Researchers warn AI boom could generate up to 5 million tons of e-waste by 2030

A new peer-reviewed study published in the journal Nature Computational Science warns that the rapid growth of generative artificial intelligence (AI) could generate up to 5 million tons of electronic waste (e-waste) annually by 2030. The international collaboration was led by Peng Wang from the Chinese Academy of Sciences and included contributions from scientists in Israel.

Researchers estimate that if immediate measures are not implemented, AI could generate between 1.2 and 5 million metric tons of e-waste by the end of this decade. This potential increase is equivalent to discarding between 2.1 and 13 billion units of the iPhone 15 Pro or more than 11,000 loaded Boeing 747 airplanes. The study emphasizes that this surge in e-waste could worsen the global toxic trash crisis, including 1.5 million tons of printed circuit boards and 0.5 million tons of hazardous batteries.

The rise in electronic waste is attributed to the rapid expansion of AI applications and data centers, which demand frequent upgrades of high-performance computing hardware. Generative AI models, such as large language models used in applications like ChatGPT, are highly resource-intensive, requiring powerful servers, processors, and storage solutions to operate effectively. This dependence on rapid improvements in hardware infrastructure and chip technology results in short life cycles for advanced processors and storage equipment, leading to a surge of discarded electronics.

Leading tech companies are spending heavily to build and upgrade data centers to power generative AI projects and to stock them with powerful computer chips. As the AI boom continues, the older chips and equipment could amount to extra electronic waste equivalent to throwing out 13 billion iPhones annually by 2030, according to a study from academics in China and Israel.

Most of the e-waste would be clustered in regions like North America, Europe, and East Asia, where most data centers are concentrated. E-waste includes discarded electronic devices such as computers, smartphones, chargers, wires, and larger server systems, defined as any product with a battery or plug. It is the planet's fastest-growing waste stream and is rapidly outstripping the capacity of recycling facilities.

The vast majority of electronic waste is not recycled, with much of it ending up in landfills or exported to lower-income countries. In these countries, people manually break apart old devices to access copper and other metals, exposing workers to harmful substances such as mercury and lead. This improper disposal leads to the release of hazardous materials, harming ecosystems and human health.

Researchers have offered solutions to reduce the electronic waste caused by AI. Implementing certain practices, including circular economy strategies, could reduce AI-related e-waste by up to 86%. By extending the lifespan of existing computer infrastructure, reusing parts, and recycling valuable materials like copper and gold, e-waste generation could be significantly reduced. The authors suggest that applying a circular economy strategy could prevent the generation of more than three million tons of waste.

Asaf Tzachor, an associate professor at Reichman University and one of the study's authors, said, "We hope this work brings attention to the often-overlooked environmental impact of AI hardware," according to The Washington Post. He added, "AI comes with tangible environmental costs beyond energy consumption and carbon emissions."

However, challenges exist in implementing these strategies. Tzachor stated, "Challenges like data security concerns and the need for high-performance hardware can make reuse and recycling more complex." Some experts, like Ana Valdivia from the University of Oxford, point out that options like reusing GPUs are not always viable. Valdivia told El Comercio Perú, "GPUs cannot be inserted into a circular economy because it is very expensive to recycle their components. 100% of a GPU ends up incinerated or in a landfill."

Geopolitical restrictions on semiconductor imports may intensify the increase in e-waste generation from AI. U.S. restrictions on the sale of advanced GPUs to countries such as China force data centers to use outdated server models, resulting in more e-waste.

The study underscores the need for responsible use of generative AI and proactive strategies for managing electronic waste to reduce the harmful effects of pollution. Peng Wang expressed deep concern regarding the competition between the expansion rate of generative AI and the adoption of the circular economy. He said, "Given the unprecedented increase in demand for this technology, to win this battle, shock measures should be implemented imminently," as reported by El Comercio Perú.

Electronic waste is already a significant and growing global problem. According to an annual United Nations report, a record 62 million tonnes of e-waste was produced in 2022. Projections from the United Nations Institute for Training and Research foresee that e-waste could soar to 82 million tons by 2030.

In light of this alarming projection, the authors of the study suggest several strategies to limit electronic waste generation. The researchers write, "Relatively simple strategies could have a major effect on e-waste generation." Dismantling, renovating, and reassembling obsolete modules, such as GPUs, for less intensive forms of computing could reduce e-waste by 42%. Extending the lifespan of these devices by just one year could prevent the generation of more than three million tons of waste.

Shaolei Ren, Associate Professor of Electrical Engineering and Computer Science at the University of California, Riverside, said, "Electronic waste is a critical issue, although often overlooked, when considering the future social impact of generative AI. This article draws attention to the problem of electronic waste generated by generative AI, and I believe it will invite a deeper debate," according to Página/12.

The study highlights that if things remain on their current trajectory, the AI industry could produce somewhere between 1.2 to 5.0 million metric tons of e-waste by the end of the decade. This increase would be as much as a thousandfold over 2023 levels, which is equivalent to "throwing away between 2.1 and 13 billion units of the iPhone 15 Pro."

As generative AI continues to expand, the environmental footprint of this technological advancement becomes a pressing concern. The study emphasizes the need for immediate measures to reduce the environmental impact of electronic waste generation, warning that without action, the consequences could be devastating.

Sources: Página/12, ABC Digital, Home, DIE WELT, El Comercio Perú, Yahoo News, Australian Broadcasting Corporation, The Washington Post

This article was written in collaboration with generative AI company Alchemiq