Study reveals hidden environmental and resource costs associated with training and deploying helpful AI systems

AI systems designed to be helpful require significant computational resources, leading to substantial energy consumption and carbon emissions

The infrastructure needed to support helpful AI models involves mining rare materials and creating large data centers with major environmental impacts

Training and running helpful AI systems generates ongoing costs in terms of water usage, e-waste, and resource depletion that are often overlooked