Human In Loop — Free AI Agents Tutorial
Learn Human In Loop in AI Agents with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Human In Loop in AI Agents with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
Written & reviewed by the Syllab.in Academic Team (CBSE/NCERT subject experts) · Updated
Human In Loop in AI Agents
Human-in-the-loop (HITL) means humans review and approve critical agent decisions. Agents recommend, humans decide. This combines agent efficiency with human judgment for safety and accountability.
Use cases: (1) High-stakes decisions (expelling student), (2) New situations (agent uncertain), (3) Ethical decisions (fairness trade-offs), (4) Learning (human feedback improves agent).
Workflow: Agent proposes action → Human reviews → Human approves/rejects → Agent learns from feedback. Iterative improvement through human oversight. Balance: too much human review slows system; too little risks bad decisions.
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