Abstract
The 2020s may see amazing advances in AI, however, as far as the
foundation and proficient utilization of energy is concerned, we have not reached the
optimized level. As AI research advances, we should demand the best platform,
methodologies, and tools for building AI models. Organizations heavily rely on AI for
various activities today, with only 7% of businesses trying to discover the facts related
to the problem that a bigger carbon footprint is left by AI, with the training process for
several large AI models emitting as much as 626,000 pounds of carbon dioxide
equivalent to the lifetime carbon footprint of nearly 3640 iPhones. As we know,
algorithmic training is an endless process for AI-powered tools, as a result, growing
reliance on AI only speeds up the death of the immediate environment. The awareness
among the people about how AI can impact the sustainability of the environment in the
near future is not considered while developing the solution. Apart from big players in
the market, the cognizant of sustainable and responsible AI is still a big question mark.
The end user or the consumers should be aware of the services they use, whether they
are only accurate or efficient as well. The balance between both factors should be
maintained based on the context and requirement. The same is studied in the given
paper concerning the concept of Red AI and Green AI and how they should be
balanced considering the environmental sustainability factor.