View source for Instruction:D0a94dfd-0df4-4668-b58b-3943f8c60e67

{{Instruction
|Title=The Environmental Cost of AI: What Can we do about it?
|Has Related Initiative=Initiative:2e8a4c5b-0523-49cf-bcf9-5c3e9632be5a
|Instruction 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
|Has Duration=0.5
|Important For=Citizen Scientists; Policy makers; students, researchers, and research ethics reviewers
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|Is 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.
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{{Instruction Step Trainee
|Instruction Step Title=The Environmental Footprint of AI: Understanding the Trade-offs
|Instruction Step Text=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.
|Instruction Step Interactive Content=Resource:H5P-397
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{{Instruction Step Trainee
|Instruction Step Title=Understanding the Systemic Impacts of Generative AI
|Instruction Step Text=This step explores the environmental impacts of generative AI across its lifecycle: from training, deployment, and inference to hardware and infrastructure.
|Instruction Step Interactive Content=Resource:H5P-400
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