"Impact of Artificial Intelligence on Climate Change: Benefits and Challenges"

In today's world, AI is essential, but how is its excessive use damaging the environment?

As our planet struggles with the ever-growing challenges of climate change, we're now facing a new, unexpected dilemma. Artificial Intelligence (AI), which is helping us fight global warming and revolutionize the digital landscape, is itself becoming a resource-hungry force. It feels almost like a twist straight out of a science fiction novel—machines designed to save the Earth are now consuming more resources than necessary, leading to environmental consequences we hadn’t fully anticipated.

Take ChatGPT as an example. Every time you ask a handful of questions, the computers processing those responses need to cool down, consuming about 500 milliliters (roughly two glasses) of clean water. While this might seem insignificant, more advanced models like GPT-3, which are far less capable than OpenAI’s latest versions, require millions of liters of water for training.

This issue hits particularly hard for countries like Pakistan, which is already feeling the intense effects of climate change. With glaciers melting in the north and unusual rainfall causing devastating floods in the south, AI holds great promise for weather prediction and climate adaptation. Yet, in a country where record-breaking heat waves are common, and water scarcity is an ongoing threat, the environmental costs of using AI to tackle climate change can’t be ignored.

As National Geographic’s Jackie Snow writes, “Climate change is the biggest challenge facing the world today. It will require all possible solutions, including artificial intelligence.” But as OpenAI CEO Sam Altman noted at the World Economic Forum, the growing energy demands of AI present a new challenge. He bluntly stated, "Without major breakthroughs, we won't be able to meet this demand."

In this race against climate change, the question now is: Can AI help us save the planet without costing us more of it?

Artificial Intelligence (AI) has the potential to be a game-changer in the fight against climate change, playing a crucial role in managing environmental disasters and finding sustainable solutions. When used effectively, AI can act as the Earth’s nervous system, detecting, predicting, and responding to environmental threats before they escalate.

One of the standout examples is Google’s Flood Hub, which predicts floods up to seven days in advance across more than 80 countries. By 2023, this service was forecasting floods for over 460 million people in regions such as Africa, Europe, and South America, including Pakistan. In October 2023, Flood Hub expanded its services to the United States and Canada, covering over 800 riverbanks and helping more than 12 million people prepare for floods.

In California, AI-powered machine learning algorithms assist firefighters in tracking and combating wildfires. Meanwhile, AI is transforming agriculture by optimizing farming methods to reduce water consumption and improve crop yields.

The urgency of using AI in these areas cannot be overstated. According to the World Meteorological Organization, improving warning systems through AI could reduce losses from weather disasters by up to 30%. AI's role in addressing climate challenges is already yielding positive outcomes. For instance, Global Forest Watch uses AI and satellite imagery to monitor deforestation in real-time, while Google's AI Green Light project is helping 12 cities reduce environmental impacts from traffic light systems, leading to a 30% reduction in vehicle stops and a 10% decrease in carbon emissions at intersections.

In the realm of clean energy, AI is also making strides. Google DeepMind’s AI system is helping scientists control nuclear fusion plasma more effectively, paving the way for emissions-free energy. These advancements are vital to our future, but they come with significant energy demands.

AI systems, particularly those used for training large models like GPT-3, require immense computing power. Training GPT-3 alone consumes about 1,287 megawatt-hours of electricity, which could power an average Pakistani family for 2,000 years. The International Energy Agency (IEA) has forecasted that by 2026, global data center electricity demand will double, largely due to AI’s energy consumption.

AI's environmental impact goes beyond electricity. Training a large language model emits 300,000 kilograms of carbon dioxide, equivalent to the emissions of 125 round-trip flights between New York and Beijing. Researchers at the University of Massachusetts Amherst have estimated that the carbon emissions from training such AI models are comparable to the emissions of five average American cars over their entire lifespans.

Water usage is another concern. Data centers, that house the servers for AI models, require significant amounts of water for cooling. Some facilities use up to 500,000 gallons of water a day, and by 2027, AI’s water consumption could account for half of the UK’s annual water use.

The rapidly growing demand for energy and water for AI systems is not just a future problem—it’s already here. In West Des Moines, Iowa, residents discovered that a local data center used 6% of the district’s water supply during the training of advanced AI models like GPT-4. The increasing computing power needed to train these systems is doubling every 3.4 months, far outpacing the typical doubling cycle described by Moore's Law.

Furthermore, the environmental impact of AI extends to the resources required for its production. Specialized AI chips need clean water and rare minerals, while the servers that run these systems depend on an uninterrupted power supply. The batteries used to store power for these systems rely on materials that are mined at the cost of the environment.

While AI shows immense potential to help us address climate change, it’s crucial to balance its benefits with its environmental costs. As we continue to harness the power of AI, we must also focus on developing more sustainable solutions to mitigate its impact on the planet.

Artificial Intelligence (AI) has the potential to bring about transformative changes in how we tackle environmental challenges, but its impact varies significantly depending on where it is deployed. While AI has proven beneficial in areas like weather forecasting, improving energy systems, and disaster response, its environmental effects are not uniform across regions. These differences highlight the need for a more nuanced understanding of how AI intersects with climate issues worldwide.

Take, for instance, Google's data centers. In Finland, Google’s data center runs on 97% carbon-free energy, a stark contrast to its data centers in Asia, where the percentage of carbon-free energy used ranges from 4% to 18%. This gap in energy sources means that populations in different regions are exposed to varying degrees of fossil fuel consumption and air pollution, which can have disproportionate impacts on vulnerable communities.

According to Shauli Ren and Adam Weerman, as noted in the Harvard Business Review, the gap between how different regions cope with climate change iaboutAI is widening. This disparity is expected to worsen. Global energy consumption for AI is predicted to increase 10-fold by 2026, potentially surpassing the total electricity consumption of Belgium. In the United States, AI-powered data centers are projected to account for 6% of the country’s total electricity use by 2026.

In countries like Pakistan, where water scarcity is a pressing concern, the demand for water in AI systems further exacerbates resource competition. Both agricultural and drinking water could be diverted to power these systems, intensifying the strain on limited resources.

Another issue contributing to the divide is the disparity in AI expertise. A survey by Stack Overflow for the OECD revealed that 30% of the world’s AI experts are located in North America, while only 0.67% are based in Pakistan. This imbalance means that while developed nations push forward with AI-driven climate solutions, developing countries might not have access to the same resources, and the solutions offered may not meet their specific needs or address their challenges.

How Can AI Save Energy?

While AI systems require vast amounts of energy, there are ways to make them more sustainable. Major tech companies, including Amazon, Microsoft, Meta, and Google, are investing heavily in renewable energy. These companies have signed deals to add about 50 gigawatts of clean energy to the grid, which is equivalent to Sweden’s total electricity generation. But sustainability isn't just about the energy mix—it’s also about designing and optimizing AI systems for efficiency.

Google has demonstrated that training better models can save energy. Its machine learning-optimized Tensor Processing Units (TPUs) generate 93% fewer emissions compared to traditional servers. Moreover, the carbon footprint of AI systems varies depending on their location. For example, Norway's electricity grid produces just 29 grams of CO2 per kilowatt-hour, whereas in South Africa, it produces 709 grams.

In regions like Quebec, and Canada, the combination of hydroelectric power and cold weather allows data centers to use clean energy and utilize excess heat for residential heating. AI research is also shifting toward "Green AI," which focuses on improving both performance and accuracy while reducing the environmental impact. Initiatives like France’s Big Science Project aim to build large models, similar to GPT-3, with low carbon emissions.

Water conservation is another priority. Meta has experimented with higher temperatures and lower humidity in its data centers, saving up to 40% of water. Google has pledged to reduce its water use by 120% by 2030, utilizing alternative sources like wetlands and rainwater harvesting.

The key to sustainable AI lies in adopting a holistic approach that considers the entire lifecycle of AI systems—from hardware sourcing to disposal. As the Copenhagen Center on Energy Efficiency highlights, “key principles for the responsible development and use of AI should include a focus on environmental protection.”

What Does Pakistan Need to Do?

For Pakistan, the challenge of adopting AI is not just about catching up technologically; it’s about ensuring that AI adoption is sustainable. Dr. Kashif Talpur, a machine learning researcher, stresses the importance of considering the full lifecycle of AI models, noting that the energy consumed during the use phase far exceeds the energy used during training. In fact, the operational phase of AI systems, driven by millions of daily queries, is where the majority of energy and carbon emissions occur.

Dr. Talpur points out that current large AI models like ChatGPT and Gemini require substantial energy for operation, and the infrastructure needed to support them—including data centers and cooling systems—adds to their environmental impact. However, there is hope for progress. Advances in AI hardware, such as more efficient chips from NVIDIA, and software optimizations like quantization, are already showing promise in reducing energy consumption.

For Pakistan, the path forward involves not just adopting AI but ensuring it is done sustainably. This could include policies that encourage the use of renewable energy for data centers, promote water conservation, and incentivize the development of energy-efficient AI models. Furthermore, investing in local talent and including Pakistan in the global conversation on responsible AI will help ensure that the solutions developed address the unique challenges faced by developing countries.

AI holds tremendous promise for addressing climate change, but this potential must be harnessed responsibly. By focusing on sustainability, optimizing energy use, and ensuring equitable access to AI technologies, countries like Pakistan can benefit from AI’s capabilities without exacerbating the environmental challenges they already face.

In conclusion, the challenge for Pakistan—and the world—is to ensure that the AI revolution contributes positively to the fight against climate change. With careful planning and a commitment to sustainability, AI can be a powerful tool for good, helping mitigate the environmental impact and offering innovative solutions for a more sustainable future.