The rapidly increasing use of technologies based on artificial intelligence (AI) is bringing potentially life-changing benefits to our commercial and industrial industries, as well as to people around the world. However, the promise of AI often clouds our understanding of the impact that AI-driven technologies are having on the environment.
These consequences are highlighted in a recent article posted to the website of The AI Journal. Titled “The Energy Crisis Limiting AI’s Promise: Hidden E-Waste Explosion Ahead,” the article underscores the often-overlooked aspect of AI technology, that is, its dependence on our current energy infrastructure. The article argues that the continued growth of AI will not only overwhelm our energy infrastructure capacity but will also have a disastrous impact on the increase in electronic waste (e-waste).
According to the article, the deployment and use of AI models currently consume an estimated 415 TWh annually. This is the equivalent of 1.5% of global electricity use today, a usage that is expected to at least double by the year 2030. But, beyond data centers, AI is dependent on data generated by devices and sensors leveraging the Internet of Things (IoT) networks. The number of IoT devices is expected to reach 29 billion (yes, that’s “b” as in “billion”!) by the year 2030.
Many IoT devices have a limited shelf life, contributing to the growth in global e-waste. But even more problematic is their current dependence on disposable batteries as an energy source. The article estimates that over 10 billion disposable batteries are produced annually, but that less than 5% of batteries in use are recycled.
This “perfect storm” will likely lead to an estimated 82 million tons of e-waste generated by 2030, not only further impacting the global environment but also constraining the growth of the technology infrastructure needed to support the future growth and deployment of AI technologies.
To offer a light of hope, the article recommends expanding the use of RF wireless power technologies to support increased energy efficiency in AI operations while also addressing growing sustainability challenges. The broader deployment of RF wireless power technology, the article argues, could be the solution to address these and other concerns while eliminating potential barriers to the future growth of AI.
The AI Journal article on the e-waste explosion likely to impact the broader deployment of AI is available at https://aijourn.com/the-energy-crisis-limiting-ais-promise-hidden-e-waste-explosion-ahead/.