AI & Climate Change

Artificial Intelligence is transforming the way we live, work, and interact with the world. From digital assistants to advanced data analysis, AI systems are becoming deeply embedded in our daily lives. But as we lean more into AI for convenience, efficiency, and innovation, it’s important to ask: what is the environmental cost?

1. What is AI?

AI, or artificial intelligence, is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. AI is powered by algorithms, which are sets of rules or instructions used to process data and make decisions or predictions. These algorithms are often refined using machine learning, where systems can learn from data and improve over time without being explicitly programmed for each scenario. There are many forms of artificial intelligence being used day-to-day, including search engines like ChatGPT and Google, digital assistants like Siri and Alexa, or chatboxes on websites. 

2. How AI is impacting the Planet

As AI is becoming more commonplace, the question of how it is affecting our planet arises. AI, like other forms of technology, requires energy to fuel it, but just how much is it consuming? On average, a ChatGPT query needs nearly 10 times as much electricity to process as a Google search. A single ChatGPT query requires 2.9 watt-hours of electricity, compared with 0.3 watt-hours for a Google search. AI is quickly becoming integrated into everything we do, causing a sharp increase in demand for energy consumption. Tech giants like Microsoft and Google who are incorporating AI at a rapid rate are seeing a surge in emissions due to data centers, making their goals of becoming net-zero more difficult. A recent report from the International Energy Agency has predicted that electricity demand from data centres worldwide is set to more than double by 2030 to around 945 terawatt-hours, which is equivalent to the entire electricity consumption of Japan today. 

However, it’s not just energy consumption that is on the rise. AI requires large amounts of water for the construction of data centers and the cooling of servers. 

Businesses that are seeing an escalating demand for generative AI products have significantly increased their water usage. It takes 9 liters of water to evaporate each kWh of energy used at the average data center. That’s equivalent to spending a minute in the shower. AI's projected water usage could hit 6.6 billion m³ by 2027. This is a growing issue as clean water is already a scarce resource when 2.2 billion people lack access to safe drinking water. 

AI’s environmental concerns don’t stop during its usage. There are worries about its potential unsustainable mining practices. AI hardware depends on resource extraction for rare minerals like silicon and gallium or metals like lithium and cobalt. The mining process is inherently non-renewable, depleting the finite resources of minerals. Mining disrupts ecosystems, leaving land barren and unusable, which impacts biodiversity and local communities. It can also lead to soil erosion and pollution through unsustainable mining practices. 

Most importantly, is the lifespan of these materials after its retirement. AI hardware adds to the rising disposal of electronic waste, which is hazardous due to the nature of its components. AI hardware is regularly replaced after only every few years due to quick advancements in technology. Unfortunately, many electronics are not properly recycled, leading to electronic waste that can cause further pollution. The materials used in these devices can contaminate air, soil and water when not disposed of correctly. In 2022, an estimated 62 million tonnes of e-waste were produced globally. Only 22.3% was documented as formally collected and recycled. Twenty-five U.S. states have e-waste management policies, but there is no federal law that requires electronics recycling, so most of it ends up in landfills. It is predicted that generative AI applications could add up to five million metric tons of this hazardous trash to the planet by 2030.

3. How AI Can Aid Climate Change

The good news is that AI also has the potential to help us combat climate change. Its ability to complete human learning and calculations at a faster rate is accelerating discovery and innovation. AI is being used to drive behavioral change by helping individuals make more sustainable choices. For example, Google Maps uses AI to suggest routes that have fewer hills, less traffic, and constant speeds with the same or similar ETA. It has helped to prevent over 1 million tonnes of CO2 annually. Alternatively, the start-up WasteNet is developing AI-powered recycling bins to help people recycle the correct items by using sensors and cameras to detect the type of waste deposited. It achieves an accuracy of 97%, classifying waste into six categories: paper, cardboard, glass, metal, plastic, and others. 

AI is also being used to track climate change effects and create models to reduce emissions. They are far more accurate and quick to help us navigate the Earth than the human eye. A few examples include:

• Tracking Icebergs: Scientists at the University of Leeds in the United Kingdom say their AI can map large Antarctic icebergs in satellite images in just one-hundredth of a second. They have implemented a neutral network that understands intricate non-linear relationships in complex imaging to track changes in iceberg area and thickness. This technology is allowing them to monitor conditions in Antarctica more accurately.
• Mapping Ocean Litter: In the Netherlands, an environmental organization called The Ocean Cleanup is using AI to help clear plastic pollution from the ocean by creating detailed maps of ocean litter in remote locations. Knowing how much and what kind of plastic has accumulated in the ocean garbage patches is important to determine the design of cleanup systems, the logistics of hauling plastic back to shore, the methods for recycling plastic, and the costs of the cleanup. Having a ‘map’ of the plastic and its ‘hot spots’ of concentration allows them to direct cleaning efforts to where most plastic is.
• Predicting Extreme Weather: AI is also changing the weather fore-casting space. For example, the IKI Project uses AI technology to help predict weather patterns, so communities and authorities can better plan how to adapt to climate change and mitigate its impact. This has been essential for both research purposes, but also for helping climate change vulnerable areas be prepared for the worst.
• Mapping Deforestation: ​Project Guacamaya is an AI-driven initiative combating deforestation in the Amazon rainforest by integrating satellite imagery, camera traps, and bioacoustic data. This multimodal approach provides comprehensive monitoring capabilities, enabling conservationists to detect and respond to deforestation activities more effectively.

Artificial Intelligence is a powerful tool with the potential to shape the future, for better or for worse. As AI continues to advance and integrate into nearly every facet of modern life, it brings with it significant environmental costs. From high energy consumption and water usage to unsustainable mining and electronic waste, the ecological footprint of AI is growing rapidly. These impacts raise urgent questions about the sustainability of our digital future. However, the same technology causing these concerns also offers innovative solutions. AI can drive meaningful progress in climate action. The challenge lies in finding a balance between leveraging AI’s capabilities to fight climate change while minimizing its environmental toll.