Sources

This page lists external research, institutional reports, and scientific publications that support claims made in the poster. Each numbered item can be referenced as [1], [2], etc.

Note: This is an index, not an authority. Where possible, links go to primary sources (official reports, journals, or archives).

  1. International Energy Agency (IEA). (2024). Data Centres and Data Transmission Networks.

    https://www.iea.org/reports/data-centres-and-data-transmission-networks

  2. Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and Policy Considerations for Deep Learning. ACL.

    https://aclanthology.org/P19-1355/

  3. Masanet, E., Shehabi, A., Lei, N., Smith, S., & Koomey, J. (2020). Recalibrating global data center energy-use estimates. Science, 367(6481), 984–986.

    https://www.science.org/doi/10.1126/science.aba3758

  4. United Nations Environment Programme (UNEP). (2023). Artificial Intelligence and the Environment: Opportunities and Challenges.

    https://www.unep.org

  5. Li, P., Yang, J., Islam, M. A., & Ren, S. (2023). Making AI Less Thirsty: Uncovering and Addressing the Secret Water Footprint of AI Models.

    https://arxiv.org/abs/2304.03271

  6. Forti, V., Baldé, C. P., Kuehr, R., & Bel, G. (2020). The Global E-waste Monitor. United Nations University.

    https://ewastemonitor.info

  7. Rolnick, D., et al. (2019). Tackling Climate Change with Machine Learning. Nature Climate Change, 9, 518–524.

    https://www.nature.com/articles/s41558-019-0509-7

  8. International Energy Agency (IEA). (2023). Digitalization and Energy Efficiency.

    https://www.iea.org

  9. World Wildlife Fund (WWF). (2020). Artificial Intelligence for Conservation.

    https://www.worldwildlife.org

  10. Food and Agriculture Organization of the United Nations (FAO). (2022). Artificial Intelligence in Agriculture.

    https://www.fao.org

  11. MIT Climate Portal. (2024). AI and Climate Change.

    https://climate.mit.edu

Mapping note

The poster uses these sources as follows (examples): electricity use [1][3], training energy [2], water footprint [5], e-waste [6], climate applications [7][11], efficiency [8], conservation [9], agriculture [10].