Aiconomy

Human-in-the-Loop (HITL)

An AI design pattern where human oversight and decision-making are integrated into the AI system's workflow, ensuring humans can review, approve, or override AI recommendations before action is taken.

Human-in-the-loop is required by the EU AI Act for high-risk AI applications in healthcare, law enforcement, and employment. The approach is standard in medical AI (radiologists review AI findings), autonomous vehicles (safety drivers), and content moderation (human reviewers for edge cases). HITL reduces error rates — AI-assisted radiologists detect 20% more cancers than either AI or humans alone. However, automation bias can undermine HITL effectiveness: studies show humans tend to defer to AI recommendations even when they should not. Designing effective HITL systems requires careful attention to when and how humans are prompted to intervene.

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