The Environmental Cost of AI: What Can we do about it?
ModulesThe Environmental Cost of AI: What Can we do about it?
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. 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
What is this about?
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
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.
Making AI More Sustainable: What Are the Options?
In this step you’ll learn about the energy and resource demands of generative AI, as well as realistic strategies that reduce environmental impacts while maintaining performance.
