Ages 6–7

Ethical Inventors

A clever machine still needs a good heart to guide it.

Children learn what a "thinking machine" really is — a tool that follows instructions and learns from examples — and grapple with the big question: who is responsible for what it does? They solve multi-step problems and design fair rules for their own inventions.

👨‍👩‍👧 For parents: Your child meets technology and AI the right way — as powerful tools that a kind, responsible human must guide. They learn how machines "learn", who is responsible when one errs, and to ask "should we?" not just "can we?". This is digital wisdom for the generation that will shape AI, not be shaped by it.
STEM & LogicEthics & Values (Akhlaq)CognitiveInquiry-basedSocratic dialogueProject-basedUnplugged coding

10 · 2 · 45weeks · sessions/week · min/session

📅 Session plan📝 Observation log

Learning objectives

  • Explain in their own words that a machine learns from examples we give it. STEM & Logic · understand
  • Argue who is responsible when a machine makes a mistake, with a reason. Ethics & Values (Akhlaq) · evaluate
  • Break a hard problem into smaller steps (decomposition). Cognitive · analyze

Modules

What Does a Machine Know?

Big idea: A machine only knows what we teach it.

Responsibility / trust (Amanah)Humans carried the Amanah — the trust. A tool has no Amanah; the person using it does. (Surah Al-Ahzab 33:72)

Teach the Sorting RobotUnplugged coding · 20m

Children "train" a pretend robot (a friend) by showing examples of apples vs oranges, then test it.

▶ Show me how
  1. Experiment Show the robot 5 apples and 5 oranges. Now give it a tricky one — what does it guess, and why?
    Facilitator cue: When it errs, ask: "Did the robot do wrong, or did we teach it badly?" This is the core idea.

Who Is Responsible?

Big idea: Tools obey; people choose.

The Courtroom of KindnessSocratic dialogue · 18m

A short scenario: a delivery robot dropped a neighbor's gift. The class reasons out who should fix it.

▶ Show me how
  1. Discuss The robot dropped it — but who told the robot what to do? Who should say sorry?
  2. Reflect Could we make a rule so it does not happen again? Write our fair rule.

Invent It Right

Big idea: A good invention helps people and harms none.

Design a Helpful MachineProject-based · 25m

Teams decompose a real problem (e.g. remembering to water plants) and sketch a machine with a fairness rule.

▶ Show me how
  1. Challenge Break the problem into 3 small steps your machine must do. Then add one rule to keep it kind.
    Facilitator cue: Push for the "kindness rule" — every team must name a person their machine must never harm.
    Stretch: Add an "if it is unsure, then ask a human" rule.

Should We, Even If We Can?

Big idea: The human stays in charge of the machine — always.

🔬 Why this works: Ethical inquiry (P4C) applied to technology and AI literacy: children learn to separate "can we?" from "should we?" and to question a tool's authority. This is the direct lesson against being controlled by machines.

The Inventor's PauseSocratic dialogue · 22m

A clever tech could do harm; children reason out whether it should be used.

▶ Show me how
  1. Discuss A machine could do your friend's homework for them. Could it? Should it? Why not?
    Facilitator cue: Draw out the difference between capability and rightness. Let them wrestle with it.
  2. Challenge Write one rule for your invention that says when it must STOP — and ask a human.
    Stretch: Add: "If it is unsure, the human decides, not the machine."
  3. Reflect Who should always decide the important things — the machine, or the person? Why the person?

Leadership we plant

  • 🌱 Asks "should we?" — not only "can we?".
  • 🌱 Keeps the human in charge of the machine.
  • 🌱 Designs so that no one is harmed (la darar).

Research foundations

Philosophy for Children (P4C) — ethical inquiry
Moral reasoning grows through structured dialogue around real dilemmas.
In practice: Courtroom-of-kindness scenarios and the "should we?" pause.
AI literacy — "humans in control" (CSforAll / MIT-style)
Children should understand machines learn from human-given examples and stay human-governed.
In practice: Training a pretend sorting robot, then ruling on its mistakes.

🏡 Try at home

Should We, Even If We Can? · 10 min

At dinner, pose one "could vs should" question ("A robot could do homework — should it? Why not?"). Let your child reason it out; there is no single right answer.

Teach the Machine · 12 min

Play "robot": your child gives you example after example to "train" you to sort fruits, then tests you with a tricky one. Ask: did the robot fail, or did we teach it badly?

Standards alignment

ISTE Standards for Students
Digital Citizen & Computational Thinker
Responsible technology use and how learning systems work.
UNESCO — AI Competency Framework for Students
Human-centred AI & AI ethics
Keeping humans in control and reasoning about AI’s impact.
CASEL — Social & Emotional Learning
Responsible decision-making
Weighing consequences and acting ethically.

Value anchors

  • Trust & responsibility (Amanah)
  • Doing no harm (La darar)There should be neither harm nor reciprocating harm — our inventions follow this rule too. (Sunan Ibn Majah)

Everything you’ll need (home or school)

  • Fruit picture cards, scenario cards, design paper, markers
  • Picture cards of fruits (some tricky: a red orange!)
🖨 Printable checklist

Assessment — portfolio

  • emerging: States that machines follow instructions.
  • developing: Explains learning-from-examples and decomposes a problem.
  • confident: Defends who is responsible and proposes a fairness rule.

Future skills

AI literacyDigital ethicsComputational thinkingProblem solvingLogical reasoning
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