Green IT : A 360-Degree Scan of Current Research , Projects and Initiatives
Figure 3-3 shows various application areas of artificial intelligence combined with relevant areas of machine learning . The individual proposals are not intended to be , and cannot be , a single solution to climate change , and will require collaboration across multiple thematic areas to implement .
Looking at the specifics of AI and how it can have an impact in the context of climate change , key areas where AI can facilitate climate action include 13 :
• Distilling raw data into actionable information : AI identifies important information among large amounts of unstructured data . E . g ., AI can analyze satellite images to identify areas of cities vulnerable to coastal inundation , or areas that are prone to forest fires .
• Improving Predictions : Based on historic data AI can make predictions on the future . E . g ., AI can make minute-level predictions on solar power generation helping to balance the electrical grid .
• Optimizing complex systems : With the help of AI methods , complex systems with many variables that can be controlled simultaneously can be optimized . E . g ., AI methods can be used to reduce the energy needed for heating or cooling a building .
• Accelerating scientific modeling and discovery : AI can accelerate the process of scientific discovery by blending known constraints with data-driven approximations . E . g ., AI can simulate portions of climate and weather models to make them more computationally tractable .
Regarding industrial settings , AI can be used to optimize the following aspects 14 :
• Supply chains : AI can help to reduce emissions in supply chains by predicting supply and demand based on past data , identifying lower-carbon products and optimizing shipping routes . Overproduction and food waste can be reduced this way .
• Improving Materials : AI can help to minimize the emissions produced by carbon-intensive materials like cement and steel by transforming industrial processes to run on low-carbon energy or even by redesigning the chemistry of structural materials .
• Production and energy : AI can help to reduce the overall electricity consumption by streamlining factories ’ HVAC systems and the development of models for industrial processes to run them on low-carbon energy instead of fossil-fueled energy .
However , despite all the possible positive effects , the damage caused by AI in the form of emissions needs to be kept in mind . Therefore , any use of AI must carefully consider the extent to which the benefits to climate change outweigh the potential harms of AI .
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