Humans in the loop is the difference between AI that works safely and AI that causes real damage. This video breaks down what it means, why it matters, and how to implement it.AI systems fail in three fundamental ways. They inherit biases from training data. They hallucinate, making up confident but completely wrong information. And they're sycophantic, prioritising agreeability over accuracy. When these systems run autonomously, the consequences can be costly and dangerous.This video walks through two real-world disasters: Air Canada's chatbot that invented a refund policy and lost in court, and a dealership chatbot that agreed to sell a Chevy Tahoe for $1. Both show what happens when AI acts alone.The solution is designing systems where humans guide, review, and override AI at critical points. You'll learn the ACA framework: Assess, Checkpoints, Accountability, for integrating AI where it adds value while protecting against risk.If you want to understand why AI behaves this way, watch the linked video WTF is an LLM Anyway. It explains hallucinations, bias, and sycophancy in plain English for non-technical people:

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