Artificial intelligence (AI) has entered K–12 education remarkably quickly. In a 2026 Gallup survey, 74% of Gen Z K–12 students surveyed reported that their schools had rules governing AI use.
Among students attending schools with AI policies, 65% said they were permitted to use AI for schoolwork. The Association for Education Finance and Policy (AEFP) has similarly noted in its Live Handbook of Education Policy Research that schools are adopting AI tools more quickly than researchers can evaluate their effects (Barnard et al., 2026).
Meanwhile, a 2025 RAND study found that 54% of surveyed middle and high school students reported using generative AI for schoolwork (Doss et al., 2025).
AI is now being explored across the educational landscape, from district leaders and school administrators to teachers, families, and students themselves. Yet important questions remain about how, when, and to what extent AI can benefit K–12 learners.
The National Education Association (NEA) has reported that educators see opportunities for AI to address some learning gaps, personalize learning, support translation, and increase accessibility for multilingual learners and students with disabilities. Educators have also identified opportunities for AI to streamline tasks and reduce workloads, potentially helping to combat educator burnout.
Alongside these potential benefits, educators have raised concerns about privacy, AI hallucinations, and the loss of human personalization in areas such as Individualized Education Program (IEP) development (Schalop, 2026).
Beyond how educators may use AI to support teaching and learning, questions also remain about the effects of students’ own AI use. As AI becomes more integrated into learning, educators must continue examining how its use might influence critical thinking, creativity, innovation, academic integrity, and students’ ability to distinguish reliable information from AI-generated inaccuracies.
Students must also learn when AI can support learning and when relying upon it may interfere with the development of knowledge and skills they need to acquire themselves. These are all important dimensions of AI literacy, and they merit continued discussion and research.
Another dimension of AI literacy is also gaining attention: AI’s impact on the environment.
Although interacting with an AI tool can feel almost instantaneous, the technology depends upon physical infrastructure and resources. According to MIT News, generative AI carries environmental consequences that include increased electricity demand, associated carbon emissions, and increased water consumption to cool computing hardware (Zewe, 2025).
As published in the MIT Technology Review, U.S. data centers consumed roughly 200 terawatt-hours of electricity in 2024, approximately as much electricity as Thailand uses in a year. AI-specific servers within those data centers were estimated to account for 53 to 76 terawatt-hours, enough at the high end to power more than 7.2 million U.S. homes for a year (O’Donnell & Crownhart, 2025).
The relationship between AI and energy, however, is complex. The MIT Energy Initiative has also identified ways AI could support the transition to cleaner energy, including helping to manage power-grid operations and supporting infrastructure development (Stauffer, 2025).
Even with this potential, the resource demands associated with using AI remain important to consider. UN News has highlighted research indicating that day-to-day AI use accounts for an estimated 80% to 90% of AI’s total energy demand (2026). Understanding both the potential benefits and environmental costs of AI is therefore becoming an important component of AI literacy.
This conversation also connects to lessons educators have long taught about the responsible use of shared resources. Globally, disparities in access to reliable electricity and clean water persist.
Where these resources are readily available, children are often taught from an early age to use them responsibly. We teach students to turn off lights when they leave a room, avoid running water unnecessarily while brushing their teeth or washing dishes, and make thoughtful choices about heating and cooling.
The message is not that electricity and water should not be used, but that valuable resources should be used with awareness and care.
AI use can become part of that same conversation. Teaching students about the energy and resources required to power AI does not mean discouraging them from using the technology.
Instead, it means helping them consider whether their use is purposeful, whether another tool might sometimes accomplish the same goal, and whether the value of an AI interaction justifies the resources required to support it.
Responsible AI literacy, then, should include not only teaching students how to use AI, but also helping them think critically about when and why they use it.
Responsible AI literacy, then, should include not only teaching students how to use AI, but also helping them think critically about when and why they use it.
How can educators begin bringing this dimension of AI literacy into the classroom? The following 10 approaches move students from making connections and investigating AI’s resource demands to making intentional choices and engaging others in conversations about responsible AI use.
1. Make Observations and Connections
Begin with something students already understand: energy is part of their everyday lives. Ask students to identify where they encounter energy consumption throughout a typical day.
They might consider lighting, heating and cooling, transportation, appliances, phones, computers, gaming systems, streaming services, and other technologies.
From there, extend the conversation to AI. Students may interact with an AI chatbot by typing a few words and receiving an answer almost immediately, but that simple interaction depends upon physical infrastructure and resources that may be largely invisible to them.
Teachers can use this as an opportunity to help students connect digital activity with the physical systems that make it possible. Rather than presenting technology as simply positive or negative, encourage students to identify both the benefits these systems provide and the resources and tradeoffs involved in operating them.
Questions might include:
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What resources are required to support the technologies you use every day?
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Which of those resources are visible to you, and which are largely invisible?
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What benefits do these technologies provide?
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What environmental costs might accompany those benefits?
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How might those costs influence the choices we make?
As research surrounding AI’s environmental impact continues to develop, teachers can introduce age-appropriate data and encourage students to examine new evidence, ask questions, and remain open to multiple perspectives.
2. Investigate AI and Energy
Once students understand that AI relies upon physical resources, invite them to investigate one part of the issue more deeply.
Students might research the hardware used to develop and operate AI systems, the electricity required by data centers, the role of water in cooling computing equipment, or innovations aimed at developing more energy-efficient hardware. Others might investigate the electrical grid, renewable energy, data-center locations, or how increasing electricity demand could influence future infrastructure.
The topic can also be approached historically. Students might investigate earlier technologies that transformed how people lived and worked, examining both the benefits they created and the new resource demands, infrastructure, or environmental concerns that followed.
Research questions can be adjusted according to grade level and subject area. The important goal is to move students beyond broad claims such as “AI is bad for the environment” or “technology makes life better” and toward evidence-based understanding of a complicated and evolving issue.
3. Debate the Tradeoffs
AI and energy provide a strong opportunity for students to practice evidence-based discussion and debate.
Rather than asking students simply whether AI is “good” or “bad,” give them questions that require them to weigh competing considerations. Should schools encourage AI use if it provides meaningful accessibility benefits?
Are some AI applications worth greater resource use than others? Should technology companies be expected to disclose more information about the energy and water required by their systems?
What responsibility, if any, should users have for considering resource consumption when deciding whether to use AI?
Students can research positions, evaluate sources, verify claims, and support their arguments with evidence. They can also practice listening to opposing viewpoints, responding to ideas rather than individuals, taking turns, and changing their positions when presented with stronger evidence.
The objective does not have to be reaching a single correct answer. Instead, students can learn that responsible technology decisions often require balancing benefits, costs, priorities, and competing needs.
4. Decide When AI Is Worth Using
One of the most practical ways students can apply this knowledge is by considering whether AI is actually necessary for a particular task.
Provide students with real-world scenarios and ask them to determine which tool they would choose. Could they complete the task themselves?
Would a calculator, textbook, search engine, conversation with another person, or another resource accomplish the goal? Does AI provide enough additional value to make it the better choice?
A student who needs to calculate a simple percentage, for example, may decide that a calculator is sufficient. A student who wants feedback on several possible approaches to a complex project might determine that an AI tool provides additional value.
The goal is not to teach students that using AI is wrong when another option exists. Instead, students should learn to consider purpose before automatically reaching for AI.
Ask them to explain their decisions:
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What are you trying to accomplish?
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Why would AI be useful for this task?
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Could another tool accomplish the same goal?
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What additional value would AI provide?
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Is that additional value worth the resources required?
These questions help shift AI use from an automatic behavior to an intentional decision.
5. Work Within an AI Energy Budget
Resource constraints can make an abstract concept much more tangible.
Give students a hypothetical AI energy budget along with a series of tasks that carry different energy “costs.” Students cannot use AI for every task without exceeding their budget, so they must decide which applications provide the greatest value.
For example, students might have to choose among using AI to brainstorm ideas for a research project, generate a novelty image, receive individualized feedback on writing, summarize material they could easily read themselves, or support translation for someone communicating in another language.
There does not need to be one correct answer. The value of the activity comes from requiring students to establish priorities and justify them.
Teachers can ask:
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Which uses provide the greatest benefit?
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Which could easily be accomplished another way?
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Are some uses worth a higher energy cost?
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Who benefits from each use?
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Would accessibility, safety, education, or another important need change your decision?
An energy budget helps students see that responsible use is not necessarily about using AI as little as possible. It is about considering whether the value created by an interaction justifies its costs.
An energy budget helps students see that responsible use is not necessarily about using AI as little as possible. It is about considering whether the value created by an interaction justifies its costs.
6. Identify AI Energy Leaks
Once students have determined that AI is an appropriate tool for a task, they can examine how unnecessary actions within an AI interaction may consume additional resources. Provide students with examples of AI-use behaviors such as repeatedly regenerating an output without reviewing it first, requesting multiple versions that are never used, generating more content than the task requires, or continuing an interaction after the original goal has already been accomplished.
Ask students to identify the “energy leak” in each scenario and suggest a more intentional approach. They might also distinguish between productive iteration, in which additional interactions serve a meaningful purpose, and unnecessary repetition, in which additional AI use adds little or no value.
Through this activity, students can begin to recognize that the number of AI interactions alone does not determine whether use is wasteful. What matters is whether each interaction contributes something meaningful to the task.
7. Make Prompts More Purposeful
Prompt-writing provides another opportunity to connect effective AI use with intentional resource use.
Give students several prompts designed to accomplish the same task and ask them to determine which is most likely to generate a useful output. Students can identify what makes one prompt clearer or more purposeful than another and then practice revising vague prompts themselves.
For example, a student might begin with:
“Help me with my essay.”
They could then revise the request to include the actual purpose, relevant context, and type of assistance needed:
“I am writing a seventh-grade persuasive essay about extending school lunch periods. Ask me three questions that will help me identify stronger evidence for my argument. Do not write the essay for me.”
The second prompt provides clearer direction about the task, the student’s needs, and the appropriate role for AI.
Purposeful prompting requires students to think before they type. By identifying their goal, providing relevant context, and communicating what they need clearly, students can strengthen both their prompting skills and their ability to approach AI interactions with greater intention.
A purposeful prompt may also reduce unnecessary retries, although prompt quality alone does not determine how much energy an AI interaction requires.
8. Bring Experts Into the Classroom
Students should also have opportunities to learn directly from people working in fields connected to the issues they are studying.
Teachers might invite university researchers, technology professionals, energy experts, environmental scientists, nonprofit leaders, policymakers, or others whose work intersects with AI, infrastructure, sustainability, or education.
Rather than having guest speakers simply give presentations, students can prepare questions in advance based on their previous research and discussions. Speakers may offer very different interpretations of the same issue, giving students an opportunity to compare claims, identify areas of agreement and disagreement, and consider how professional backgrounds influence perspectives.
Students might ask:
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How is your field responding to increased AI use?
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What concerns you most about AI’s resource demands?
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What developments make you optimistic?
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What information do you think the public often misunderstands?
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What responsibilities belong to technology companies, governments, schools, and individual users?
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What changes do you expect to see in the next five or ten years?
Hearing from multiple experts reinforces an important lesson: emerging technologies rarely present simple questions with simple answers.
In that sense, responsible AI literacy is not only about teaching students how to use AI. It is also about teaching them to think carefully about when, why, and how much they use it.
9. Write to Decision-Makers
Once students have researched and discussed the issue, give them an opportunity to communicate what they have learned.
Students might write letters or emails to technology companies, policymakers, school leaders, researchers, or other decision-makers. Their messages could explain what they learned about AI and energy, identify areas that excite or concern them, ask questions, or propose actions they believe organizations should consider.
This creates an authentic opportunity to practice persuasive and informational writing. Students must consider their audience, organize evidence, distinguish fact from opinion, and determine what they are asking the recipient to consider or do.
Teachers can also encourage students to represent complexity rather than simply advocating for or against AI. A strong letter might acknowledge the benefits of AI while asking a technology company for greater transparency about energy use, or recognize the value of AI in education while proposing ways schools could encourage more intentional use.
Students can expand the conversation beyond their classroom by organizing a school or community forum on AI, energy, and responsible technology use.
Depending on students’ ages, they might help identify topics, develop questions, invite participants, advertise the event, moderate discussions, or summarize what they learned afterward.
Panels can include stakeholders representing different perspectives, including educators, students, families, researchers, technology professionals, environmental advocates, energy experts, and community leaders.
Preparing for a forum requires students to move beyond their own positions. They must consider what different stakeholders value, where disagreements exist, what evidence supports various claims, and which questions remain unanswered.
The result is not simply an event about AI. It is an opportunity for students to practice communication, collaboration, leadership, civic engagement, and responsible participation in a complex public conversation.
Final Thoughts
AI’s environmental impact is a complex and rapidly developing issue. Students do not need to become experts in data centers, electrical grids, or computing hardware before they can begin thinking responsibly about the resources behind the technologies they use.
We already teach children that access to a useful resource does not mean it should be used without consideration. Turning off a light when leaving a room does not mean electricity is bad.
Turning off the tap while brushing our teeth does not mean we should avoid using water. These habits teach awareness, responsibility, and respect for resources.
AI literacy can incorporate the same principle.
Teaching students about AI’s energy demands should not be about making them feel guilty for using AI or discouraging them from exploring a technology that may offer meaningful educational and societal benefits. It should be about giving them another piece of information they can use when making decisions.
As AI becomes increasingly embedded in education and everyday life, responsible use will require more than knowing how to write a prompt or evaluate an output. Students should also learn to ask whether AI is the right tool for the task, whether their use is purposeful, what resources make that interaction possible, and whether the benefits justify the costs.
In that sense, responsible AI literacy is not only about teaching students how to use AI. It is also about teaching them to think carefully about when, why, and how much they use it.
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