AI Innovation Challenge · Week 1 of 4

Let's Build
Something Real.

For the next 4 weeks, your team will design an AI system, pitch it to the world, and compete for a real prize — having it actually built.

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The Prize

The top teams' ideas get built into a real, working AI system by your teacher. This isn't a class project — it's a product pitch.

Today's Session · 60 min

What We're Doing Today

0–10 minThe challenge brief + prize revealWhat you're building, how judging works
10–20 minWhat makes a great AI system idea?Criteria, examples, pitfalls
20–35 minTeam formation + brainstorm sprintStructured idea generation activity
35–50 minTeams share top ideasClass feedback, quick gut-checks
50–60 minIdea Brief intro + homeworkWhat teams submit by next class
Teacher: Keep energy high — this is their first impression of the challenge. Be enthusiastic about the prize.
The Challenge

How This Works

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Your Team

4–5 people. You'll work together across all 4 weeks to design and pitch one AI system idea.

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Your Idea

Any real-world problem you care about. Your AI system should solve it meaningfully — not just use AI for the sake of it.

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The Pitch

At the final exhibition, you present your idea to an audience. They vote. Judges score. Top 3 teams win.

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The Prize

Your teacher will build the winning idea into a real working AI system. Your concept becomes reality.

Pitch Requirements

What Your Pitch Must Cover

Every team addresses all 6 of these
1The Problem — What real issue are you solving? Who's affected and how badly?
2The AI Solution — What type of ML does your system use? Why that approach?
3Data & Bias — What data does it need? What biases could creep in and how do you address them?
4Ethics & Impact — What are the ethical risks? Who could be harmed? How is that mitigated?
5Limitations & Failures — When does your system break down? What are its known weaknesses?
6Future Work — If given more time/resources, what would you improve or expand next?
Teacher: This is the rubric backbone. Return to it every week.
Idea Quality

What Makes a Good vs Weak Idea?

✅ Strong Idea

Solves a real, specific problem someone actually has. The AI component is genuinely needed — not a gimmick. You can explain what type of ML it uses and why. You've thought about who could be harmed.

❌ Weak Idea

"An AI that does everything." Too vague. Or: "An app that uses AI to make life better." — What problem? For who? Or slapping AI onto something that doesn't need it.

✅ Strong Idea

Acknowledges its own limitations honestly. Shows awareness of training data requirements. Considers failure cases thoughtfully.

❌ Weak Idea

"Our AI will be 99% accurate and never make mistakes." Overconfidence is a red flag. No acknowledgment of bias, edge cases, or what happens when the system fails.

Teacher: Ask students: "Would this actually need AI, or could a simple app do it?"
The Golden Rule

Start With the Problem,
Not the Technology.

Don't say: "We want to build a neural network."
Say: "Students struggle to study effectively — here's how AI helps fix that."

💬 Quick Discussion — 5 minutes
  • What's one problem in your daily life that genuinely frustrates you?
  • What's one problem in your school, neighbourhood, or country?
  • Could AI realistically help — and why AI specifically?
Teacher: Cold call 3–4 students. Write ideas on the board to get momentum going.
Activity · 15 min

Team Brainstorm Sprint

1

Form your team (3 min)

4–5 people. Sit together. Choose a team name — something you'd actually put on a product.

2

Each person writes 3 ideas (5 min)

Individually and silently. One problem per sticky note / paper. No filtering — wild ideas are fine.

3

Share & cluster (4 min)

Each person pitches their 3 ideas in 30 seconds. Group similar ones together. Identify your top 2 as a team.

4

Pick your #1 (3 min)

Gut check: Can you explain the problem in one sentence? Is AI actually needed? Any obvious ethical issues?

Teacher: Circulate actively. Push teams who are stuck to think about local problems — school, Lebanon, their community.
Share Out · 15 min

Let's Hear Your Ideas

Each team: 30 seconds max.
"The problem is ____. Our AI system would ____. It would use ____ type of ML."

🎯 Class feedback prompts
  • Is the problem real and specific enough?
  • Does it actually need AI — or could a simpler solution work?
  • What data would this system need to learn from?
  • Who could be harmed if this system makes mistakes?
Teacher: Be encouraging but push them on vagueness. "That's interesting — what type of ML specifically?" is a great redirect.
Homework Due Next Class

The Idea Brief

Your team submits one shared document. Keep it short — this is a pitch, not an essay.

Idea Brief — 1 page, due next class
→Team name & members
→The problem — 2–3 sentences. Who has it, how bad is it?
→The AI solution — What does your system do? What type of ML? (classification, generation, recommendation, etc.)
→Who benefits — Your target users
→One concern you already have — Bias, ethics, data, or limitations

Use the student worksheet handed out today to draft this in class.

What's Coming

Your 4-Week Roadmap

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Week 1

Ideation & team formation. Submit your Idea Brief.

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Week 2

Design your AI system. Build your pitch deck.

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Week 3

Practice pitches. Peer feedback. Refine everything.

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Week 4

The Exhibition. Pitch to the world. Audience votes.

You have 4 weeks to take your idea from a thought to a full pitch. Make it count.