Grade 6 · AI and Energy

AI Uses Energy Too:
Energy Sources, Carbon Impact, and Scale

Two Grade 6 lessons that help students distinguish energy use from carbon impact and understand how small AI actions become large systems when repeated at scale.

Grade 6
Energy sources
Carbon impact
Scale

Big idea for Grade 6

The environmental impact of AI depends not only on how much energy it uses, but also on where that energy comes from, how often AI is used, and whether the use creates meaningful value.

Energy use
Energy source
Carbon impact
Scale

Classroom message

Think beyond the prompt. Consider the system, the source of energy, and the scale of use.

Unit purpose

Helping students connect AI use with energy systems and scale

This Grade 6 mini-unit deepens students’ understanding of AI’s environmental footprint by distinguishing between energy use and carbon impact.

Students learn that the same AI task may have different environmental consequences depending on the electricity source, the efficiency of the system, the type of task, and the scale of use.

Lesson 1: Energy Use vs. Carbon Impact

Students understand that AI uses energy, but its carbon impact depends partly on how that energy is produced.

Learning goal

Students distinguish between energy use and carbon impact in AI systems.

Key message

Energy use and carbon impact are connected, but they are not the same thing.

Duration

45–50 minutes.

Materials

Board or chart paper, markers, student worksheet or paper, pencils, sticky notes, and optional energy source cards.

The energy chain

From AI prompt to carbon impact

Energy use tells us how much electricity is used. Carbon impact tells us how much greenhouse gas pollution may be created because of producing that electricity.

AI prompt
Data center
Electricity grid
Energy source
Carbon impact

Lesson flow

  • 1
    Opening question: Ask whether two computers using the same electricity always create the same carbon impact.
  • 2
    Build the energy chain: Connect AI prompt, data center, grid, energy source, and carbon impact.
  • 3
    Energy source sorting: Students sort energy sources by usually higher carbon, usually lower carbon, and energy management.
  • 4
    Compare scenarios: Students compare data centers powered by different energy mixes and different AI uses.
  • 5
    Mini-diagram: Students create “From AI Prompt to Carbon Impact.”
  • 6
    Exit ticket: Students explain the difference between energy use and carbon impact.

Energy source sorting

Usually higher carbon Usually lower carbon Helps manage energy
Coal, oil, natural gas Solar, wind, hydroelectricity, nuclear, geothermal Battery storage, grid storage, demand management

Student sentence stems

Energy use means __________.
Carbon impact means __________.
AI can have different carbon impacts because __________.
A responsible AI user should __________.

Simple assessment

  • Students can distinguish between energy use and carbon impact.
  • Students can explain why electricity sources matter.
  • Students can describe the chain from AI prompt to carbon impact.
📈

Lesson 2: Scale — When Small Uses Become Big Systems

Students understand that a single AI use may seem small, but repeated use by many people can create significant energy, infrastructure, and environmental demand.

Learning goal

Students understand that small AI actions can become large impacts when repeated by many people over time.

Key message

Scale matters: small digital actions can become large impacts when millions of people repeat them.

Duration

45–50 minutes.

Materials

Board or chart paper, markers, student worksheet or paper, pencils, sticky notes, optional counters, and scenario cards.

Scale formula

Small actions can become big systems.

Scale means how large something becomes when it is multiplied across people, places, and time.

One action
×
Many people
×
Many times

Lesson flow

  • 1
    Opening question: Ask whether one AI question is a big environmental problem.
  • 2
    Everyday scale examples: Compare one plastic bottle, one light left on, or one car trip with large repeated patterns.
  • 3
    AI scale simulation: Students calculate how AI questions multiply across a class, school, or city.
  • 4
    Scale and value comparison: Students evaluate school-wide AI uses by asking whether impact and value grow together.
  • 5
    Create a rule: Students write a scale-aware AI rule for the class or school.
  • 6
    Closing discussion: Students discuss why habits matter more than one isolated prompt.

AI scale simulation

Group If each asks 3 AI questions If each asks 30 AI questions
1 student 3 questions 30 questions
25 students 75 questions 750 questions
500 students 1,500 questions 15,000 questions
100,000 students 300,000 questions 3,000,000 questions

Student sentence stems

If everyone used AI this way, __________.
A scale-aware AI rule for our class is __________ because __________.
Small actions become big systems when __________.

Simple assessment

  • Students can explain what scale means.
  • Students can reason how repeated AI use grows across groups.
  • Students can distinguish between high-value and low-value uses at scale.

AI Use at Scale

Small actions become big systems. Build AI habits worth scaling.

🎯
Purpose: Why am I using it?
⚖️
Amount: Am I using just enough?
🔁
Habit: Would this be good if repeated?
👥
Scale: What if everyone did this many times?
Value: Would the benefit grow too?
🛠️
Alternative: Could a simpler tool work?
🌍
Impact: Could this reduce a larger waste?
Teacher takeaway

For Grade 6, the key ideas are energy source and scale.

Students are ready to distinguish energy use from carbon impact and to reason about scale. They should understand that AI’s environmental effect is not determined only by one prompt.

It depends on energy sources, infrastructure, task type, habits, and repeated use across many people. This prepares students for more advanced discussions about data centers, carbon intensity, renewable energy, efficiency, rebound effects, and AI as both an environmental challenge and a possible environmental tool.