AI1: Lesson 4: Data is Power How AI Uses Information

Can you trust what the AI says - or is it just copying bad data?

This KS3 / lower secondary computing lesson shows students how AI makes decisions - and why data quality matters.

It starts with a fast-paced prediction challenge that reveals how AI systems use patterns in data to make recommendations. Then, students unpack the difference between raw data and meaningful information - and learn why poor data leads to poor outcomes.

Through two structured activities, students build and test their own datasets, identify flaws in broken examples, and explore what happens when AI is given unfamiliar or unbalanced data. Key ideas like bias, training data, and fairness are embedded throughout.

By the end of the lesson, students can explain how AI learns from data, why accuracy and diversity in datasets matter, and how to spot when an AI might be making unreliable decisions. A clear, practical step in developing critical digital thinking.

Through this, students uncover:

• How datasets and training data are used by AI to spot patterns and make predictions
• Why poor or biased data quality can lead to unfair or incorrect AI decisions
• What makes a dataset strong, fair, and useful for building smart AI

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