The Dark side of AI

The Dark side of AI

How Artificial intelligence is contributing to climate change

Artificial intelligence has been commended as a game changer in the tech industry, with likely transforming industries from retail to medicine. However, the creation of every chatbot and image generator requires a lot of electricity, which means the technology may be responsible for a huge amount of global-warming carbon emissions.

The Dark side of AI


This article will examine into the dark side of AI and explore how its energy consumption is contributing to climate change.

The impact of AI on Energy Consumption

Major tech companies such as Microsoft, Alphabet’s Google and open AI use cloud computing that depend on thousands of chips inside servers in a massive data center across the globe to drill AI algorithms called models. This process involves in analyzing data to help them “learn” to perform tasks. AI uses more energy than other forms of computing and training a single model can eats up more electricity than 100 U.S. homes use in an entire year.

The growing energy consumption of AI

The AI sector is growing rapidly and its energy consumption is growing along with it. Sadly, there is limited transparency in the industry, so no one know exactly how much total electricity use and carbon emission can be attributed to AI. In addition, the emissions could widely depend on what type of power plants provide that electricity. A data center that draws its electricity from a coal or natural gas-fired plant will be responsible for much higher emission than one that power from solar or wind farms.

The need of sustainable AI

To reduce the environmental impact of AI, there is a need for sustainable AI. This means developing AI systems that are energy efficient and powered by renewable energy sources such as wind and solar systems. It also means creating transparency in the society, so that the energy consumption and carbon emissions of AI can be correctly measured and tracked. There are numerous ways to reduce energy consumption in data centers and we can grasp this technology to promote sustainability and protect our planet.

The need of transparency in the environmental impact of AI models

We need greater transparency on the power usage and emissions for AI models. Bitcoin has been criticized for its outsized power consumption, using as much annually as Argentina, according to the Cambridge Bitcoin Electricity Consumption index.

Training GPT-3, which is a single general purpose AI program that can generate language, used about 1.287 gigawatt hours or as much electricity as 120 U.S. homes would consume in a year, according to a research paper published in 2021. The lack of transparency makes it difficult for government and companies to determine the worth of using large models for certain applications and might bring more analysis to the industry.

Carbon Neutrality Commitments

AI models are getting larger in many cases and companies are also regularly working on the improvements that can make them run more efficiently.

Microsoft, Google and Amazon, the biggest U.S. companies have carbon negative or neutral pledges.

  • Microsoft has pledged to be carbon negative by 2030. It will remove more carbon from the atmosphere than it emits and by 2050 It will remove from the environment all the carbon the company has emitted either directly or by electrical consumption since it was founded in 1975.
  • Amazon has committed to reach net-zero carbon emissions by 2040. The company is working to power its operation with 100% renewable energy by 2025.
  • Google has pledged to be carbon negative by 2030 and will operate on carbon-free energy everywhere, 24/7.

These companies are also encouraging other companies to commit to achieving net-zero emissions by 2040. These net-zero pledges and commitments form major AI companies demonstrate a growing awareness of the environmental impact of AI and a commitment to finding a sustainable solution that will enable us to benefit from the progressive or advanced technology.

As a part of commitment to create a more sustainable future, Microsoft is investing in research to measure the energy use and carbon impact of AI and exploring alternatives to make large systems more efficient in both training and application.

Data centers and the carbon footprint of AI

As the use of AI continues to grow across industries, concerns are also growing about the environmental impact of the technology. One of the main offender is the data center, where the massive computing power demand to train AI models is sheltered.

Most of the data centers rely on the graphics processing units (GPU) to train these models, which are some of the most power-starving components in the chip industry. A single large AI model require tens of thousands of GPU’s and training process can take weeks and months to complete.

Up to now the total carbon emissions associated with these chips are mystery in the AI industry. As the world becomes more dependent on AI, it’s is very important to consider the environmental impact of the technology. The industry needs to find ways to reduce the carbon footprint of data centers and develop more energy efficient hardware and it is very essential to create sustainable future for both AI and our planet.

Net zero pledges

As the models are getting larger in many cases, the AI companies are also constantly working on improvements that make them run more efficiently.

Similarly, Microsoft has pledged to be carbon negative by 2030, meaning it will remove more carbon from the atmosphere than it emits. The company plans to achieve this through a range of measures, including using 100% renewable energy by 2025 and investing in carbon capture and storage technologies. Microsoft is also using AI to optimize its data centers, reducing energy consumption and costs. Amazon has committed to being carbon neutral by 2040, and the company is working to power its operations with 100% renewable energy by 2025. The e-commerce giant has also launched initiatives such as The Climate Pledge, which encourages other companies to commit to achieving net-zero carbon emissions by 2040. Overall, these net-zero pledges and commitments from major AI companies demonstrate a growing awareness of the environmental impact of AI, and a commitment to finding sustainable solutions that will enable us to benefit from this transformative technology without causing any harm to the planet.

Artificial intelligence has the potential to make significant changes and improvements to our society, including:

  • Healthcare: AI is being used to assist healthcare professionals in diagnosing diseases, monitoring patience conditions and developing in personalized treatment plans.
  • Finance: AI is being used in fraud detection, risk management and investment analysis.
  • Transportation: AI is used to optimize traffic flow, improving road safety, enable autonomous vehicles.
  • Gas/Fuel station: Operating a gas station requires considerable investment including maintenance, manpower and margins, with the help of artificial intelligence, gas stations can drastically improve their overall service and drive customer satisfaction. Learn more about AI-powered fuel station
  • Retail and E-commerce: AI is being used to personalize marketing, improve customer experience and in development of supply chain management.
  • Manufacturing: AI is used to advance and optimize production process, reduce waste and improve quality control.
  • Natural language processing: AI is being used in chatbots, voice assistants and language translation.
  • Entertainment: AI is being used to create virtual characters and to improve gaming experiences.

AI has some downsides and challenges that need to be conveyed, including job displacement, data privacy, safety and security risks. The mass development of AI also raises ethical questions about how we are using and regulating these technologies that need to be addressed.

Hence, it is essential to acknowledge both the benefits and challenges of AI, also work towards maximizing its benefits and minimizing its risks. Now, it requires the collaboration between policymakers, industry experts and researchers to ensure that “AI” is developed and used in a responsible, ethical and transparent manner.









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