Artificial Intelligence | Sustainability @ DIA

Artificial Intelligence for Sustainability

Written by Tom Collar - Head of Primary, Dubai International Academy Emirates Hills

Tom Collar is a passionate educator, school leader, and advocate for sustainability, not just as a curriculum focus, but as a model for life. As Head of Primary at DIA Emirates Hills, Tom has helped shape a culture where environmental action is embedded at every level of the school experience, from the youngest learners planting seeds to older students leading international sustainability campaigns through the Model United Nations.

Tom believes that education is about legacy. For him, sustainability offers a blueprint not only for a greener, healthier future, but for a more ethical, inclusive, and purposeful one. He challenges students and educators alike to see themselves not as owners of knowledge, but as custodians of opportunity, asking: What footprint will we leave? What systems will we build for those who come next?

A firm believer in empowering student voice and distributed leadership, Tom works to ensure that DIA’s environmental mission is not dependent on any one initiative or individual, but endures through shared culture, community, and care.

A Curriculum Built to Adapt

Environmental action at DIA isn’t a bolt-on project or the initiative of a passionate few. It is built into our school’s infrastructure, our curriculum frameworks, and crucially, our culture.

We map every Primary Years Programme unit to a UN Sustainable Development Goal. Our Middle and Diploma Programmes interweave sustainability across sciences, economics, and literature. From farming projects run by 5 year olds to our DP students studying Environmental Systems and Societies, students don’t learn about sustainability, they live it.

Curriculum designers use AI to analyse gaps and redundancies across units and grade levels, helping educators shape a more coherent, vertically aligned sustainability journey. Natural language processing helps scan literature or student reflections for emerging themes; making implicit understandings of environmental ethics visible, trackable, and improvable.

At DIA, AI isn't just a tool to make learning more efficient. It’s a collaborator in crafting a living, responsive, and deeply personalized education. Our curriculum doesn’t just adapt, it anticipates, evolves, and empowers.

But it is in the how that AI begins to make its mark.

AI is Already Here – Quietly and Powerfully

Artificial Education is no longer futuristic. It is subtle, ambient, already reshaping how our students learn, plan, and reflect.

Take our E-Waste Campaign - initiated by a student, scaled through data and passion. With AI tools, students now design logistics routes, track volume metrics, and model environmental impact in real time. What started as a campaign is now a live system. AI didn’t spark the idea - but it helped it scale.

In our urban greenhouse, students monitor conditions and harvest data. The next step is AI-assisted sensors that alert for moisture imbalance or seasonal planting cycles. These tools won’t just guide planting - they’ll guide thinking.

Through our 17 year international legacy of DIAMUN (DIA Model United Nations) and more recently our Junior DIAMUN and Model COP28, our students already engage with climate data and policy modeling. Imagine those debates enriched by AI: tools that simulate carbon trajectories, predict regional outcomes, or suggest policy alternatives based on real-world models. That’s not fantasy. That’s the next step in our programme.

Crucially, these models provide never before seen access to a wider portion of the student body, who can all now tailor their access to complex initiatives with the support of AI.

AI Will Make Environmental Education More Relevant, More Personal, More Urgent

What AI offers is not simply efficiency. It’s context.

Imagine a student in Year 6 exploring ocean pollution. With AI, they can visualise the flow of plastic in the Indian Ocean. They can track changes over time, compare regions, and see how behaviour affects biosphere. And they can do it in a way that speaks to their own region, in their own language, at their own pace. AI personalises learning. Not in a superficial sense, but in a way that lets every learner see themselves as an environmental actor. It also allows teachers to track progress more meaningfully, spot trends in thinking, and adapt tasks based on student reflection and capability.

AI will not change what we believe. But unprecedented access to relevant and bespoke information will.

Precision Without Perspective: Risks That Could Undermine Impact and risk social divide

Of course, no tool is neutral. It can provide answers too easily. It can complete a data set, generate a report, summarise an article, all before a student has paused to think.

Environmental education could become about consumption, not curiosity. Students may skip the difficult, formative work of formulating questions, conducting fieldwork, and wrestling with ambiguity. But sustainability is not solved with answers—it’s driven by problems worth staying with. That’s why we insist on friction: slow, human processes that build critical thinking.

The Illusion of Objectivity

AI often presents information as precise and impartial. But models can reflect systemic biases, limited data sets, or oversimplified worldviews. An algorithm that recommends conservation strategies based only on Western case studies may ignore indigenous knowledge or context-specific needs.

In environmental education, this matters. The world does not need one-size-fits-all answers. It needs solutions that are locally rooted and globally aware. At DIA, we teach students to interrogate the source, not just accept the solution.

Creativity at Risk

AI is trained to optimise. But environmental leadership is about vision, empathy, and the messy, beautiful unpredictability of human ideas.

If AI is used too heavily in student projects, there's a risk that outputs become too uniform. They will become smooth, polished, but lifeless and as humans we will become overly reliant on these models. We must avoid sustainability campaigns that “look right” but say nothing personal. A coral reef conservation pitch that ticks every box but lacks soul.

At DIA, we counter this by championing student voice over algorithmic noise. We use AI to support expression, not substitute it. We don’t just teach how to use AI - we teach how to question it.

We ask:

What data is this model based on?
Who benefits from its conclusions?
Is speed worth more than sense?

These are the critical lenses our students must hold onto as AI becomes more integrated into learning.

In Closing

So, do I believe Artificial Education will fundamentally transform opportunities for students in environmental education?

Yes. And I believe it has already started.

But at DIA, we have built something even more powerful than an AI toolset. We’ve built a culture that is ready to use those tools with care, courage, and creativity.

We don’t fear the future of sustainability education.
We’re programming it.
We’re planting it.
We’re preparing students to lead it - with insight, integrity, and action.