Implications of Artificial Intelligence-Related Data Center Electricity Use and Emissions: A Workshop
Author or publisher unknown · 2024-11-12
The National Academies hosted a two-day workshop bringing together experts from industry, utilities, and government to examine AI data centers' electricity usage, exploring its energy demands, mitigation strategies, regional siting considerations, and renewable resource availability.
Author unknown. 2024-11-12. Implications of Artificial Intelligence-Related Data Center Electricity Use and Emissions: A Workshop. https://www.nationalacademies.org/event/43750_11-2024_implications-of-artificial-intelligence-related-data-center-electricity-use-and-emissions-a-workshop (AI & Environment Resource Hub; record video-004; collection snapshot 2026-09-15).
Classification and context
Included in the original Multimedia collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
Formats and evidentiary standards vary; evaluate each original source. Source link reachable · checked 2026-09-15. Source identity and required metadata verified. The import date is not the original date added.
Ordered by the number of shared provisional topic labels. This indicates a browsing connection, not agreement between sources.
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Land use, heat, and noise; Built environment and infrastructure
In the Environmental Impacts of Data Centers 101 course, you will learn to analyze the environmental impacts of data centers using a life cycle assessment (LCA) perspective that goes beyond what you see in the news. This will include energy, water, land use, carbon emissions, global supply chains, e-waste concerns, ecological impacts, and environmental justice case studies. Whether you work in tech, sustainability, policy, or are just curious about how AI systems operate behind the scenes, this course gives you the clarity and frameworks to understand these impacts from end-to-end.
Nathaniel Burola
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
AI and ML optimize optoelectronic systems for sustainability by enhancing energy efficiency, renewable energy harvesting, environmental monitoring, and smart cities while also advancing ocean optics and photonics for marine ecosystem monitoring and climate change mitigation.
Library Progress International
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
Open access book assembling cutting-edge research exploring AI infrastructures and sustainability across media and communication, covering AI-driven media, energy consumption, climate change, and policies/ethics.
Palgrave Macmillan Cham
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
AI’s rapid growth is driving an unprecedented surge in energy and water demand, raising serious environmental justice concerns, especially in marginalized communities, while sparking debate over whether climate benefits can outweigh the harms without stronger accountability and sustainable innovation.
