How Are Researchers Using AI to Combat Climate Change

Climate change is one of the most pressing issues facing the world today. It’s only natural that researchers would address it with one of today’s most promising technologies. Teams across the globe have started using artificial intelligence (AI) to combat climate change.

Scientists say the world must reduce emissions by 7.6% every year until 2030, but that involves a lot of complex problems. Since AI can figure out complex issues far faster and with higher accuracy than humans, it’s the ideal tool for this effort. Here are a few ways researchers today are using it.

Understanding Climate Issues

The first step to addressing any problem is understanding it, and climate issues are complex. These changes often differ from place to place, like how the Gulf of Maine has warmed faster than 99% of the global ocean. As a result, what works in one area may not work in another.

Researchers need to understand how the climate is developing on a more granular scale, and AI can help. Machine learning models can produce accurate climate predictions and model various scenarios for a specific area. Officials can then tailor and analyze those results to find the best path forward given their unique situation.

AI is a crucial tool for making sense of climate data to drive meaningful action.

As researchers develop new theories for combatting climate change, they can run simulations in AI models first. That way, they can see how they would impact various climate issues. They can then find the best all-around solution instead of something that would fix one problem while creating another.

Optimizing Energy Consumption

AI is also helping people around the world reduce their energy-related carbon emissions. Most energy today comes from fossil fuels, and a lot of that energy also goes to waste. As a result, people produce a lot more harmful emissions than necessary, but AI can change that.

“AI is a crucial tool for making sense of climate data to drive meaningful action.” 

A few years ago, Google started using its DeepMind AI to reduce energy consumption in its data centres. The AI analyzes how various processing and cooling processes use electricity then automatically adjust them to use as little power as possible. Energy consumption dropped by as much as 30% across these data centres as a result.

This same concept could apply to entire electrical grids. AI-powered smart grids could adapt to changing demand and environmental factors to allocate power more efficiently and minimize waste. This would make the transition to clean energy smoother, reducing emissions before the world eliminates them entirely.

In Summary: AI can help accomplish the same work with less power, reducing energy-related emissions.

Reducing Transportation Emissions

While energy produces a lot of emissions, transportation is the most significant source in the U.S. Switching to electric vehicles will help eliminate these emissions, but in the meantime, AI can optimize transportation routes and infrastructure. Cities can then design greener roads and public transport systems.

Another Google project, Environmental Insights Explorer (EIE), aims to remove one gigaton of carbon emissions by 2030 by applying AI to transportation. The system uses AI to analyze local transportation issues that contribute to emissions. The AI can then make recommendations about transport options that would result in the most substantial differences.

Specific approaches may vary between locations. Some cities may benefit the most from more efficient bus routes, and others could see more improvement from building an electric train system. AI insights reveal what the best way forward is for each specific situation.

AI’s Energy Problem

Despite AI’s vast potential for fighting climate change, it introduces some climate issues of its own. The downside of using AI to reduce emissions is that this technology consumes a considerable amount of energy. As a result, researchers end up putting more carbon into the atmosphere as they try to reduce it.

Training one large deep learning model can produce more than 626,000 pounds of CO2 equivalent. That’s more than five times the emissions that a car will produce over its entire lifetime, including its manufacturing. If AI doesn’t become more eco-friendly, it may prove counterproductive in the fight against climate change.

Thankfully, this isn’t a problem without an answer. Transitioning data centres to use renewable energy and using more sustainable data management techniques and reduce AI’s emissions. Researchers can then use it effectively to address climate issues.

In Summary: Training and using AI produces hefty carbon emissions, but renewable energy could fix that.

AI Isn’t Perfect, But It’s Helping

AI may still carry some environmental concerns, but its sustainable potential is vast. If researchers can address this technology’s energy problem, it could be one of the world’s most valuable tools for saving the planet.

Climate change is a complex issue, but AI is adept at handling complex problems. While it’s not a perfect solution, AI could help pave the way for a greener future.

Also, Read Future of Robotics in Domestic Field