“THE REASON I TALK ABOUT REGENERATION AS OPPOSED TO SUSTAIN- ABILITY IS THAT OUR WHOLE APPROACH IS UNSUSTAINABLE. THIS IS WHY WE’RE IN ECOLOGI- CAL CRISIS. SO, WE DON’T WANT TO BE SUSTAINING THE CURRENT SYSTEMS. WE NEED TO REGENERATE ECOSYSTEMS USING A LENS OF HEALING, REPAIR, AND RESTORING RELATION- SHIPS. SUSTAINABILITY DOESN’T CAPTURE THAT.”
One of the things we want to be doing
right now is slowing down and thinking about how to navigate this moment with discernment. For instance, what kind of criteria should guide us in making sure that quality thinking stays at the centre of educa- tion? We need to consider how we will align the use of technologies with core values and connect the digital with ecological and rela- tional literacies. I want us to think about regeneration not
sustainability, along with truth and recon- ciliation, decolonization, and pedagogies of inclusion that support well-being. All these things should be considered together in thoughtful ways.
MP: Can you talk a bit about what you mean by the term regenerative?
MV: Te reason I talk about regeneration as opposed to sustainability is that our whole approach is unsustainable. Tis is why we’re in ecological crisis. So, we don’t want to be sustaining the current systems. We need to regenerate ecosystems using a lens of heal- ing, repair, and restoring relationships. Sus- tainability doesn’t capture that. Many distinct
Indigenous knowledge
systems advocate coming back to princi- ples of reciprocity that really bring about regeneration, as opposed to what we are doing right now by extracting as much as possible from the Earth as quickly as we can in order to make profit and sustain our current way of life.
MP: Could you talk a bit about the envi- ronmental impacts of AI?
MV: Every time you put a prompt into ChatGPT that is the equivalent of using about a bottle of water, and that number goes up substantially when you’re engaged in image generation. Tere was a study released November 10 in Nature and Sus- tainability reporting that by 2030, the cur- rent rate of AI growth would annually put about 24 to 44 million metric tons of car- bon dioxide into the atmosphere. Tat’s the equivalent of adding about five to 10 million cars to the roadway. Tinking about that in the context of the climate crisis, the way AI systems are currently being developed is in- creasing those emissions. For water, by 2030 we’re on track to use as much water for AI as the entire country of Denmark uses, and that will only continue to increase. Looking at it from the lens of environ-
mental justice, people are building AI data centres in poor and marginalized communi-
28 ETFO VOICE | WINTER 2025
ties, which are already facing water shortages. Tere are ways that AI can be configured
that would be more ecologically sustainable. We could decarbonize and use more sustain- able regenerative energy for AI operational efficiencies that would absolutely reduce emissions and water use. But that’s not the mindset of corporations. It’s important to build collective movements and that educa- tion advocate for discernment about how we’re using these tools, how we’re talking about them, how we’re supporting learners to map and understand the systemic realities of AI. Tese issues are interconnected. AI runs on data. All the knowledge we’ve
produced fuels AI. But to feed that data into AI, it needs to be what’s called “cleaned.” Re- moving violent and pornographic images is work that needs to be done, and is oſten done in Global South nations by exploited workers making unfair wages and exposing them to trauma. Tat’s another shadow aspect of AI that people are not aware of. Tese are critical justice issues, intersect-
ing with environmental issues, that absolutely must be driving decision-making in society.
MP: Tere are lots of resources about how to use AI, but there are not a lot of conversations happening about whether to use it. How do you think educators can teach students to think critically about the use of AI and to consider its environ- mental impacts?
MV: Tere are mixed studies about whether AI is good or bad for critical thinking, but what it is telling us very clearly is that AI magnifies learning design. Some studies show that if AI is well scaffolded with critical inquiry, it can actually support the develop- ment of quality thinking, but in unstructured use, when students are outsourcing the hard parts of thinking, we actually see measurable drops in critical engagement and in students’ critical thinking abilities. Te cognitive offloading piece is very important. Within education, we should be very
concerned about this and carefully design- ing learning to prevent the decline in criti- cal thinking. One of the big concerns around whether to use AI is whether AI is training us to accept unexamined answers, especially in the current context of rising authoritari- anism. Examining evidence, having delibera- tive discussions with each other, engaging in the thoughtful examination of issues in our communities is essential for democracy. If we’re offloading critical thinking to AI and accepting its answers uncritically, there are
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