Is AI Sustainable?

Businesses today face a dual challenge of adopting artificial intelligence (AI) while also ensuring sustainable practices. The AI market is booming, having grown by nearly $50 billion from 2023 to 2024 (that’s right, billion).

It now stands at $184 billion and is expected to surpass $826 billion in 2030. As AI rapidly evolves, sustainability is a global priority. So, how do we balance the growth of AI with the rising concerns of sustainability?

This article explores how you can incorporate AI sustainable practices within the Environmental, Social, and Governance (ESG) criteria to drive meaningful change. From optimizing algorithms and utilizing efficient data centers to ensuring unbiased and fair practices, AI can play a vital role in all aspects of sustainability efforts.

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The Business Case for Sustainable AI

As consumers are increasingly demanding sustainable practices, businesses are turning to sustainable AI for innovation. Sustainable AI refers to the development and use of artificial intelligence in ways that minimize environmental impact. We can also look at sustainable AI in terms of social equity and transparent governance. Businesses have a corporate responsibility to uphold ESG criteria and AI is already impacting each aspect in unique and transformative ways.

First coined by the United Nations Global Compact, ESG is a set of metrics for companies to measure their social and environmental impact. It has become increasingly important for organizations to provide strong ESG rankings in today’s competitive and climate conscious world. ESG’s are also a great way to measure how AI is impacting sustainability movements.

Let’s take a closer look at AI’s role in the environmental, social, and governance categories:

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Environmental Impact of AI

Energy consumption of AI is an increasing concern for businesses. In 2023, Google’s global greenhouse gas emissions were nearly 50% higher than 2019, which can largely be tied to its data centers. The International Energy Agency (IEA) projects that global electricity demand from AI will increase by nearly 75% from 2022 to 2026.

The rise in data centers has increased energy demands. The equipment and machines inside the data center require cooling, which, in turn, needs water. This drives electrical demand and raises energy costs. 

Energy-efficient AI practices, also known as “Green AI”, are important strategies for businesses to reduce their environmental footprint. This can include optimizing algorithms and using energy-saving hardware.

For example, DeepMind, Google’s AI subsidiary, has developed methods with machine learning and predictive outputs to reduce energy usage, particularly in cooling their data centers. This has resulted in reducing cooling energy consumption up to 40%.

Google also adapts its cooling strategies based on local conditions to manage energy and water consumption. While water cooling uses about 10% less energy than air-cooling, it can be more problematic in regions facing water scarcity. For example, in Arizona, Google opts for air-cooling to mitigate the impact on local water resources. 

Another sustainable AI example involves the retail giant, Walmart. Together with AI, Walmart helps their employees minimize food and fashion waste.

Walmart employees can scan fruit and vegetables to assess their freshness, with AI suggesting actions like lowering prices, returning items to vendors, or donating them. Similarly, AI helps manage seasonal clothing inventory, analyzing demand to make informed decisions and reduce fashion waste.

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Social Considerations of AI in Business

Ethical AI is another consideration when thinking about sustainability. Many of us have probably wondered about AI's potential to replace jobs. According to the World Economic Forum, AI could disrupt the job market on a scale similar to the automation revolution of the 1950s.

To balance this impact, companies are combining AI-driven automation with human oversight. For example, Siemens leverages AI, IoT, and data analytics to streamline production, while also keeping their employees at the front line of operations. This allows AI to handle more repetitive tasks, while humans focus on final inspections, problem-solving, and more creative work.

Companies can also use AI for ethical frameworks during the hiring process. It can support eliminating biases to ensure fair hiring and promote social equality in the workforce. Paired with diverse training and a human-centered approach, ethical AI during hiring can foster a more inclusive culture that values different perspectives and experiences.

Additionally, AI has made waves in the healthcare industry, especially for patients in underserved communities. Take the Butterfly iQ+, a portable ultrasound device powered by AI. The Butterfly Network created this device to create high-quality ultrasound images from users’ smartphones.

The Butterfly iQ+ has been used in remote areas with limited infrastructure, helping to overcome barriers to healthcare access. The company also trains healthcare workers to use the device effectively, enhancing social good through AI and expanding access to medical care where it is needed most.

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Governance and Accountability in AI

In the public sector, AI can enhance decision-making processes by promoting transparency and accountability. Explainable AI plays a large role in this context, as it bridges the gap between complex algorithms and human users. It helps build trust by clarifying how AI conclusions are reached and identifying any mistakes to prevent future ones.

Additionally, establishing an AI ethics committee is another step many organizations take to establish corporate responsibility and oversee any AI projects. An AI ethics committee can review all AI applications and assess their potential social impacts. This can be balanced with community involvement and engagement to ensure that AI applications reflect diverse perspectives and needs, and help to minimize any biases in data sets.

Overall, a company can use AI to monitor and report on its entire ESG performance. After aligning AI practices with the ESG principles, advanced algorithms can analyze data to provide insights into a company’s environmental impacts, social inclusivity, and governance practices.

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Integrating Sustainability in AI

While the concept of sustainable AI may seem daunting, it's important to focus on practical steps that can be taken today. Implementing energy-efficient AI technologies, fostering diversity and inclusion, and establishing ethical AI guidelines are key actions that contribute to sustainability.

There’s both a wealth of opportunities and challenges that come with the rise of AI and how it relates to sustainability. As these two concepts become more intertwined, focusing on the ESG impacts of AI initiatives are a good way to measure sustainable practices.

Looking forward, technology and responsibility must continue to go hand in hand. Long-term business growth is nothing without the people and communities driving it. Continuing to focus on these efforts and evaluating AI in environmental, social, and public lenses, can help lead to a more equitable and sustainable world for everyone.