Designing Fair AI Designing Fair AI | AI Ethics + Bias | Lesson 1Quick View
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Designing Fair AI Designing Fair AI | AI Ethics + Bias | Lesson 1

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Essential question: How can AI be fair and unbiased? Learning focus: Define bias in AI and its impact. Identify bias examples in AI and effects. Suggest ways to reduce AI bias. What’s included: 1 fully planned lesson Canva-ready slide content included in the unit CSV workflow Hook, concept development, activity, reflection, and exit ticket Real-world example connected to the lesson topic Structured classroom activity Classroom activity: In groups or alone, design a simple AI system that avoids bias. Decide what data to use and how to check fairness.
Bias in Training Data and Fairness in AI – Digital Technologies Lesson 5Quick View
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Bias in Training Data and Fairness in AI – Digital Technologies Lesson 5

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This ready-to-use lesson explores bias in AI training data and the importance of fairness. Includes editable slides, lesson plan, activities, and teacher notes. Students will learn to explain bias, identify examples, and appreciate fairness in AI. Ideal for lower secondary teachers seeking clear, practical resources that reduce planning time. Part of the comprehensive Data Foundations unit.
How Recommendation Systems Use Your Data – Lesson 6Quick View
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How Recommendation Systems Use Your Data – Lesson 6

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No-prep lesson with editable slides and teacher notes explaining recommendation systems and data use. Students will understand how data personalizes online experiences. Ideal for lower secondary Digital Technologies classes. Included in the Data Foundations unit.
Designing Fair Data Collection – Lesson 7Quick View
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Designing Fair Data Collection – Lesson 7

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No-prep lesson with editable slides and teacher notes focused on fair and ethical data collection. Students will learn to design inclusive and respectful data collection methods. Suitable for lower secondary Digital Technologies classes. Included in the full Data Foundations unit.
Understanding Data Quality – Lesson 4Quick View
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Understanding Data Quality – Lesson 4

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Ready-to-teach lesson with editable slides and teacher notes that explain data quality issues. Students will define and identify noise, errors, and missing values in data and understand their effects. Suitable for lower secondary Digital Technologies classes. Included in the full Data Foundations unit.
Understanding Structured vs Unstructured Data – Lesson 3Quick View
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Understanding Structured vs Unstructured Data – Lesson 3

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No-prep lesson with editable slides and teacher notes on data types. Students will learn to distinguish structured and unstructured data and their importance in AI. Suitable for lower secondary Digital Technologies classes. Included in the Data Foundations unit.
What Counts as Personal Data? – Lesson 2Quick View
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What Counts as Personal Data? – Lesson 2

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Ready-to-teach lesson with editable slides and teacher notes on personal data. Students will identify personal data and understand its importance. Ideal for lower secondary Digital Technologies classes. Included in the Data Foundations unit.