Shifting from Red AI To Green AI

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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.