Scratch AI Extensions Tutorial: Build Your First AI Project (2026)

Scratch isn't just for simple animations anymore. With AI extensions powered by ml5.js and Google's Teachable Machine, kids can build projects that recognize faces, classify objects, respond to voice commands, and detect body movements — all using Scratch's familiar drag-and-drop blocks. Over 100 million kids use Scratch worldwide (MIT Media Lab, 2025), and AI extensions are the fastest-growing category. This tutorial walks you through 3 AI projects, from beginner to intermediate, in about 2 hours total.

What You Need

• A computer with Chrome browser (AI extensions work best in Chrome)
• A webcam (built-in or external)
• A microphone (built-in works fine)
• Scratch account (free at scratch.mit.edu) — optional but recommended for saving projects
• No coding experience needed!

Understanding Scratch AI Extensions

Scratch's AI capabilities come from community-created extensions that connect to machine learning models:

Extension	What It Does	Best For	Difficulty
ml5.js Image Classifier	Recognizes objects through webcam	"What is this?" games	Beginner
Teachable Machine	Train custom AI models	Gesture games, sound apps	Beginner
PoseNet	Detects body position/movement	Dance games, exercise apps	Intermediate
Speech-to-Text	Converts voice to text	Voice-controlled stories	Intermediate
Text-to-Speech	Makes projects talk	Interactive characters	Beginner

Project 1: AI Animal Identifier (Beginner — 30 minutes)

What you'll build: A project where kids show animals (toys, pictures, or real pets) to the webcam, and Scratch identifies what animal it is.

Step 1: Open Scratch with Machine Learning

1. Go to machinelearningforkids.co.uk — this site provides the easiest Scratch + AI integration
2. Click "Try it now" → "Log in" (create a free account or use as guest)
3. Click "Projects" → "+ Add a project"
4. Name it "Animal Identifier"
5. Choose "Images" as the recognition type

Step 2: Train Your AI Model

1. Click your project → "Train"
2. Create labels: "Dog", "Cat", "Bird" (or whatever animals you have)
3. For each label, add 10-15 images:
   • Click "Add example" → use webcam to take photos of toy animals
   • OR drag in images from the internet
4. Click "Back to project" → "Learn & Test"
5. Click "Train new machine learning model" — wait 1-2 minutes
6. Test it! Show an animal to the webcam and see if it's recognized correctly

Step 3: Build in Scratch

1. Click "Make" → "Scratch 3"
2. Scratch opens with special AI blocks already loaded
3. Build this script:

when green flag clicked
forever
  recognise image from camera (label)
  if <(label) = [Dog]> then
    say [That's a dog! 🐕] for (2) seconds
    play sound [dog bark]
  end
  if <(label) = [Cat]> then
    say [That's a cat! 🐱] for (2) seconds
    play sound [meow]
  end
end

4. Click the green flag and show animals to the webcam!

What Kids Learn

• AI needs training data (examples) to learn
• More examples = better accuracy
• AI can make mistakes when images are unclear

Project 2: Rock-Paper-Scissors Against AI (Beginner — 45 minutes)

What you'll build: Play rock-paper-scissors against the computer using hand gestures recognized by AI.

Step 1: Train Hand Gestures

1. Create a new project → Type: "Images"
2. Create 3 labels: "Rock", "Paper", "Scissors"
3. For each gesture, take 20 webcam photos from different angles
4. Train the model

Step 2: Game Logic in Scratch

when green flag clicked
say [Show your hand! Rock, Paper, or Scissors?] for (2) seconds
wait (3) seconds
recognise image from camera (player_choice)
set [computer_choice] to (pick random (1) to (3))

if <(player_choice) = [Rock] and (computer_choice) = [2]> then
  say [Paper beats Rock. Computer wins!]
end
... [continue for all combinations]

What Kids Learn

• AI can recognize visual patterns (hand shapes)
• Computer programs use logic (if/then) to make decisions
• Random number generation creates unpredictable opponents

Project 3: Body-Controlled Dance Game (Intermediate — 45 minutes)

What you'll build: A dance game where a character copies your body movements in real-time using PoseNet body detection.

Step 1: Set Up PoseNet Extension

1. Open Scratch at stretch3.github.io (enhanced Scratch with PoseNet)
2. Click "Add Extension" → "PoseNet2Scratch"
3. Allow webcam access when prompted

Step 2: Make a Character Follow Your Movements

when green flag clicked
forever
  set x to (nose x) * (2)
  set y to (nose y) * (2)
  if <(right wrist y) > (right shoulder y)> then
    switch costume to [hands-up]
    say [Hands up! 🙌]
  end
end

Step 3: Add Dance Challenges

Create a sequence of poses and challenge the player to match them:

• Hands up! ✋✋
• Touch your toes! 🦶
• T-Pose! ✈️
• Dab! 💃

The AI checks if the player's body position matches the target pose.

What Kids Learn

• AI can understand body position in 3D space (pose estimation)
• Real-time AI processing (the model runs continuously)
• Game design: how to turn AI capabilities into fun challenges

Troubleshooting Common Issues

Problem	Solution
"Webcam not working"	Check browser permissions (Chrome → Settings → Privacy → Camera)
"Model won't train"	Need at least 10 examples per label; check internet connection
"AI keeps getting it wrong"	Add more training examples, ensure good lighting, try different angles
"Extension not loading"	Use Chrome (not Safari/Firefox), clear cache, try incognito mode
"Scratch is slow"	Close other browser tabs, AI extensions use significant CPU

Next Steps After These Projects

Ready for more? Try these advanced Scratch AI projects:

1. Emotion Detector: Train AI to recognize happy, sad, surprised faces
2. Language Translator: Combine Speech-to-Text + Translation API + Text-to-Speech
3. Smart Pet Feeder Simulator: AI recognizes when your "pet" sprite is hungry based on time and activity
4. AI Music Composer: Use Scratch's sound blocks with AI-generated melodies

Frequently Asked Questions

Do Scratch AI extensions work on tablets?

Unfortunately, most AI extensions require Chrome on a desktop/laptop computer. The webcam and processing requirements are too heavy for tablets. Standard Scratch works on tablets, but AI features do not.

Are Scratch AI extensions free?

Yes, completely. Machine Learning for Kids, PoseNet2Scratch, and all Teachable Machine integrations are free. No paid tier exists. The only "cost" is a computer with a webcam.

Can my child share AI Scratch projects?

Projects using Machine Learning for Kids can be shared within that platform. Standard Scratch community sharing doesn't support AI extensions directly — the shared project won't include the trained model. Workaround: share a video recording of the project in action.

What age is best for Scratch AI?

Ages 8-9 for guided projects (with parent helping). Ages 10-12 for independent projects. Ages 13+ may want to explore more advanced tools (Teachable Machine standalone, Python ML). The AI concepts are the same regardless of tool — Scratch just makes them visually accessible.

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What Success Looks Like (And What It Doesn't)

Parents often measure AI education success by the wrong metrics. Here's a recalibration:

Success IS:

• Your child asks "how does this work?" instead of just using AI passively
• Your child can explain an AI concept to a friend or sibling in their own words
• Your child spots an AI-generated image or text without being told
• Your child chooses to use AI for creating, not just consuming
• Your child questions AI outputs: "Is this actually true?"

Success IS NOT:

• Your child uses AI tools for X hours per week (time ≠ learning)
• Your child can list 20 AI tools by name (knowledge ≠ wisdom)
• Your child gets A's by using AI for homework (grades ≠ understanding)
• Your child impresses adults by using "AI vocabulary" (jargon ≠ comprehension)

The 3-Month Challenge

Want to put this article into action? Here's a structured 3-month plan:

Month 1: Explore

• Try 2-3 different AI tools from this article
• Spend 15-20 minutes per session, 3-4 times per week
• Focus: What does my child enjoy? What frustrates them?
• Goal: Identify 1-2 tools that genuinely engage your child

Month 2: Build

• Settle on 1-2 primary tools
• Complete at least one structured project or challenge
• Start connecting AI learning to school subjects
• Goal: Your child creates something they're proud of

Month 3: Reflect

• Discuss what they've learned about AI (not just what they've done with it)
• Evaluate: Has their critical thinking about technology improved?
• Decide: Continue with current tools, try new ones, or adjust approach
• Goal: AI literacy becomes a natural part of your child's thinking, not just screen time

Expert Perspective

AI education researchers consistently emphasize three principles:

1. Process over product — How a child interacts with AI matters more than what they produce. A child who asks thoughtful questions learns more than one who generates impressive outputs.

2. Transfer over mastery — The goal isn't mastering one AI tool. It's developing thinking patterns that transfer to any tool, any technology, any future challenge.

3. Agency over compliance — Children who choose to use AI thoughtfully are better prepared than those who follow AI rules without understanding why.

These principles should guide every decision about AI tools, screen time, and learning activities.

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