Climate change is one of the most substantial issues facing the world today. It only makes sense that people would use one of the most disruptive technologies, AI, to fight it.
Researchers, businesses and governments alike have all applied AI extensively in the fight against climate change. However, while this has shown some impressive results, its environmental downsides have also become clearer. Here’s a closer look at the benefits and disadvantages of using AI to address climate change.
Benefits of Fighting Climate Change With AI
The world has invested hundreds of millions of dollars into climate-focused AI. Despite being relatively new, these technologies have already made significant improvements, and their potential goes even further. Here are a few of the leading benefits of AI in sustainability.
1. Making Accurate Climate Predictions
Effective sustainability efforts require an understanding of the environment and how it’s changing. AI research tools can help provide that. Advanced data analytics engines can offer insight into various ecosystems and how different changes could affect them.
Researchers use AI to characterize sources of pollution, estimate exposure to contaminants, predict toxicity levels and more. This information provides a more in-depth picture of the environment and how it could change as different factors shift. Companies can use this information to make greener choices, and governments can use it to make more informed legislative decisions.
AI predictions can show how sustainability initiatives could impact the environment. Global agencies could then adjust their goals as necessary.
2. Revealing Ways to Reduce Carbon Footprints
Similarly, AI-driven insights can help people reduce their carbon footprints. Some emissions sources are obvious, but it can be difficult to grasp the full scale of a company’s output, especially when you factor in indirect sources. AI can reveal the ins and outs of these elements and suggest effective changes.
AI algorithms can analyze all of a company’s direct and indirect emissions sources and catalog them according to their size and potential for change. These businesses can then make better decisions about reducing their carbon footprints, like electrifying their fleets or using renewable energy. Some studies suggest that using AI like this can reduce emissions by 5.3 gigatons by 2030.
Smaller-scale improvements can help, too. For example, some logistics companies use AI to optimize the routes their delivery trucks take. As a result, they travel less distance, reducing transportation-related emissions.
3. Optimizing Renewable Energy
AI can also help make the most of renewable energy sources. Wind and solar produce no harmful emissions, but they don’t generate power around the clock, and energy storage is complicated. Power consumption is also rising, with the U.S. consuming 13 times more electricity in 2020 than in 1950, adding more complications. AI can help.
AI-powered smart grids can analyze real-time energy generation from renewables and demand from nearby buildings. They can then send various levels of electricity to different areas, meeting diverse power needs while minimizing energy waste. That way, renewables can deliver power more reliably.
Intelligent algorithms can also analyze various factors to find ideal locations for new solar or wind farms. These insights can help provide as much renewable energy as possible with minimal infrastructure, reducing material costs and habitat destruction.
Downsides to Using AI to Fight Climate Change
As beneficial as AI can be in fighting climate change, it carries some concerns of its own. Here are the most significant downsides of AI for the environment.
1. Energy Consumption
The biggest caveat with using AI to protect the environment is this technology’s massive energy requirements. Studies have found that training one machine-learning model can emit more than 626,000 pounds of carbon emissions, on par with the lifetime output of five cars.
Running the advanced calculations you find in AI algorithms requires extensive computing infrastructure. These computers consume a lot of energy, and most electricity today comes from fossil fuels. As a result, heavier AI use often generates more harmful emissions.
Transitioning to renewable energy would help address this issue, but that will take time. Some experts worry that rising AI use will create more demand for fossil fuels in the meantime, counteracting any positive changes it brings.
2. Reliance on Rare Earth Metals
The data centers that support AI processes also contribute to environmentally destructive mining activity. Computer hardware requires rare earth metals, and mining them takes a toll on the environment.
Every ton of rare earth mined also produces 12,000 cubic meters of waste gas, 75 cubic meters of wastewater and one ton of radioactive material. This waste, especially the radioactive residue, can seep into the surrounding ecosystem and threaten wildlife and water sources. Mining equipment also typically relies on emissions-producing diesel engines.
The world needs to address rare earth mining if AI is to be truly eco-friendly. That means either finding alternative materials or coming up with more sustainable processes.
AI Has a Complicated Relationship With the Environment
AI can be one of humankind’s best tools in the fight against climate change, but it also carries a substantial footprint of its own. Researchers and organizations need to address this complicated relationship to make the most of this technology. AI could lead the world into a more sustainable future, but only if something changes with its energy and resource needs.
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