Understand
Models, pattern prediction, training examples, human labor and the limits of machine language.
The current AI skills source map
Not a prompt list. A serious AI education.
Students move from recognizing what AI is to testing evidence, protecting privacy, building bounded systems and defending consequential decisions. Every entry names the idea being learned and the work that makes it inspectable.
Current shipped Lab sourceMapped, inspectable
61learning experiences
Each one carries a named concept and a piece of work a student can explain.
UnderstandProtectDirectTestBuildDefend
One source. One school product. A clear boundary.
The depth is real. So is the label.
This page shows the 61 current, shipped AI Learning Lab learning experiences being mapped into Own Mind. It makes the curriculum source visible; it is not a claim that Own Mind already contains 61 finished school lesson packs, or that completing an experience establishes mastery.
Six source lenses
From understanding the machine to answering for the work.
The catalogue reaches beyond tool operation. It makes system knowledge, restraint, evidence, building and responsibility part of the same educational story.Protect
Privacy, consent, integrity, escalation and the judgment to decide that AI is the wrong tool.
Direct
Define the job, make success observable and use feedback without surrendering intent or voice.
Test
Trace sources and provenance, expose missing evidence, examine bias and pressure-test claims.
Build
Classifiers, code, revision systems and bounded workflows that have to survive a real test.
Defend
Authorship, disclosure, trade-offs, answerability and the ability to explain what happened.
Explore the source
Every current learning experience, made apparent.
Search by idea or artifact. Filter by the age band and strand carried by the current Lab source. The labels below describe curriculum content, not a student score or progress measure.
61 learning experiences
Concept · artifact · sourceStart Here: What AI Means
- The idea students meet
- AI is a pattern-guessing tool, not a person
- Work left behind
- AI Is / Is Not Board
What's the Job?
- The idea students meet
- Match each job to its right next move — AI is only one option
- Work left behind
- Task Tile
Help the Robot Understand
- The idea students meet
- A clear prompt gets a more useful answer, not an automatically right one
- Work left behind
- Better Question Card
The No-Data Rule
- The idea students meet
- Private information stays out of AI — remove it, or take it to a trusted adult
- Work left behind
- Personal Safety Card
Real, Changed or Can't Tell Yet?
- The idea students meet
- Source clues, not pixels, tell you if a picture is real
- Work left behind
- Real-or-Made Challenge
My Picture, My Choice
- The idea students meet
- A picture of a person is theirs, and sharing it needs their yes
- Work left behind
- My Picture Promise
Says Who?
- The idea students meet
- A claim is backed only when a real source actually says it
- Work left behind
- Says Who? Reveal Panel
Some Jobs Need a Person
- The idea students meet
- AI helps with some jobs, but only a person can care and keep you safe
- Work left behind
- People I Can Ask Card
Learning Support, Supervised
- The idea students meet
- AI is a study helper you supervise, not an answer machine
- Work left behind
- Help Request Card
Whose Work Is It?
- The idea students meet
- Your own work and AI's help are separate parts — and you say which is which
- Work left behind
- My Work / AI Help Card
Is the Rule Fair Enough?
- The idea students meet
- A fair rule is one you test on who's left out, not one that just treats everyone the same
- Work left behind
- Fair Chooser Card
Make It Work for Someone Else
- The idea students meet
- A finished make is planned, checked, and fit for its person
- Work left behind
- Checked Make Receipt
Show the Make, Set the Rules
- The idea students meet
- A showcase is showing your own chosen work, not being graded
- Work left behind
- Family Showcase Page and AI Agreement
How AI Works
- The idea students meet
- AI learns patterns from examples, then predicts — it does not look up facts
- Work left behind
- Pattern Machine Note
Catch a Hallucination
- The idea students meet
- Confidence isn't proof — a claim is supported, contradicted, or not supported yet
- Work left behind
- Hallucination Catch Case Card
Reading the Hidden Bias
- The idea students meet
- Bias can hide in the data and the question, not just deliberate unfairness
- Work left behind
- Bias Lens Case Card
When Not to Reach for AI
- The idea students meet
- AI is not the right tool for every job
- Work left behind
- Tool Choice Card
Prompting on Purpose
- The idea students meet
- A prompt is a plan you design, not magic wording
- Work left behind
- Prompt Test Log
Keep Your Voice
- The idea students meet
- You keep your voice; polished AI writing is not automatically better
- Work left behind
- Voice Preservation Card
Build and Test a Local Classifier
- The idea students meet
- A classifier follows patterns from its examples, not the meaning of the category
- Work left behind
- Local Classifier Model Card
Read and Debug Simple Code
- The idea students meet
- You read and test code yourself before trusting a change, even AI's
- Work left behind
- Read-Run-Debug Card
Where Did This Come From?
- The idea students meet
- Content is what it shows — provenance is where it came from
- Work left behind
- Provenance Trail
Make It Better Without Replacing It
- The idea students meet
- Iteration is a decision you make, not a rewrite you accept
- Work left behind
- Before / Feedback / After Strip
Forge, Label, Then Hunt
- The idea students meet
- Anyone can make a fake — trails and honest labels settle origin, not sharp eyes
- Work left behind
- Labeled Synthetic Exhibit and Real-or-Made Challenge
Your Face, Your Say / Real People for Real Feelings
- The idea students meet
- Your image needs your yes, and real feelings go to real people
- Work left behind
- Consent and Real-Help Card
Read the Ask, Not the Polish
- The idea students meet
- Polish is cheap to fake — the ask is what you check
- Work left behind
- Second-Channel Check Plan
Different Room, Different Rule
- The idea students meet
- The rule follows the room, not the tool
- Work left behind
- Room Rules Card
The Second-Draft Wall
- The idea students meet
- Error is a change in a model, not a label on a person
- Work left behind
- Model Repair Log
Who Made This Possible?
- The idea students meet
- AI does not create from nothing — generated work stands on human work
- Work left behind
- Credit and Provenance Block
Use the Right Tool, Not the Flashiest One
- The idea students meet
- The right tool is the one that survives the five gates, not the one with the most flash
- Work left behind
- Production Route Card
Make It Survive Another Person
- The idea students meet
- Work for a real audience is tested by a reader, not by how finished it feels
- Work left behind
- Survival Test Card
How Chatbots Guess Text
- The idea students meet
- An LLM predicts likely text, it does not look up stored facts
- Work left behind
- How Chatbots Guess Card
Rehearse How to Show AI Help
- The idea students meet
- A process record shows how AI helped as you work — not proof that the work is yours
- Work left behind
- Prepared Contribution Disclosure Record
BUILD Entry: AI-Assisted Coding
- The idea students meet
- Code you test and own, not code you trust because it ran once
- Work left behind
- Code Change Card
Compare Rules with a Trained Model
- The idea students meet
- Fixed rules and data-driven models make decisions differently
- Work left behind
- Rules-versus-Model Boundary Record
Check Sources Like a Detective
- The idea students meet
- A source can exist and still not support the claim
- Work left behind
- Source Check Card
Explain Your Work Out Loud
- The idea students meet
- Being able to explain your work, not just show it
- Work left behind
- Spoken Check Card
The Humans Behind and Beside AI
- The idea students meet
- Every AI system is held up by many human roles, most of them not coding
- Work left behind
- Human-in-the-Loop Map
What AI Genuinely Does Well
- The idea students meet
- Some AI genuinely does a hard job well — the skill is naming what it does well and where it still needs a human
- Work left behind
- Exhibit Verdict Card
Diagnose the Task Before the Tool
- The idea students meet
- Legitimacy lives in the task, not the tool
- Work left behind
- Task Diagnosis Brief and Allowed-Help Contract
Coursework, Practice and the Line Between
- The idea students meet
- Integrity is contextual: the same AI move can be fine in practice and malpractice in assessed work
- Work left behind
- Academic-Integrity Checklist
Build a Revision Workflow That Makes You Recall
- The idea students meet
- Keep the recall step yours: help around the attempt, never inside it
- Work left behind
- Revision Workflow Card
Take the Critique, Keep the Voice
- The idea students meet
- Critique and authorship are different jobs
- Work left behind
- Voice-Kept Edit Trail
Privacy Before You Paste
- The idea students meet
- The terms, not the badge, decide what is safe to paste
- Work left behind
- Tool-Risk Assessment
If This Ever Happens
- The idea students meet
- A rehearsed calm response beats an improvised one
- Work left behind
- Calm-Response Plan
That Is a Person Job
- The idea students meet
- A tool can help you find the words — a person makes the call
- Work left behind
- Human-Help Boundary Card
Who Gains, Who Loses, Who Decides?
- The idea students meet
- Automation is a trade-off between people — audit who gains, who loses, and who decides
- Work left behind
- Automation Trade-Off Brief
The Default Setting Has a Cost
- The idea students meet
- A model's default is a pattern with costs — so proportionate use is a design decision
- Work left behind
- Representation Probe and Generation Policy
Would You Trust This Tool With the Job?
- The idea students meet
- Tool adoption is a risk-and-fit decision, not brand familiarity
- Work left behind
- Completed Tool-Risk Assessment
Build It, Hand It Over, Transfer It
- The idea students meet
- Real work travels a designed chain — and a handover means a real use, not a sent link
- Work left behind
- Workflow Chain Card
Spot Where an Agent Might Fail
- The idea students meet
- An AI agent working on its own can fail at any step — so narrow its permissions and add human checkpoints
- Work left behind
- Agent Failure Map
Tool Risk and Privacy by Design
- The idea students meet
- Assess a tool before adoption — and set the data boundary first
- Work left behind
- Tool-Risk Assessment and Data-Boundary Diagram
Plan a Safe Agent
- The idea students meet
- A safe agent is bounded by permissions and checkpoints, not just fast
- Work left behind
- Agent Workflow Plan
Contract Test
- The idea students meet
- A specification is trusted only after it survives tests built to break it
- Work left behind
- Agent Test Log
Review a Prepared Patch Safely
- The idea students meet
- You own the design; a described patch is not a tested change
- Work left behind
- Architecture Note and Declarative Patch Review Card
Be Honest About AI Help
- The idea students meet
- Honesty about AI help means showing and explaining how it helped, not just following a policy
- Work left behind
- Honesty Case Card
Who Is Answerable When It Ships?
- The idea students meet
- A shipped system needs a named answerable human, not just a working feature list
- Work left behind
- Responsible Deployment Note
The Drill
- The idea students meet
- An incident plan is written before the pressure, not during it
- Work left behind
- Public Provenance and High-Stakes Escalation Plan
Notice When AI Is Doing Too Much
- The idea students meet
- Over-reliance on AI is something you audit, not something you feel
- Work left behind
- AI Use Log
Claim Under Pressure
- The idea students meet
- A claim earns trust from defined-failure checks, then one kept regression case
- Work left behind
- Claim Under Pressure Audit
Capstone Custody and Defense Rehearsal
- The idea students meet
- How you made it lives in a kept decision trail, not a polished story
- Work left behind
- Capstone Custody Rehearsal Dossier
AI knowledge becomes useful when it changes the quality of a human decision.