




AI2: Lesson 4: Training AI and Bias The Importance of Data
Can your AI stay fair when the weather gets extreme?
Train your students to spot AI bias before it happens. This powerful KS3 / lower secondary computing lesson plunges students into the world of dataset fairness — showing how the data we feed an AI directly shapes its decisions.
Using a live (offline) simulation, learners modify unbalanced training data and observe changes to fairness and accuracy in real time. Tasks include an editable WeatherWise AI investigation, an extended design challenge to build a fair year-round dataset, and a class reflection on ethical design and real-world impact.
Through this, students uncover:
• How to identify bias and balance in an AI training dataset
• Why underrepresentation and overrepresentation affect model fairness
• How to justify dataset choices using real-world seasonal distribution
• What fairness means in practical, measurable terms — and why it matters
Files download instantly.
Pairs well with
A next-gen lesson that keeps your curriculum aligned with emerging trends in computer science
Built for formal scrutiny — structured around intent, implementation, and impact
Includes a full inspection-grade lesson plan
Packed with high-standard classroom activities — expertly designed and immediately classroom-ready
Includes full slide-by-slide speaker notes to support confident and consistent delivery
Keeps your curriculum sharp and future-facing — with topics that reflect today’s most relevant computing advances

AI2: Lesson 4: Training AI and Bias The Importance of Data
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Whats included:
Your digital download for this lesson contains 5 professionally organised folders, each containing matched teaching materials, student tasks, model answers, and full adaptations.
The lesson can be taught directly from the fully scripted presentation for confident, inspection-ready delivery.
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Cover / Independent work
Classroom Adaption Guide