🟣 Year 6 Artificial Intelligence

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🎯 Aim

Today you will learn what Artificial Intelligence is, how AI systems use data to find patterns and make predictions, and why humans need to use AI responsibly.

🤖 Explain AI Explain what Artificial Intelligence is and identify examples of AI in everyday life.

📊 Understand Data Understand that AI systems use large amounts of data to find patterns.

🧠 Understand Limitations Recognise that AI can make mistakes and that its answers are not always accurate.

🌍 Use AI Responsibly Make sensible choices about when AI can be helpful and when humans need to check its work.

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💡 Be Inspired

Artificial Intelligence is already part of everyday life. It can help computers recognise pictures, understand speech, recommend videos, translate languages and answer questions.

Watch the video carefully. As you watch, think about this question: What makes Artificial Intelligence different from an ordinary computer program?

⭐ KEY IDEAS TO LOOK FOR

🤖 AI Can Learn from Data AI systems can use examples and data to find patterns.

🔎 AI Finds Patterns AI can identify patterns in information that help it complete a task.

🎯 AI Makes Predictions After finding patterns, an AI system can use them to make a prediction or decision.

⚠️ AI Can Make Mistakes AI does not automatically know that an answer is correct. The information it produces needs to be checked.

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👀 Check It Out

Let's take a closer look at how an AI system can use data, patterns and predictions.

Your teacher will demonstrate the process using simple examples. Watch carefully and think about what happens at each stage.

📊 1. DATA — An AI system is given examples and information to learn from.

🔎 2. PATTERNS — The system looks for patterns and relationships in the data.

🎯 3. PREDICTION — The system uses the patterns it has found to make a prediction or decision.

⚠️ 4. CHECK — A human checks the result because AI can be wrong, incomplete or misleading.

Remember: AI is a tool. It does not automatically understand whether something is true, fair, useful or appropriate. Humans are responsible for checking and using AI carefully.

🧠 THINK LIKE AN AI DETECTIVE

Is the information accurate? AI can produce incorrect information.

Where did the information come from? Think about the source of the information used by an AI system.

Could there be bias? AI systems learn from data created or selected by people, so the results can sometimes be unfair or biased.

Should a human check it? Important decisions and information should not simply be accepted because AI produced them.

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💻 Do It Yourself

Now it is your turn to explore how Artificial Intelligence can use data to find patterns and make predictions.

Complete the Code.org AI and Data activity. You will work through a series of challenges where you sort data, make predictions and discover how computers can learn from examples.

🤖 Your Challenge

Work through the Code.org activity carefully.

1. Explore the data — Look at examples that have already been sorted.

2. Find the pattern — Think about why the items have been placed into different groups.

3. Make predictions — Use what you have learned to predict where new items should go.

4. Test your thinking — Try sorting data yourself and see whether your partner can work out your rule.

📊 Think Like an AI

As you work, ask yourself:

What patterns can I see?
What information am I using to make my prediction?
What happens if I do not have enough examples?
Could my prediction be wrong?

🚀 Start the Code.org AI Activity

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⭐ Extension

Now think beyond the activity. You have seen how a computer can use examples to find a pattern and make a prediction. But what happens when the examples are limited or do not give the computer enough information?

🧠 The AI Training Challenge

Imagine you are training an AI system to sort objects into two groups.

You give the AI lots of examples and it finds a pattern. It then uses that pattern to make predictions about new objects.

Now imagine that you only give it a few examples, or that your examples are all very similar.

What could happen?

Think about:

• Could the AI find the wrong pattern?
• Could it make an incorrect prediction?
• Could it struggle with something it has never seen before?
• How could you improve the data you give it?

💡 Mini-Teacher Challenge

Explain to a partner why more useful and varied data can help an AI system make better predictions.

Then explain why more data does not automatically mean better data.

Try to use these words in your explanation: data, pattern, prediction, example and accuracy.

🔎 Think Like a Computer Scientist

A computer does not simply "know" the correct answer. It uses the information and examples it has been given.

If the examples are incomplete, limited or unhelpful, the pattern may not represent the real world accurately.

Good AI depends on good data and careful human thinking.

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🏆 Finished!

Well done! You have completed your Artificial Intelligence lesson.

You have learned that AI systems can use data to find patterns and make predictions, but that AI can make mistakes and needs responsible human users.

💭 Before You Leave...

🤖 What is Artificial Intelligence?

📊 How can data help an AI system find patterns?

⚠️ Why should we check information produced by AI?

🌍 What does it mean to use AI responsibly?

🎉 Ready for some fun?

Try your AI knowledge in the Train the TKA AI! challenge.

🎮 Train the TKA AI