Eco-friendly AI

While the benefits of AI are substantial, the environmental costs are mounting, and without proper regulatory measures, we risk repeating the ecological oversights of the Industrial Revolution on a much larger scale. The massive data centres required to train and operate AI models consume enormous amounts of electricity, leading to significant carbon emissions. These centres also require vast quantities of water for cooling purposes, straining local resources in areas already grappling with water scarcity. Furthermore, the rapid pace of AI development relies on critical minerals like cobalt and lithium, often sourced through mining in ecologically fragile regions. This extraction not only depletes non-renewable resources but also exacerbates environmental degradation.

Compounding the issue is the growing volume of e-waste generated by obsolete AI infrastructure and devices. These materials, if not recycled or managed properly, leach hazardous chemicals into the environment, causing long-term harm to ecosystems. To address these pressing concerns, it is imperative to establish a robust global regulatory framework for AI governance. Such a framework should include standardised metrics for measuring AI’s environmental footprint, mechanisms to incentivise sustainable AI development and deployment, and penalties for non-compliance with environmental standards.

Majid Burfat

Karachi