loop is an AI design pattern where humans review and approve critical AI decisions before they're finalized. Instead of full automation, this pattern keeps humans as active participants who validate outputs and maintain control. It's essential for high-stakes decisions, situations requiring ethical judgment, or when building trust in new AI systems. Examples include Grammarly suggesting edits that you approve, content moderation tools that flag issues for human review, and medical AI that provides recommendations for doctors to confirm.
Problem
Fully automated AI systems risk critical errors and lack transparency. Users need review and override capabilities for safety and trust.
Solution
Design systems for human intervention, review, or approval of AI outputs. Provide clear handoff points, easy override mechanisms, and transparent explanations.
Real-World Examples
Implementation
AI Design Prompt
Guidelines & Considerations
Implementation Guidelines
Clearly indicate when human review is required or possible.
Facilitate easy override, correction, or feedback on AI outputs.
Log interventions for transparency and improvement.
Explain AI decisions to support human judgment.
Design workflows that minimize AI-human handoff friction.
Design Considerations
Balance efficiency with safety; too many interventions can slow workflows.
Avoid overwhelming humans with excessive review requests.
Address potential bias in AI and human decisions.
Provide training and support for users in review roles.
Monitor and refine human-in-the-loop trigger thresholds.