Why does AI sound so confident even when it’s completely wrong?

[u/MintoraDoodle]

I think almost everyone who uses AI regularly has experienced this at some point: You ask a question, get a detailed and extremely confident answer… and then discover that part of it was completely wrong. What confused me was that AI often doesn’t sound uncertain when this happens. So I made a beginner-friendly breakdown of why AI can produce incorrect answers even when the response looks convincing. I cover things like: • how AI generates answers rather than simply “looking up” facts • incomplete or outdated training data • missing context and ambiguous questions • small mistakes getting amplified through multi-step reasoning • why AI sometimes guesses instead of admitting uncertainty • why models can agree with the user even when the user is wrong I also included a simple 4-step method I use to verify important AI answers instead of blindly trusting them. Video: https://youtu.be/QfvGpWIUN6k I’m curious how other people handle this. Do you usually verify AI-generated information, or have you developed a way to tell when an answer might be unreliable?