The Workshop
The AI Quiz is an interactive educational session exploring artificial intelligence's hidden environmental costs. Through engaging quiz questions, participants discover how training and operating AI systems consume significant computational energy and water, and explore approaches to building more sustainable AI. The session moves beyond common misconceptions about AI as immaterial to reveal the very material environmental impacts of computation, helping participants make informed choices about AI use and advocate for sustainable AI development practices.
Why It Matters
This workshop matters because AI is increasingly embedded in decisions affecting resource allocation, environmental management, and social systems - yet most people are unaware of AI's environmental footprint. Understanding these impacts is essential for making informed choices about AI adoption, evaluating corporate sustainability claims, and advocating for tech companies to commit to renewable energy and water efficiency. As AI becomes more powerful and widespread, its environmental costs become more critical to manage and monitor.
Good to Know
Training large language models can consume significant electrical energy and require substantial freshwater cooling for data centers. A single long session with a language model can indirectly consume half a liter of fresh water. Generating large amounts of text uses power equivalent to running an LED bulb for hours, while generating short videos consumes electricity comparable to charging a laptop multiple times. As of 2025, median AI prompts in cloud environments have smaller footprints than common digital habits like streaming, though energy efficiency varies significantly by provider and infrastructure.
What to Expect
Facilitators introduce the computational infrastructure behind AI systems; participants answer quiz questions about AI's energy consumption, water use, and environmental footprint; facilitators reveal data on computing infrastructure impacts and how these vary by energy source; discussion explores trade-offs between AI capabilities and environmental costs; participants learn about corporate commitments to renewable energy and efficiency improvements in AI systems; the session concludes with participants identifying ways to advocate for sustainable AI in their organizations and hold tech companies accountable for environmental impacts.
