The rapidly advancing artificial intelligence (AI) technology is quickly gaining abilities such as engaging in human-like conversations, creating art, and even making films. However, researchers from the Chinese Academy of Sciences warn that this progress may have a negative impact on the environment.
According to studies, the rise of generative AI applications such as chatbots and content creation systems could result in the production of an additional 1.2 to 5 million tons of electronic waste (e-waste) by the end of this decade.
The research, particularly focusing on large language models (LLMs), highlights how these AI systems, capable of interpreting and generating human language, can perform a variety of tasks, including answering questions, writing text, and generating visuals.
In addition to these capabilities, the rapid development of generative AI requires more hardware infrastructure and chip updates. Researchers warn that upgrades needed to keep up with this technology's growth could exacerbate existing e-waste problems.
E-waste could reach 2.5 million tons annually The study notes that the high energy consumption and carbon footprint of the substantial computational resources needed to train and operate LLMs lead to sustainability issues.
The research team calculated AI's potential to generate e-waste between 2020-2030 under four different scenarios. In the highest usage scenario, it is projected that AI-related e-waste could reach 2.5 million tons annually by 2030.
In this intense usage scenario, it is anticipated that e-waste from AI will include 1.5 million tons of printed circuit boards and 500,000 tons of batteries, which could contain harmful substances like lead, mercury, and chromium.
The study also notes that only 2.6 thousand tons of electronic waste last year was attributed to AI technologies, but this amount is expected to rise significantly along with the general increase in e-waste.
By 2030, the total amount of e-waste is expected to increase by 30%, reaching a massive 82 million tons.
Researchers emphasize the importance of circular economy strategies to reduce e-waste generation.
These strategies include extending the lifespan of existing infrastructure and reusing essential materials.
The study highlights that if these methods are applied, AI-related e-waste could be reduced by up to 86%.
