Difference between revisions of "Instruction:D0a94dfd-0df4-4668-b58b-3943f8c60e67"
From The Embassy of Good Science
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Revision as of 14:38, 22 September 2025
ModulesThe Environmental Cost of AI: What Can we do about it?
Instructions for:TraineeTrainer
Related Initiative
Goal
By the end of this micromodule, participants will be able to:
- Identify key environmental impacts of AI technologies
- Explain how AI’s infrastructure contributes to climate and environmental pressures
- Reflect on trade-offs and future governance needs regarding AI deployment
Duration (hours)
0.5
For whom is this important?
What is this about?
Artificial Intelligence (AI) can be seen as a powerful tool to tackle sustainability challenges — but it also comes with hidden socio-environmental costs. This micromodule focuses on AI’s environmental impact. From energy-hungry data centers to e-waste and water use, this micromodule explores AI’s footprint and what people can do about it. Participants will explore both the opportunities and risks of AI in the environmental context and begin to imagine what a more sustainable AI future could look like.
1
The Environmental Footprint of AI: Understanding the Trade-offs
In this activity, you’ll explore the environmental impacts associated with AI technologies. Concerns include electricity use, water consumption, rare earth mining, and e-waste. Possible solutions and governance ideas are also explored. Interactive exercises to test your understanding are also included.
The Environmental Footprint of AI: Understanding the Trade-offs
2
Understanding the Systemic Impacts of Generative AI
This step explores the environmental impacts of generative AI across its lifecycle: from training, deployment, and inference to hardware and infrastructure.
Steps
