AI can sound completely confident... and still be completely wrong. Let's learn to catch it.
Below are 5 example answers an AI chatbot might give (these are illustrative examples, not a live chat). For each one, decide: does it look right, or does something need a check?
Notice that 2 of the 5 were totally accurate — AI isn't wrong about everything. The skill is knowing which kind of answer to double-check.
A hallucination is when AI states something false, confidently, and often in convincing detail — as if it were certain. Remember from Lesson 2: AI generates answers from patterns it learned, instead of looking facts up in a verified database. Most of the time, the pattern that fits is also true. But sometimes it isn't — and the AI has no built-in way of knowing the difference, so it says the wrong answer just as confidently as the right one.
AI can also show bias: since it learns from huge amounts of data made by people, it can pick up a narrow or one-sided view and state it as if it were settled fact — like calling one kind of pet "the best" for everyone. Bias can also mean treating one group of people unfairly compared to another. That can happen because the training data reflects old, unfair patterns from the real world.
The habit to build is "trust but verify": treat an AI's answer as a helpful starting point, not the final word. For anything that actually matters — homework facts, health questions, big decisions — double-check with another trusted source.
Think of a time someone (or something) sounded totally sure but turned out to be wrong. What happened?
This is saved right in this browser, on this device — it's never sent anywhere.
10 questions, picked at random from a bigger question bank — so if you take it again, you'll likely see a different mix. Let's go!
Time to generate your first AI image.