AI, Data Centers, and Energy – Data Set

Summary

Data Center Electricity Use Data Set

This student data set asks learners to analyze how global and U.S. data center electricity use is changing over time and why AI is accelerating that growth. Students interpret graphs showing global data center electricity consumption, server stock, server capacity, and projected increases through 2030, then connect those trends to the rise of accelerated servers used for AI workloads.

The activity helps students distinguish between measured data and projections, identify changes in growth rate, and explain how server capacity is increasing faster than server count. Students also examine how U.S. data centers are becoming a larger share of national electricity use and consider how clustered facilities may affect local power systems and communities.

This resource is especially useful for teachers searching for environmental science activities for high school, data analysis worksheets for high school, AI electricity use activity, or energy demand graph analysis. It supports NGSS-aligned science practices including interpreting data, making evidence-based claims, and evaluating system-wide impacts of infrastructure growth.

Because the questions move from straightforward interpretation into causal reasoning and systems thinking, the activity works well as a class discussion tool, independent practice, or assessment.

Extend the Lesson:
Use this Data Set after the Reading Activity to give students the background they need for graph analysis. For a broader systems connection, pair it with lessons on the Electric Grid or Energy Choices.