AI is accelerating fossil fuel extraction.
The AI supply chain is powered by extractive industries, and the mining of materials needed for computational devices. AI is also used for extractive purposes. For example, AI is being used to pinpoint the exact location for water extraction, which is further privatizing water management. In addition, a Greenpeace report exposes how the three largest cloud companies — Amazon (33% market share), Microsoft (18%), and Google (8%) — are partnering with oil companies to use artificial intelligence technologies to accelerate the unlocking of oil and gas deposits in the US and around the world at a time where we cannot afford any additional carbon in the atmosphere.
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AI models, without ecological awareness, can perpetuate and amplify environmentally damaging narratives, exacerbating ecological crises.
The integration—or lack thereof—of ecological awareness in AI systems manifests significantly in how AI influences public and private sector decisions. For instance, without ecological consideration, AI-driven recommendations in urban planning and resource management could prioritize economic gains over sustainability, leading to increased carbon footprints and depletion of natural resources. The H4rmony Project addresses this by embedding ecolinguistic principles into AI to ensure its outputs promote sustainability.
Environmental Justice Human Rights Issue 2023Companies are rushing to integrate LLMs into products even though the output of these tools cannot be fully controlled.
This can be seen in the Gemini image generation debate. "A system that you cannot debug through a logical, Socratic process is a vulnerability that exploitative tech tycoons will use to do what they always do, undermine the vulnerable."
Community Health and Collective Security Economic Justice Environmental Justice Gender Justice Racial Justice Issue 2020There is a need for a better understanding of environmental harms and AI among policymakers, experts, and the broader public.
A Mozilla workshop on "Trustworthy AI x Climate Crisis" concluded that "experts" feel unequipped to talk about this intersection. This is a new field, and there is a general sense that no one has the answer. Participants expressed a desire to define the problem and gain a clear understanding of the environmental harms of AI. They wanted to articulate the connections between AI and the climate crisis that addresses underlying power structures and might yield possible solutions. There's also a need for a clear articulation of AI harms on the environments that are most likely to be harmed. The analyses should include who and which environments are most likely to be harmed, and a clear understanding of which harms we are talking about, from AI supply chain, to carbon emissions, to how it is optimizing the global extraction economy.
Environmental Justice Issue 2019AI is intensifying energy consumption, with disproportionate impact in the Global South.
The environmental movement originally saw tech and digital transformation as a path to efficiency for a resource-depleted planet. But the dream of "the paperless office" has given way to the reality of planned obsolescence, e-waste, and the huge carbon footprints of the server farms that power cloud computing, encryption methods like Bitcoin, and AI models. Research suggests that AI is intensifying energy consumption, especially from the development of AI by major tech companies: Amazon, Microsoft, and Google. Currently, there is little to no information about how much energy Big Tech's algorithms consume, but data suggest that the biggest carbon emissions are coming from training models, and the storing of large datasets and training a single AI model can emit as much carbon as five cars in their lifetime. The ad tech industry is assumed to be the biggest pollutant in this area. Research on energy emissions/impact of AI is from the Global North, but the disproportionate impacts of energy consumption and climate change is almost always in the Global South.
Environmental Justice