The rise of AI-based technology has led several experts to ask how it can help with one of the greatest threats facing humanity, which is climate change. According to new research by a few best-known thinkers, the mission is to answer this question, giving a range of examples of how machine learning could potentially help prevent human destruction.
There are a few broad areas of deployment which includes using machine vision to monitor the environment, evaluating data analysis to find inefficiencies in emission-heavy industries, and determining AI to model complex systems, just like Earth’s own climate, so we can better prepare for major changes in the future.
There are a few fields where machine learning could be effectively deployed which are categorized by the time-frame of their potential impact. Read the list below.
How AI Can Fight Climate Change in 6 Major Ways
1. Build Efficient Electrical Systems
Electricity systems are flooded with data however nothing substantial is being done to take benefit of this information. Machine learning might help by predicting electricity generation and demand, allowing the suppliers to better integrate the major renewable resources into national grids and reduce waste. Experts at Google has demonstrated this kind of work already, using Artificial Intelligence to predict the energy output of wind farms.
2. Track Agricultural Emissions and Deforestation
The greenhouse gases are not only emitted by car or train engines and power plants but it also arises due to the destruction of trees and other plant life which has captured carbon through the process of photosynthesis over millions of years. Another reason can be deforestation and unsustainable agriculture which leads to this carbon being released back into the atmosphere. However, using images taken from the satellite and AI, we can check where this is happening and protect these natural carbon sinks.
3. Build New Low-Carbon Materials
According to a recent study, up to nine percent of all global emissions of greenhouse gases come from the production of concrete and steel. Machine learning might reduce this figure by helping to develop low-carbon alternatives to these materials. Artificial Intelligence helps scientists discover new materials by allowing them to model the properties and interactions of rare chemical compounds.
4. Forecast Extreme Weather Events
Some of the major effects of climate change in the coming decades will be driven by complex systems, such as changes in cloud cover and ice sheet dynamics. These are mindboggling problems AI is great at digging into. Modeling these major changes will help scientists predict extreme weather events, such as droughts and hurricanes, which can help governments protect against their worst effects.
5. Make Transportation Efficient
The transportation sector accounts for a one-fourth of global energy-related CO2 emissions, with 70% of this generated by road users. When it comes to electrical systems, machine learning could make this sector more efficient, lowering the number of wasted journeys, enhancing vehicle efficiency, and transforming freight to low-carbon options like rail. Artificial Intelligence could also lower car usage through the deployment of shared, autonomous vehicles, however, the authors note that this technology is still not proven.
6. Lower Wasted Energy from Buildings
Buildings are long-lasting and are rarely constructed with new technology. Adding smart sensors to calculate air temperature, water temperature, and energy use, can lower energy usage by 20% in a single building, and large-scale projects monitoring whole cities could have an even greater impact.