4-5:07:Good Data, Good Decisions – Fairness and Accuracy

If you teach AI with bad examples, you get bad answers. Grades 4–5 take the Bias Challenge – can you guess correctly with missing data? – and learn to be fact checkers before they trust what AI says.

This is the curriculum’s first real look at AI ethics, pitched for 9–11 year olds: if the examples are unfair or incomplete, the AI is too. The fact-checker role gives them something practical to do about it.

What your child will do
• A story about an AI that kept making mistakes because it hadn’t seen enough good examples
• Interactive Bias Challenge: predict from incomplete, uneven data – does it feel fair or accurate?
• Becoming a Fact Checker: how to verify whether information is correct and complete
• Reflection: “Imagine an AI that helps choose who gets a prize. What data would it need to be fair to everyone?”

By the end, your child can
• Bias and missing data lead to unfair results
• Check facts before trusting AI output
• Why fairness matters to everyone

Learning focus (Fink’s Taxonomy of Significant Learning): Caring · Integration.

Interactive challenge with a reflection activity. Part of Grades 4–5: Mission: AI Explorers, Module 2 – How Does AI Learn? – Feeding the Machine Mind, Week 3. Next lesson: AI Learning Story – Roleplay and Comic Creation.