AI literacy activities for History lessons

• Source evaluation is AI literacy: the questions pupils ask of Cold War propaganda (who made this, why, and what is missing) are the questions to ask of AI output.
• Pupils sort images by their own rules, then see that machine learning classifies in the same way and inherits the same bias from its examples.

• Machine learning: a type of AI that learns patterns from examples instead of following fixed rules.
• Training data: the examples an AI learns from. If the examples are biased, the AI will be biased too.
• Algorithmic bias: unfair results from an AI system caused by flawed data or design choices.
• Classification: sorting things into categories, which both people and AI do.
• Pattern recognition: spotting regularities in information. People do it naturally; AI does it at scale.

• UNESCO: question the ethics of AI systems and the data behind them.
• OECD/EU AI Literacy: design an AI system and weigh the trade-offs it creates.
• PISA 2029: identify bias in AI outputs and the examples behind them.
• Anthropic AI Fluency: use discernment and diligence before trusting AI output.

Illustrative links. A generated guide gives the detailed mapping for your lesson and region.

• The Industrial Revolution was the last time technology changed how people work so completely. Pupils already weigh automation, working conditions and who benefits: the same questions society asks about AI.
• Judging whether a factory owner’s account is reliable is the same analysis pupils need for AI output: who made it, why, and what is missing.

• Algorithm: a set of step-by-step instructions for a task, like a factory production line.
• Automation: using machines or computers for work people used to do, like spinning jennies replacing hand spinners.
• Bias: a one-sided view from a system or source, like a factory owner writing about working conditions.
• Pattern recognition: spotting something that repeats or follows a rule.

• UNESCO: apply ethical reasoning to how AI is governed and designed.
• OECD/EU AI Literacy: consider how AI should be managed and held accountable.
• PISA 2029: evaluate the credibility of AI-generated content.
• Anthropic AI Fluency: use discernment to tell human and AI-generated content apart.

Illustrative links. A generated guide gives the detailed mapping for your lesson and region.