E-waste is the term to explain things like air conditioners, televisions, and private electronic devices corresponding to cell phones and laptops after they are thrown away. These devices often contain hazardous or toxic materials that may harm human health or the environment in the event that they’re not disposed of properly. Besides those potential harms, when appliances like washing machines and high-performance computers wind up within the trash, the beneficial metals contained in the devices are also wasted—taken out of the availability chain as an alternative of being recycled.
Depending on the adoption rate of generative AI, the technology could add 1.2 million to five million metric tons of e-waste in total by 2030, in accordance with the study, published today in Nature Computational Science.
“This increase would exacerbate the present e-waste problem,” says Asaf Tzachor, a researcher at Reichman University in Israel and a co-author of the study, via email.
The study is novel in its attempts to quantify the results of AI on e-waste, says Kees Baldé, a senior scientific specialist on the United Nations Institute for Training and Research and an writer of the most recent Global E-Waste Monitor, an annual report.
The first contributor to e-waste from generative AI is high-performance computing hardware that’s utilized in data centers and server farms, including servers, GPUs, CPUs, memory modules, and storage devices. That equipment, like other e-waste, comprises beneficial metals like copper, gold, silver, aluminum, and rare earth elements, in addition to hazardous materials corresponding to lead, mercury, and chromium, Tzachor says.
One reason that AI corporations generate a lot waste is how quickly hardware technology is advancing. Computing devices typically have lifespans of two to 5 years, they usually’re replaced steadily with the latest versions.
While the e-waste problem goes far beyond AI, the rapidly growing technology represents a possibility to take stock of how we take care of e-waste and lay the groundwork to handle it. The excellent news is that there are strategies that may help reduce expected waste.
Expanding the lifespan of technologies by utilizing equipment for longer is one of the vital significant ways to chop down on e-waste, Tzachor says. Refurbishing and reusing components also can play a big role, as can designing hardware in ways in which makes it easier to recycle and upgrade. Implementing these strategies could reduce e-waste generation by as much as 86% in a best-case scenario, the study projected.
