How AI Contributes to Environmental Protection Efforts

Most AI users probably don’t think about the environment every time they interact with a chatbot or other AI tool. If you talk to some conscientious environmentalists, however, you’ll hear a lot about the impact of AI on the environment. The data centers that support the complex algorithmic and data handling loads of today’s AI platforms are massive, and AI’s energy usage is unparalleled. The UN’s Environment Programme explains why: These facts are daunting, and some AI critics advocate for total abstinence from these platforms until the environmental impact can be mitigated . Even so, some environmentalists are excited about the potential positive impacts of AI on environmental causes. If leaders in the AI industry can positively harness the power of AI to protect the environment while also reducing its negative environmental impact, then they can answer the important ethical questions about AI’s impact on the world around us. HVAC and refrigeration systems are one of the biggest global contributors to climate change. New federal regulations in the US create compliance requirements for most large facilities, but it’s not just a matter of complying because it’s required. Leveraging AI to improve a building’s energy efficiency saves money and helps the environment. AI systems can analyze hundreds of thousands of data points from large commercial buildings in real time, identifying patterns and opportunities for optimization that would be impossible for humans to process. This capacity allows for dynamic adjustments to heating, cooling, and other energy systems based on occupancy, weather conditions, and building characteristics. By making these small but significant tweaks to building operations, AI can dramatically reduce energy waste while maintaining or improving comfort for occupants. Much of the deforestation is caused by human activities, including logging and development, but there are also natural causes. Sometimes, a subtle change in tree cover can raise the alarm that something is going on in the environment that needs to be investigated. Monitoring these changes can also help identify illegal deforestation. AI uses satellite imagery to monitor massive forests, detecting even the smallest changes in tree cover that would otherwise go unnoticed. These systems can distinguish between natural changes, sustainable forestry, and illegal deforestation. The technology also helps quantify the carbon storage capacity of forests, which is essential for carbon offset programs and evaluating the effectiveness of reforestation initiatives. This data-driven approach to forest management supports more targeted conservation strategies. Greyparrot , a software startup in London, has developed an AI system that analyzes waste processing and recycling capabilities to help facilities recover and recycle more waste material. In 2022, Greyparrot tracked 32 billion waste items across 67 waste categories. It turns out that their system identifies an average of 86 tons of material per facility that could be recovered but is instead being sent to the landfill. AI systems like this can dramatically improve both waste sorting and recycling. By analyzing waste production in real-time, AI can optimize the recovery of recyclable materials that would otherwise end up in landfills. Keeping waste out of landfills reduces those landfills’ methane gas emissions. It’s a devastating fact that our oceans are full of garbage. AI technologies can improve ocean cleanup efforts by detecting and mapping plastic pollution in the ocean. When AI creates a detailed map of litter concentration, this data is exactly what cleanup organizations need to make strategic decisions about what to tackle next. Marine plastic pollution is a serious threat to our oceans’ ecosystems, and it contributes to climate change through greenhouse gas emissions. Organizations like The Ocean Cleanup can use AI to clear plastic pollution from the ocean more efficiently. Weather forecasting in the United States is facing challenges, especially with proposals to eliminate funding for the National Oceanic and Atmospheric Administration (NOAA). Weather industry professionals are anxiously watching what happens in the field of weather forecasting and natural disaster preparation. One of NOAA’s cutting-edge approaches to weather forecasting is the NOAA Center for Artificial Intelligence (NCAI), which is applying AI/ML tools to accelerate the analysis of large volumes of data to speed scientific discoveries that inform U.S. fishery and ocean management policy. Recent AI-supported research projects from NCAI include: AI platforms track and analyze emissions data from industrial operations to identify specific processes and equipment that contribute most significantly to a company’s carbon footprint. These insights enable targeted interventions that maximize emissions reductions while minimizing costs. By integrating data from multiple sources, including satellite imagery and on-site sensors, AI provides a more comprehensive and accurate picture of industrial emissions than was previously possible. This transparency is crucial for verifying progress toward decarbonization goals. Scientists have monitored changes in polar ice for several decades, but AI tools are making huge improvements to how this is done. Today’s scientists can use AI to analyze satellite imagery to detect and measure shifts that would take humans exponentially longer to process. This faster analysis enables researchers to track the accelerating pace of ice melt with unprecedented precision. This is what scientists at the University of Leeds have been doing. They are mapping large Antarctic icebergs in one-hundredth of a second. This technology helps scientists understand how much meltwater icebergs release into the ocean. This data helps us understand the relationship between warming temperatures and polar ice dynamics, and it can help us predict sea level rise and other climate change impacts. The environmental applications of AI present us with a pretty significant paradox. On the one hand, AI can help us monitor, predict, and mitigate environmental damage from human and natural causes. However, the environmental price tag of casual AI use is a major problem that we can’t ignore. The massive data centers that power AI systems use staggering amounts of water and produce dangerous electronic waste. This creates tension in settings where people are trying to solve environmental problems. It’s important for everyone to consider their environmental footprint. If AI platforms can figure out how to reduce their negative impact on our natural world, then we can celebrate the benefits of AI without hesitation. Our environmental challenges demand powerful tools, but we need tools that don’t exacerbate the very problems we’re trying to solve.