Artificial Intelligence (AI) has been around for a short period of time but is already considered a game-changer because of its transformative potential. However, its development, maintenance, and disposal are all accountable for a large carbon footprint. This makes people worry about the environmental impact of AI. In this blog, we’ll dig deep into this hidden dilemma.
Real Environmental Impact of Artificial Intelligence: Negative vs Positive
Behind any AI, there is an energy-intensive process with a massive carbon footprint. Today AI data centers run 24/7 and use energy mostly derived from fossil fuels. They account for nearly 2.5 to 3.7% of global greenhouse gas emissions.
You’ll be shocked to know that as per OpenAI researchers, the computing power required to train the best AI models has been doubling every 3.4 months since 2012. A recent study by experts from the University of Massachusetts, Amherst, also looked at the environmental impact of training various large AI models. They discovered that this process could produce over 626,000 pounds of carbon dioxide. That’s almost 5 times the emissions of an average American car throughout its lifetime.
The table below represents the major positive and negative impacts of AI:
| Positive Impacts | Negative Impacts |
| Assists in fighting deforestation, wildfires, wildlife diseases, and monitoring biodiversity. | High electricity consumption during training. |
| Encourages Circular Economy initiatives. | Potential increase in resource usage like water and raw materials. |
| Optimizes agriculture, transportation, and waste management processes. | Contributes to electronic waste generation. |
| Predicts energy usage patterns and boosts energy efficiency. | May exacerbate existing environmental issues. |
| Improves performance in renewable energy sources. | Extensive computing time for training escalates AI emissions. |
| Manages electricity supply and enhances reliability. | Biases in training data can lead to biased decisions by AI algorithms. |
| Analyzes soil, predicts yields, and identifies pests for sustainable farming. | Higher energy demand as AI usage rises. |
| Assists in efficient disaster response. | Freshwater-intensive training contributes to water shortages. |
| Facilitates the creation of new materials. | Generates CO2 emissions comparable to aviation, affecting marginalized communities. |
| Supports biodiversity conservation efforts. | Energy consumption leads to air pollution. |
Negative Impact of Artificial Intelligence on Environment
Its main downside is linked to data centers as they consume a lot of energy to maintain AI models. Compared to regular buildings, they use about 10 to 50 times more energy per floor. With Large Language Models (LLM) like GPT-4 getting larger, the energy usage of these data centers continues to increase. Let’s discuss some environmental challenges associated with AI.
1. Increasing Energy Consumption
Training AI models consume a massive amount of electricity, which is mostly produced from fossil fuels. All this results in increased greenhouse gas emissions.
According to the US Office of Energy Efficiency and Renewable Energy, data centers, including those used for AI, account for nearly 2% of total electricity usage in the U.S.
2. Increasing Resource Consumption
The use of AI in industries such as manufacturing can increase the consumption of resources including water and raw materials. This can harm the environment.
AI training also relies on GPUs (Graphics Processing Units). For their production, rare metals and significant water usage are needed.
3. Adding to Electronic Waste
This waste consists of harmful chemicals including lead, mercury, and cadmium. Apart from polluting water and soil, they can also cause significant harm to humans as well as nature.
By 2050, the World Economic Forum predicts, we’ll produce more than 120 million metric tonnes of e-waste each year. To prevent this from happening, we need better e-waste management and recycling.
Cross-reference: Current E-Waste Management Using Artificial Intelligence Techniques
4. Impacting Natural Ecosystems
AIs such as driverless cars and delivery drones can harm animals and nature. This can lead to increased waste and consumption, especially in e-commerce, where goods are delivered quickly and often.
AI in farming might also use too many fertilizers and pesticides. This can harm water, soil, and biodiversity. Using AI for the environment also gives rise to ethical concerns. We must balance AI benefits with protecting nature for them to coexist.
5. Increasing Carbon Emission
Since AI operations are accountable for consuming a lot of energy, they are the major culprits behind increased carbon emissions. Millions of hours of computing time are spent training new generations of AI models. This further increases energy consumption.
Often, the production of this energy also depends on natural gas, oil, coal, or, hydroelectricity, which are all major sources of AI emissions.
6. Promoting Bias in Decision-Making
The major problem every anti-AI has is related to the probability of AI making biased decisions. AI algorithms heavily rely on the data they’re trained on. Biased decisions can cause biases in this data.
Using AI to control the environment raises a string of ethical worries. If its algorithm is trained on data that favor economic growth over environmental care, it might prioritize short-term economic gains over long-term environmental health.
Cross-reference: What Do We Do About the Biases in AI?
7. Increasing Energy Demand
The current trends show how AI has gradually grabbed a place in our lives as a helping tool. With time, its usage will increase more and so will its energy demand. This is thus a major contributor to greenhouse gas emissions.
For example, if current AI trends persist, by 2027, NVIDIA could deliver nearly 1.5 million AI server units each year. These servers might use about 85.4 terawatt-hours of electricity yearly. This will even exceed the energy consumption of many small countries.
8. Contributing to Water Wastage and Air Pollution
You might not know that Training AI models demand a lot of fresh water. This can also contribute to water wastage. A recent study suggests that ChatGPT requires nearly 500ml of water for every 20-50 questions and answers to cool down its data centers. This water may become contaminated with chemicals and waste. So to reuse it, extra treatment may be required.
The study also conveyed that training GPT-3 might have consumed over 700,000 liters of clean water. Unfortunately, the water evaporates during use and cannot be reused. This worsens the problem of water shortage. The energy AI uses can also contribute to air pollution, especially if it’s using non-renewable energy sources.
Also, check out How to Reduce Carbon Footprint as a Student in School or College
9. Has a Lack of Accountability and Transparency
Often, AI development and use aren’t transparent or accountable. Many companies prioritize their financial gain and competitiveness over the potential environmental harm caused by AI technologies.
AIs are also complex and due to this complexity users struggle to figure out their real environmental footprint. Moreover, the hidden data and secretive training methods used for AI development hinder the accurate evaluation of AI’s carbon footprint or environmental impact. To make sure that AI aligns with environmental concerns, we need to develop and implement transparent procedures and laws.
10. May Harm Historically Marginalized Communities
This technology is used across various sectors and generates carbon dioxide emissions similar to those of the aviation industry. These increased emissions are particularly harmful to the historically marginalized communities living in heavily polluted areas. They are more susceptible to the health risks associated with pollution.
Also Read: ChatGPT’s Thirsty Data Centers are draining Water Resources
Positive Impact of Artificial Intelligence on Environment
Don’t just overload yourself with its negative aspects, it has many positive ones as well. It has the ability to analyze vast amounts of data, like that from weather satellites. The other positive impacts associated with it are discussed below:
1. Mitigating Climate Change
AI has a massive potential to help us preserve nature and combat nature. It helps in quicker as well as broader monitoring of climate change. Its data can help us predict natural disasters accurately. This not only facilitates efficient evacuation but also minimizes minimizing damage. Here are some ways in which it helps mitigate climate change:
- Combating Deforestation: By analyzing satellite images, it helps organizations like WWF use AI, such as Forest Foresight detect and prevent illegal deforestation.
- Fighting Wildfires: By analyzing data like camera footage, it can help locate and predict the growth of wildfires. This enables the firefighters to respond more effectively.
- Detecting Wildlife Diseases: It is quick in identifying signs of diseases in wildlife. This is very helpful in early detection as well as prevention.
- Tracking Biodiversity: When AI is combined with drones and satellite footage, it can efficiently monitor changes in animal behavior. It can not only track different animal populations but also identify threats to biodiversity.
- Preventing Overfishing: AI tools like the Smart Boat Initiative can help us monitor fishing practices and prevent illegal fishing activities.
Cross-reference: AI-based monitoring aids on-farm disease detection
2. Contributing to Circular Economy
They can help contribute to a circular economy by
- Identifying and Recovering Recyclables: AI-guided robots are faster and more efficient in sorting recyclables. They help promote recycling and reduce greenhouse emissions.
- Recycling and Reusing Water: You can use AI tools to monitor water quality. They help detect pollution early and also assist in water treatment processes.
3. Optimizing Operations
They optimize operations across a wide variety of sectors:
- Agriculture: In this sector, AI tools are used to possess data on soil and weather. This not only helps enhance precision farming but also increases yields.
- Transportation: Its tools can be used to optimize routes and reduce traffic congestion. Overall, they minimize emissions caused by transportation.
- Waste Management: AI can be used to predict demand and optimize inventory. This can enhance waste management processes to reduce waste and improve efficiency.
4. Improving Energy Efficiency
The points below show how AI can improve this efficiency:
- Predicting Energy Usage: It is able to predict energy consumption patterns and can identify areas for energy conservation.
- Optimizing Cooling Systems: Companies like Google use AI to optimize cooling systems. This not only reduces energy consumption but also carbon emissions.
5. Supporting Renewable Energy
It also supports the bloom of renewable energy sources like solar and wind power. It does so by forecasting their energy production, improving their performance, and streamlining their maintenance.
For instance, GE Renewable Energy makes use of AI in its wind turbines. These turbines have sensors and AI algorithms, which can predict changes in wind conditions. They then adjust the turbine operations accordingly. This predictive ability not only boosts their energy production but also ensures that turbines are running efficiently.
6. Assisting Smart Grids
AI helps make energy grids smarter. It examines information from sensors and meters. This information helps utilities manage electricity supply and demand. This further decreases energy waste and enhances reliability.
Microsoft is also using AI to boost energy efficiency in its data centers. As a part of its sustainability goals, it is aiming to become carbon-negative by 2030.
7. Helping Sustainable Agriculture
AI can be a great support in sustainable farming. How, you must be curious. Well, it can analyze soil data and forecast crop yields. It can also detect pest and disease outbreaks. They can help farmers maximize their crop production. They promote minimum use of fertilizers and pesticides.
FarmWise is one example of AI being used in sustainable farming. It is using AI-driven robots to accurately identify and remove weeds from fields. This reduces the need for chemical herbicides and helps support their sustainable farming methods.
8. Assisting in Disaster Response
AI can speed up technological progress. This can be a game changer in disaster response. AI tools can give accurate predictions about major environmental events like weather changes, erosion, and landslides. If we have more accurate knowledge about the occurrence of a disaster, we’ll be more ready to fight it.
9. Creating New Materials
This technology can also be helpful in the creation of eco-friendly materials. They can be designed to have certain qualities like lightweight or strong. We can use such materials for construction or aerospace.
If we can make the materials from renewable sources, we’ll also reduce our reliance on fossil fuels. This also will minimize the environmental harm associated with material production.
10. Promoting Biodiversity
This is one of the major positive environmental impacts of AI. It aids in the protection of different ecosystems and species. It can analyze large amounts of data. It uses this ability to analyze data about the population, habitat, and threats related to different ecosystems and species.
Now, let’s discuss the relationship between AI and environmental sustainability. It will help us determine if they can coexist.
Also See: Urtopia Unveils World’s First Electric Bike Integrated with ChatGPT
Is Environmental Sustainability Possible Through AI?
Yes, AI can be very helpful in improving environmental sustainability. Some of the ways in which it can make environmental sustainability possible are discussed below
- For agriculture, it can be used to monitor environmental conditions and crop yields. It can even help reduce the use of water and fertilizers.
- It can optimize water usage and provide efficient water resource management. It tries to lower the management’s cost and environmental impact.
- In manufacturing, it can help make precise system designs. This can help cut down on waste and energy use in production.
- By recycling heat and tracking occupancy, it can optimize energy use in buildings. It can thus be great for facilities management.
- AI with satellite imagery helps detect changes in land use and crop diseases early on. This helps in the sustainable use of land.
- It can monitor air pollution levels and warn urban residents about pollution sources.
- It is able to manage energy supply efficiently and has improved renewable energy production forecasts.
- It detects pollution early on and thus reduces greenhouse gas emissions from vehicles.
- It can help conserve natural resources. It does so by streamlining agricultural inputs, cutting waste in manufacturing, and optimizing energy use in buildings.
Also See: Top 15+ Startups Developing AI for Energy Efficiency
Thoughts on Generative AI Sustainability by Tech CEOs and Business Schools
This is another kind of artificial intelligence that can create different types of content including images, sound, text, and synthetic data. The recent excitement surrounding it is due to its easy-to-use interfaces, which let users make top-notch text, graphics, and videos quickly.
This is what the renowned tech CEOs, companies, and business schools have to say about Generative AI:
1. According to Paul Daugherty, who is Accenture’s Chief Technology and Innovation Officer, their company advocates for actively engaging with generative AI. He says that companies should dive in, use it, experiment, and gain firsthand experience. This approach is also followed in Accenture internally.
2. According to IBM, generative AI can enhance business resource efficiency. It can do so by analyzing data for real-time energy distribution, reducing costs and emissions. It helps CEOs design sustainable enterprises. This ensures that ideals translate into actionable strategies and measurable outcomes. This will help management meet stakeholder expectations effectively.
3. Harvard Business Review states that generative AI can boost creativity for employees and customers. It can aid in generating and spotting new ideas and enhancing their quality. It can also promote divergent thinking, counter expertise bias, evaluate ideas, refine them, and foster collaboration.
4. EY states another interesting fact. It discovered that nearly 70% of CEOs recognize the urgency of adopting generative AI (GenAI) to stay competitive. But 68% are also quite uncertain about this technology. This lack of certainty is hindering their ability to act swiftly.
5. As per Deloitte’s analysis, effective digital transformation can boost market value by up to $1.25 trillion. And, Gen AI will act as a major catalyst to bring this change. With the Gen AI market doubling every other year, predictions state that AI-driven productivity enhancements could add $7 trillion to global GDP in the next decade.
So, generative AI is still new but surely is praised for its abilities. It can enhance your creativity, boost resource efficiency, and even drive digital transformations. Although, the real environmental impact of AI is recognized, CEOs are still a bit uncertain about its adoption. For more such informative content, stay tuned to our website.
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