AI Impacts Statement

Our unions’ Joint Media and Narrative Committee and Climate Justice Committee collaborated in writing this recommended statement about artificial intelligence and compiling additional resources. The statement is based on the work of the national AAUP’s Ad Hoc Committee on Artificial Intelligence and Academic Professions, including this recent report.

AI is increasingly viewed as an important tool for writing, analysis, and creative output. However, it is important to recognize that AI use has significant social and environmental impacts. Reducing use by avoiding unnecessary AI queries can minimize environmental degradation and human exploitation. Further, unlike other forms of consumption, the resource use associated with AI cannot be recycled or undone, which makes it particularly important to understand the complex footprint and potential repercussions of utilizing generative AI technology. 

Please consider the following before using AI:

  1. Generative AI depends on intense energy use, which increases greenhouse gas emissions and exacerbates climate change. The International Energy Agency estimates that by 2026, global energy use from AI, data centers, and cryptocurrency will double from 2022 use to levels “roughly equivalent to the electricity consumption of Japan” (International Energy Agency, 2024).
  2. Generative AI uses a substantial amount of water to cool hard drives to optimal temperatures for data processing. Global AI use is projected to involve the withdrawal of an alarming 4.2 to 6.6 billion cubic meters of water by 2027; for perspective, that equates to half of the annual water withdrawal of the entire United Kingdom (Li et al., 2025; Rogers, 2024; Danelski, 2023). 
  3. Generative AI requires substantial hardware resources to power AI software. Digital hardware often requires extracting rare earth minerals via exploitative mining labor practices (Fuchs, 2015).
  4. As companies seek to further commercialize their platforms, continual upgrades of AI software to power increasingly large language models also generate immense amounts of e-waste, with estimates of 2.5 million tons of e-waste per year by 2030 (Wang et al., 2024).

These are just a few examples of the complex effects of AI on human life and natural ecosystems. With these impacts in mind, we encourage you to reconsider AI use whenever possible. Beyond minimizing your use of generative AI platforms like ChatGPT, you can mitigate AI-related harm by avoiding AI search assist in web browsers such as Google since many basic searches do not require the advanced processing that powers AI. To do this, simply type “-ai” after your search query. For example: “who owns facebook -ai”

References

Danelski, D. (2023, April 28). “AI programs consume large volumes of scarce water.” University of California Riverside. https://news.ucr.edu/articles/2023/04/28/ai-programs-consume-large-volumes-scarce-water

International Energy Agency. (2024, January). “Energy 2024.” https://www.iea.org/reports/electricity-2024

Fuchs, C. (2015). “Social Media’s International Division of Digital Labour.” In Culture and Economy in the Age of Social Media (1st ed., pp. 207–245). Routledge. https://doi.org/10.4324/9781315733517-9 

Li, P., Yang, J., Islam, M.A., & Ren, S. (2025). “Making AI Less ‘Thirsty’: Uncovering and Addressing the Secret Water Footprint of AI Models.” https://arxiv.org/pdf/2304.03271#:~:text=Even%20considering%20the%20lower%20estimate,half%20of%20the%20United%20Kingdom.

Rogers, R. (2024, July 11). “AI’s energy demands are out of control. Welcome to the Internet’s hyper-consumption era.” Wired. https://www.wired.com/story/ai-energy-demands-water-impact-internet-hyper-consumption-era/

Wang, P., Zhang, L.-Y., Tzachor, A., & Chen, W.-Q. (2024). “E-waste challenges of generative artificial intelligence. Nature Computational Science, 4(11), 818–823. https://doi.org/10.1038/s43588-024-00712-6

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