Quantifying the Environmental Impact of AI Lifecycle Management
Keywords:
Green AI, AI lifecycle management, Sustainable AI, Policy frameworks, AI environmental impactAbstract
This is an era of AI. Nowadays AI has become an integral part of our lives. AI is not only useful for businesses but also it is useful for individual’s life too. Questions arise about whether the massive use of AI will help businesses motto to keep the environment clear or not. Day by day AI systems are growing and their environmental impact particularly in terms of energy consumption and carbon emission becomes a big question. Current research on Green AI focuses predominantly on the training phase, leaving other lifecycle stages underexplored. This study aims to quantify the environmental benefits of adopting a comprehensive Green AI approach, covering the full lifecycle of AI models. With the help of correlation and regression analysis, this research paper evaluates the relationship between various AI lifecycle management strategies (data-centric approaches, real-time emissions monitoring, and model optimization) and reductions in energy consumption and carbon emissions. The findings support the development of policy frameworks that incentivize sustainable AI practices across industries.
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