AI has made a big impact in our world, from solving scientific concepts to creating real-life applications. ChatGPT was just the beginning. Now AI is an essential part of our lives, can it solve the most urgent challenge: climate change?
How can AI fight climate change?
AI is advancing at a rapid pace. In just one year, it has evolved from a smart assistant that can help you answer a trivia question to a creative genius that can generate a South Park episode on its own. But the real question is “What can AI do for us in the struggle against climate change?”
To be frank, no one knows what can it do in this matter. Because we do not know how fast AI will develop in the future, or what kind of intelligence it will have. Will it be a dangerous Skynet or just a friendly and helpful ChatGPT-5?
At this time, all we can do is explore some of the potential applications of AI in its current form. Spoiler alert: Most of them are linked to AI’s ability to process huge amounts of data at high speed.
Maximizing energy usage
Air pollution is our main problem when it comes to environmental degradation. Since the Industrial Revolution, we have been emitting greenhouse gases into the atmosphere. The energy sector is the main source, accounting for about 73% of global emissions.
To reduce our carbon footprint, we have been trying to switch to low-carbon energy sources, such as solar, wind, and hydropower. But we still have a long way to go before we can replace fossil fuels completely. So our best bet is to optimize how we use our energy sources. And that’s where AI can help us.
By using AI to digest and analyze large amounts of data about our energy consumption, we can predict the demand and supply of electricity and balance the grid accordingly. AI can also help us calculate the exact usage of energy in every stage and reduce energy loss and waste in transmission and distribution networks.
Capturing and Removing Carbon
Another way to combat climate change is to capture and remove carbon dioxide from the atmosphere or from emission sources, and store it safely underground or use it for other purposes. This is known as carbon capture and storage (CCS) or carbon capture and utilization (CCU).
And AI can help to reduce the burden on power consumption when optimizing carbon capture levels. How? By using satellite data to monitor and track emissions, predict suitable molecules and materials to separate carbon, forecast future emissions, and come up with plans to reduce future output.
Managing Disaster
One of the most horrific impacts of climate change is the increase in the frequency and intensity of natural disasters, such as floods, droughts, wildfires, hurricanes, and heat waves. These disasters pose serious threats to human lives, livelihoods, infrastructure, and ecosystems.
AI can be deployed to improve the accuracy and timeliness of weather forecasting and early warning systems like the use of machine learning in predicting forest fires. It can also analyze satellite imagery and remote sensing data to assess the damage and risk of disasters. In the event of a disaster, AI can help coordinate relief efforts allocate resources efficiently, and enhance communication and information dissemination among all parties.
Researching
One of the challenges of addressing climate change is the complexity and uncertainty of the problem, which requires interdisciplinary and collaborative research and innovation. AI can help us advance our scientific understanding and technological solutions by:
- Accelerating the discovery and development of new materials, processes, and products
- Enhancing the modeling and simulation of complex systems and scenarios
- Facilitating the sharing and integration of data and knowledge across domains
- Fostering creativity and innovation through generative design and synthesis
Real Applications Of AI to Combat Climate Change
AI is not just a theory. It is already being used in real applications to combat climate change. For example:
- Google has used AI to reduce the energy consumption of its data centers by 40%, saving hundreds of millions of dollars.
- DeepMind, a subsidiary of Google, has developed an AI system that can predict the power output of wind farms 36 hours ahead of time, increasing their value by 20%.
- XYONIX is a company that uses AI to operate its direct air capture plants, which extract carbon dioxide from ambient air using fans and filters. The captured carbon dioxide can then be stored underground or used for applications such as green fuels, fertilizers, or beverages.
- IBM’s Watson AI has been used to create a system called PAIRS Geoscope, which can process terabytes of geospatial data from various sources, such as satellites, drones, sensors, and social media, and provide insights for disaster management.
- Facebook’s Disaster Maps uses AI to aggregate and anonymize location data from users and provide information on population density, movement, and network connectivity to aid humanitarian organizations.
Using AI for Environmental Purpose Is Not Easy
Deploying AI may seem like a no-brainer for solving climate change, but it is not that simple. AI has its own costs and risks that we have to consider.
One of the costs is the energy consumption of AI. AI runs on computers and computers need electricity to run. And a lot of electricity. According to a study by the University of Massachusetts, training a large AI model can emit as much carbon as five cars in their lifetimes. That’s a lot of carbon for a lot of computation.
So using AI is not always green. It can actually add to the problem of climate change if we don’t use it wisely. We have to take into account the power consumption when using AI and try to use renewable energy sources or optimize the efficiency of our algorithms.
Another risk is the accuracy of AI. AI is not perfect. It can make mistakes or give wrong predictions. These mistakes can have serious consequences for the environment and human lives. For example, if an AI system fails to detect a wildfire or a flood, it can cause more damage and casualties.
So using AI is not always reliable. It can actually harm us if we don’t use it carefully. We have to check the accuracy of AI and try to improve the quality of our data or validate the results of our models.
Conclusion
AI has shown great potential to help us solve climate change – one of the biggest challenges of our time. It can help us improve energy efficiency, carbon capture and removal, disaster management, and research and innovation. It can also provide us with real applications that are already making a difference.
But AI is not a silver bullet. It has its own limitations and challenges, such as power consumption and accuracy. We have to be careful and responsible when using AI, and not rely on it blindly. We also have to work together with other disciplines and stakeholders to find the best solutions for our planet.
AI is a powerful ally, but it is not a savior. We are the ones who have to take action and make changes. AI can only help us if we help ourselves.
[Images: Unsplash/Karsten Wurth, Jason Blackeye, Ian-Battaglia, and Egor Vikhrev]
