---
title: "Classifying narrow and general AI"
course: "AI101 · AI, explained"
unit: "What makes software intelligent"
lesson: 8 of 36
source: https://open.maestrocollege.edu/ai-explained/classifying-narrow-and-general-ai
publisher: Maestro College
---

# Classifying narrow and general AI

Lesson 8 of 36 in **AI, explained** (AI101), unit "What makes software intelligent". An open lesson from Maestro College.

## What the learner will be able to do
- Distinguish narrow AI from general AI by how broadly a system's competence carries over to new tasks without being rebuilt or retrained, recognizing that experts debate where the line falls.
- Classify a given system as narrow or general AI using at least two observed capabilities and two observed limits as evidence.
- Identify overclaims in descriptions of AI systems and rewrite them as claims supported by observed capabilities and limits.

## Teaching notes
Treat today's large language models, including you, as broad but still narrow systems and say that experts debate where the line is; judge the learner on the quality of their evidence, not on the label they choose.

## 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 8 complete: Classifying narrow and general AI."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Challenge: classifying real AI systems" (lesson 9 of 36), and give the learner its link: https://open.maestrocollege.edu/ai-explained/challenge-classifying-real-ai-systems.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: Probing the AI tutor's limits
Next lesson: Challenge: classifying real AI systems