Artificial intelligence is changing our lives and reshaping sectors such as education, healthcare, the environment, and workplaces. Improve accessibility with assistive technology for people with disabilities. However, the rapid development of AI raises concerns about its ethical implications and environmental footprint.
This article discusses ongoing efforts to mitigate the energy consumption of AI and its environmental impact.
Understanding AI's environmental footprint
Increased AI usage increases the demand for more data and computing power, putting a heavy burden on natural resources. The United Nations Environment Programme points out that when assessing the environmental footprint of AI, the software and hardware lifecycle must be evaluated together. Software Lifecycle It includes data collection and preparation, model construction, training, validation, deployment, inference, maintenance and retirement. Hardware Lifecycle It includes raw material extraction, production, transportation and data center construction, followed by e-waste management, maintenance and disposal. Evaluating the hardware lifecycle of AI is complicated. This is because it has an environmental impact on each stage, from mining and extraction to transport, energy and water consumption, to E-Waste generation.
The overall environmental impact of AI is divided into three categories:
- Direct: Greenhouse gas (GHG) emissions from computing, energy and water consumption, mineral extraction, pollution, and e-waste production.
- Indirect: GHG emissions from AI applications and machine learning.
- Higher Effects It can amplify existing inequality, bias, and degradation of quality in training data.
How does AI affect the environment?
The deployment of AI at scale raises several environmental concerns. Most AI servers are stored in data centers. E-waste It can contain toxic chemicals such as mercury and lead. Data centers consume a huge amount of electricity and generate greenhouse gas emissions. Also, there is a large amount of need water To cool construction and electrical components. Global AI demand is expected to consume 4.2-6.6 billion cubic meters of water by 2027, with Denmark's total annual water withdrawal exceeding 40-6 million cubic meters.
The digital economy can sometimes be considered virtual or “cloud,” but it still relies heavily on physical resources and raw materials. Digital devices, hardware and infrastructure are made from plastic, glass, ceramics, and a variety of minerals and metals. Data centers depend on Minerals and rare elementsoften mined continuously. To make a 2-kg computer, approximately 800 kg of raw materials is required.
How much electricity does ChatGpt use to answer your questions?
AI-powered virtual assistants such as ChatGpt use more energy than traditional search engines. According to the International Energy Agency (IEA), a single ChatGPT request requires 10 times more power than a Google search. The average ChatGPT query price is around $0.0036 (0.36 cents). Machine learning and AI account for less than 0.2% of global electricity demand in 2021, accounting for less than 0.1% of global GHG emissions. However, the demand for AI computing is growing rapidly. In recent years, META has seen an increase in the computing demand for machine learning training and inferences of over 100% annually. Increased use of AI will increase energy demand and use low-carbon energy sources that are essential to reducing GHG emissions.
The growing need for data centers
Data centers are the backbone for storing, processing, and distributing data from a wide range of applications, including websites, clouds, and AI services. Data centers that host AI technology consume vast amounts of energy to enhance complex electronic devices. The majority of it still comes from fossil fuels, contributing to greenhouse gas emissions. The rapid growth of AI has increased new data center investments to meet growing electricity demand. In 2022, data centers accounted for around 1% of the global market Electricity demand, This is expected to only rise. In Ireland, where the data centre market is rapidly developing, electricity demand from data centres accounted for 17% of the country's electricity consumption in 2022. If this trend continues, Irish data centres will double their electricity consumption by 2026.
The number of data centers has grown from 500,000 in 2012 to 8 million today, with experts predicting that AI's escalating energy needs will continue to grow this rapidly.
Can ai be the solution?
Despite the environmental impact, AI could also reduce its footprint. AI algorithms can identify patterns in data, detect anomalies, and predict and predict future outcomes. AI could help governments, organizations, and individuals monitor changes in the environment and make more responsible decisions. AI could also accelerate innovation in energy technology.
According to the United Nations Environment Programme's Climate Technology Progress Report 2024, AI is increasingly important in mapping the possibilities of renewable energy, optimizing efficiency, and promoting interconnectivity with other sectors such as water and agriculture. However, AI cannot completely replace physical infrastructure and governance systems that are essential for energy transitions. A strong governance framework is needed to ensure the responsible use of AI in renewable energy projects. National policies, including circular economy strategies, will help reduce the growing demand for ICT hardware and infrastructure. However, financial barriers continue, especially in developing countries, limiting the mainstream use of AI-driven sustainability solutions.
What is being done to address the environmental impact of AI?
Governments and international organizations are taking steps to mitigate the environmental footprint of AI. Over 190 countries in the UN system have adopted UNESCO recommendations on the ethics of artificial intelligence to address the ethical application of AI, including environmental impacts. The European Union has passed AI Act, a legislative framework that regulates the environmental impact of AI.
The UN Environment Programme recommends that to curb environmental fallout from AI.
- The country is developing standardized methods for measuring the environmental footprint of AI.
- The government is developing regulations requiring businesses to disclose the environmental impact of AI-based products and services.
- High-tech companies make AI algorithms more energy efficient, reduce energy demand while recycling water, and reuse feasible components.
- Countries are encouraging organizations to use renewable energy and carbon offsetting to green data centers. AI-related policies should also be integrated into broader environmental regulations.
AI and digital transformation offer opportunities for social and economic advancement, but their environmental impacts are complex and impact planetary health, environmental sustainability, and human well-being. Increased demand for critical minerals, rare earth elements, and water resources to support the expanding data center requires careful assessment. Prioritizing e-waste recycling, energy-efficient data centers, renewable energy adoption and responsible resource management is essential to mitigate the environmental impact of AI.
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