Human-in-the-Loop (HITL)

Combining human judgment with AI for ethical, accurate outcomes

💡 Concept

Humans should validate, supervise, and correct AI predictions to prevent errors, bias propagation, or harmful outcomes. HITL balances automation with accountability.

🧩 Example: AI-Assisted Content Moderation

An AI flags potentially harmful content. A human moderator reviews these cases before publishing. This ensures accuracy and fairness while maintaining speed.

# Pseudo-code for HITL pipeline
ai_predictions = ai_model.predict(batch)
for item, prediction in zip(batch, ai_predictions):
    if prediction.confidence < 0.8:
        human_review(item)
    else:
        auto_publish(item)

✅ CTO Takeaway

Even with advanced AI, human oversight is essential for trust. Design pipelines where humans can intervene at critical decision points.