📘 Chapter 2: How It Works (No Coding Required)
🧠 What Powers AI?
You don’t need to be a programmer to understand how AI works. The key is knowing that AI systems follow instructions, learn from examples, and make predictions based on patterns in data.
Think of it like teaching a robot by showing, not telling.
⚙️ Key Concepts Explained Simply
| Term | What It Means in Plain English | Example |
|---|---|---|
| Algorithm | A set of instructions a computer follows | A recipe for making decisions |
| Model | The “brain” of an AI that’s trained to do a task | A model that recognizes cats in photos |
| Training Data | Information used to teach the AI how to do something | Thousands of photos labeled “cat” or “not cat” |
AI gets smarter over time by adjusting its models based on feedback — just like you learn from making mistakes.
💡 Real Life Comparison
Imagine you’re learning to tell the difference between muffins and chihuahuas. You look at hundreds of photos, sometimes mess up, then get better the more examples you see. AI does the same thing — but faster, with more data.
🔍 Types of AI “Thinking”
- Rule-Based AI: Follows strict if-this-then-that logic (like an old calculator)
- Machine Learning (ML): Learns from examples and updates its model as it gets new data
- Deep Learning: A type of ML that mimics the brain with “neural networks” — great for images, speech, and language
🧪 Try It Yourself
Draw a Decision Tree!
Create a flowchart for something you decide every day.
Example:
“Should I eat a snack?” → “Am I hungry?” → “Is it healthy?” → “Do I have time?”
This is how AI often breaks down choices — into small yes/no steps.
🛠️ Project Idea
Mini-Project: Interview + Reflection
- Interview a friend, parent, or teacher:
“What do you think AI is? How do you feel about it?” - Write or record a reflection:
- What did you learn from their answers?
- Were their ideas different from yours?
- How did it help you better understand AI?
Optional: Turn your interviews into a short podcast or slideshow for class.
🧾 Quick Recap
- AI works by learning from data — not just following rules
- Machine Learning is the most common form of AI today
- You can think about AI using real-world examples and decisions
- Everyone understands AI differently — and that’s okay
🔗 Next Up: Chapter 3 – Ethics + Bias