AI Machine Learning Has A Carbon Footprint And Thus So Do Self-Driving Cars

Dr. Lance Eliot, AI Insider

[Ed. Note: For reader’s interested in Dr. Eliot’s ongoing business analyses about the advent of self-driving cars, see his online Forbes column: https://forbes.com/sites/lanceeliot/]

The benefits of AI Machine Learning (ML) and Deep Learning (DL) has taken a slightly downbeat turn toward pointing out that there is a potential ecological cost associated with these systems. In particular, AI developers and AI researchers need to be mindful of the adverse and damaging carbon footprint that they are generating while crafting ML/DL capabilities.

It is a so-called “green” or environmental wake-up call for AI that is worth hearing, some refer to this as Green AI.

Let’s first review the nature of carbon footprints (CFPs) that are already quite familiar to all of us, such as the carbon belching transportation industry. A carbon footprint is usually expressed as the amount of carbon dioxide emissions spewed forth, including for example when you fly in a commercial plane from Los Angeles to New York, or when you drive your gasoline-powered car from Silicon Valley to Silicon Beach.

Carbon accounting is used to figure out how much a machine or system produces in terms of its carbon footprint when…