---
title: "Why models hallucinate and show bias"
course: "AI103 · Prompting that works"
unit: "How LLMs work (and fail)"
lesson: 9 of 35
source: https://open.maestrocollege.edu/prompting-that-works/why-models-hallucinate-and-show-bias
publisher: Maestro College
---

# Why models hallucinate and show bias

Lesson 9 of 35 in **Prompting that works** (AI103), unit "How LLMs work (and fail)". An open lesson from Maestro College.

## What the learner will be able to do
- Understand that because an LLM optimizes for plausible continuations, fluent output is not verified output: each output is evidence to check, not a fact to trust.
- Identify hallucinations in sample outputs and trace each to a likely cause, such as missing knowledge, a knowledge cutoff, or pressure to give a plausible answer.
- Identify bias in sample outputs and trace it to patterns in pretraining data or choices made in post-training.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 9 complete: Why models hallucinate and show bias."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Context sensitivity and reasoning failures" (lesson 10 of 35), and give the learner its link: https://open.maestrocollege.edu/prompting-that-works/context-sensitivity-and-reasoning-failures.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: Sampling, temperature, and non-determinism
Next lesson: Context sensitivity and reasoning failures