Spotting Hallucinations, Bias & Fact Verification

Staying Safe in an AI-Driven World

While LLMs are immensely capable, they have critical limitations that every user must understand.

What is an AI Hallucination?

A hallucination occurs when an LLM confidently generates false, fabricated, or non-existent information (such as fake court cases, non-existent code libraries, or incorrect historical facts).

Golden Rules for AI Verification

1. Never Trust Unverified References: Always check cited links, package names, or legal cases independently.
2. Require Citations & Primary Sources: Ask the model "Provide official documentation URLs for any APIs referenced."
3. Use Retrieval-Augmented Generation (RAG) / Grounding: Provide authoritative source documents in your prompt and instruct the AI: "Answer ONLY based on the provided text."
4. Be Aware of Training Data Cutoffs: Standard models may not know about events or software updates that occurred after their training date.