For our planet and people: IBM focuses on AI ethics for sustainability.

AI can be a force for good, but it can also lead to environmental and sustainability issues. IBM is committed to the responsible development and deployment of this technology to help our clients achieve their sustainability goals.

“AI is an incredible opportunity to solve some of the world’s most pressing challenges, in healthcare, manufacturing, climate change, and more,” said Christina Shim, Global Head of Sustainability Software at IBM and AI Ethics Committee member. “However, it is important to achieve these benefits while minimizing the environmental impact. This means making more sustainable choices about how models are built, trained and used, where processing takes place, what infrastructure is used, and how open and collaborative we are in the process.”

Design, adopt, and train AI with attention to sustainability.

The European Commission estimates that more than 80% of all product-related environmental impacts are determined at the design stage. As large language models (LLMs) grow in popularity, it’s important to decide whether you need an LLM or a traditional AI model. According to an article from Columbia University, LLM queries use up to five times more performance than traditional search engines. As data use and processing activities increase, global emissions will also increase. Therefore, it is important to design and manage systems sustainably.

IBM’s concrete actions to support AI sustainability

Creating AI requires enormous amounts of energy and data. According to the European Union’s 2023 Energy Efficiency Directive, data center electricity consumption in Europe is expected to increase by 28% from 2018 to 2030, illustrating the environmental costs of AI use. IBM has taken many steps to mitigate the environmental impact of its AI systems. In our 2023 Impact Report, we reported that 70.6% of IBM’s total electricity consumption came from renewable energy sources, including 74% of the electricity consumed by IBM data centers. By 2023, 28 data centers around the world will have 100% of their electricity coming from renewable energy sources.

IBM is focused on developing energy-efficient ways to train, tune, and run AI models, such as its own Granite-based models. With a 13 billion parameter model, the Granite model is smaller and more efficient than larger models, so it has a lower environmental impact.

In 2022, IBM launched Vela, the first AI-optimized cloud-based supercomputer. This design allows you to efficiently deploy and manage your infrastructure anywhere in the world, helping to reduce the strain on existing resources.

Other IBM products designed to support AI sustainability include:

• IBM® Envizi™ is a software suite designed to help companies simplify environmental, social and governance reporting.
• IBM TRIRIGA®, an integrated workplace management system that can help you improve energy management.
• IBM Maximo® helps you monitor, manage and maintain operations in a way that promotes sustainability throughout the asset lifecycle.

“It’s encouraging to see growing interest from customers in balancing the benefits of generative AI with long-term sustainability goals,” said John Thomas, vice president and distinguished engineer at IBM Expert Labs, and member of the AI ​​Ethics Committee. “Some of our key customers are introducing these requirements into their enterprise AI governance frameworks.”

Holistic sustainability: includes social impacts beyond the environment

IBM aspires to have a lasting positive impact on the environment, the communities where we work and live, and business ethics. In 2021, IBM launched IBM Sustainability Accelerator, a free social impact program that applies IBM technology and expertise, including AI, to strengthen and scale nonprofit and government organization solutions. This program helps populations that are particularly vulnerable to environmental threats. In 2024, IBM released its latest call for proposals on the topic of Resilient Cities, which aims to find ways to foster urban resilience over the long term. IBM plans to increase its investment in this program by up to $45 million over the next five years.

IBM is also focused on closing the skills gap in the workforce, including in AI and sustainability. Last year, IBM SkillsBuild® added a new Generative AI course as part of its new AI education efforts. IBM also launched a new sustainability curriculum to help equip the next generation of leaders with the skills for a green economy. This free training connects cutting-edge technologies to ecology and climate change.

Focus on AI ethics and sustainability in the IBM ecosystem.

IBM has a longstanding commitment to doing business with suppliers that behave with high levels of ethical, environmental and social responsibility. This commitment includes a code of conduct through the Responsible Business Alliance, of which IBM is a founding member. We support this commitment by setting specific environmental requirements for our suppliers and working with them to drive continuous improvement.

In 2022, IBM completed its first commitment to promoting AI ethical practices across the ecosystem, exceeding its goal of training 1,000 ecosystem partners in technology ethics. In 2023, we announced a new commitment to train 1,000 technology vendors on technology ethics by 2025, and we’re well on our way to doing that.

AI can augment human intelligence, increase fairness, and optimize or reduce returns. While regulation may impose some level of responsibility, developers and users must consider people, planet, and interests throughout their use of AI.

A human-centric approach to AI must improve AI’s capabilities while also adopting ethical practices and addressing sustainability challenges. As IBM infuses AI across our applications, we are committed to using AI sustainably and supporting AI stakeholders to do the same.

Learn more about IBM’s sustainability solutions Learn more about IBM’s AI ethics