AI Constitution

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Education Concept Tracker

A prerequisite knowledge graph of 1590 learning concepts across 8subjects. Track what you've mastered and see exactly what you're ready to learn next — the topics whose prerequisites you've already met. Built on the Marble Open Skill Taxonomy.

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Knowledge-graph map

Learning to Learn
Mastered Ready to learn LockedHover a node for its description · click to open
Asking for HelpAsking for Help — frontier Ask for help when you've had a go yourself and are still stuck — knowing when to ask is a skill in itselfChecking Your Own WorkChecking Your Own Work — frontier After finishing a task, look back at what you did and ask yourself: does this seem right?Persisting When It's Ha…Persisting When It's Hard — frontier Keep trying when something feels hard — making mistakes and trying again is how learning happensFeeling of not understa…Feeling of not understanding — locked Notice the feeling of not understanding — recognise when something is confusing rather than reading or listening past itPlanning a TaskPlanning a Task — locked Make a simple plan before starting a task: what do I need to do, and what should I do first?Thinking Before StartingThinking Before Starting — locked Before starting something new, stop and think: what do I already know about this topic?Spotting PatternsSpotting Patterns — frontier Spot patterns and recurring structures — in numbers, words, nature, sounds, or events — and use them to make sense of new informationDescribing Rules & Patt…Describing Rules & Patterns — locked When you notice a pattern repeating, describe it as a rule that works every time — then test whether the rule holds in new casesLearning from MistakesLearning from Mistakes — locked When you get something wrong, investigate why — what did you misunderstand or overlook? Analysing errors is one of the most powerful ways to learnTransferring SkillsTransferring Skills — locked Recognise when a skill or strategy learned in one subject or situation can be applied in a completely different one
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Designing Fair AI Rules

Computing · Artificial Intelligence · conceptual

Design thinking applied to AI ethics: if you were designing an AI system, what rules would you give it? Who should it help? What should it not be allowed to do?

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What mastery looks like

  • Propose at least three rules for a hypothetical AI system they are designing
  • Explain why AI designers need to think about who might be harmed, not just who benefits
  • Describe one real example of AI being used responsibly and one where it was not

Check your understanding

If Designing Fair AI Rules was designing an AI assistant for their school, could they think of rules to make sure it was fair and helpful for everyone?

Prerequisites

Required first

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