The aspect that makes Artificial Intelligence (AI) a dramatically powerful tool is its capacity to adapt to a wide range of uses. Once sufficient know-how is reached, AI will likely inform every level of society. A significant debate has recently surged concerning AI’s environmental impact. This technology has already been employed to address climate change, particularly in the private sector. Nevertheless, one should also consider the ecological aftereffects of implementing AI software – which might be surprisingly severe.
Examining the “pros” related to the use of AI for environmental ends, it is important to note that the technology is very efficient in carrying out analyses, making predictions, and pairing up with other devices to facilitate environmental action. Acknowledging the main practical risks of climate change and ecological degradation, the private and public sectors can join efforts and set up action plans beforehand. For instance, the Sipremo company in São Paulo, Brazil, developed an AI device capable of foreseeing when and where natural disasters will occur. If applied broadly, such a tool would help to avoid dreadful human and economic losses. Another example is provided by Eugenie.ai, a Californian company that created an emissions-tracking platform that merges satellite imagery with data from machines and processes. AI helped the company to track, trace, and reduce emissions by 20-30%. Finally, an AI-driven computer was used in companion with a drone to reforest hills in Rio de Janeiro, Brazil, as part of an initiative launched in January 2024.
However, AI has its environmental challenges. The most significant is its high electricity consumption. The amount of electricity AI systems consume is challenging to calculate, especially for specific Large Language Models (LLM) like GPT-3 created by OpenAI, which consume more than others. Furthermore, since the private sector primarily drives AI development, there is a pressing need for more transparency. AI devices also require substantial data storage, a significant source of emissions within the electronic domain.
In conclusion, using AI in the environmental field remains a trade-off. PAM and CGS enhance the international community’s expertise, ensuring that governments harmonize practices and incentivizing the private sector’s transparency.
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References
- Brown, P., “AI & Sustainability: Artificial Intelligence for Tackling Environmental Challenges”. Available at: https://www.fdmgroup.com/news-insights/ai-and-sustainability/
- Coleman, J., “AI’s Climate Impact Goes Beyond Its Emissions”. Available at: https://www.scientificamerican.com/article/ais-climate-impact-goes-beyond-its-emissions/
- Li, R., “The Environmental Impact of AI”. Available at: https://insights.grcglobalgroup.com/the-environmental-impact-of-ai/
- Masterson, V., “Nine ways AI is helping tackle climate change”. Available at: https://www.weforum.org/agenda/2024/02/ai-combat-climate-change/
- Safdie, S., “What is the Environmental Impact of AI?”. Available at: https://greenly.earth/en-us/blog/ecology-news/what-is-the-environmental-impact-of-ai