Artificial Intelligence Makes Energy Demand More Complex — And More Achievable

Artificial intelligence, a field known for its expanding uses across society, is also increasingly notorious for the massive amount of energy it needs to function. In a 2024 paper(opens in new window), researchers from Carnegie Mellon University and machine learning development corporation Hugging Face found that generative AI systems could use as much as 33 times more energy to complete a task than task-specific software would.

“The climate and sustainability challenge can be overwhelming in the amount of new clean technology that we have to deploy and develop, and the ways that the energy system has to evolve,” said Costa Samaras(opens in new window), head of the university-wide Wilton E. Scott Institute for Energy Innovation(opens in new window). “The scale of the challenge alone can be overwhelming to folks.”

However, Carnegie Mellon University’s standing commitment to the United Nations' Sustainable Development Goals and its position as a nationally recognized leader in technologies like artificial intelligence mean that it is uniquely positioned to address growing concerns around energy demand, climate resilience and social good.

The research in sustainability and climate solutions that happens across the university’s seven schools and colleges — as exemplified by the countless and ongoing contributions of researchers like Harry Kresja, Destenie Nock, Azadeh Sawyer(opens in new window), Emma Strubell(opens in new window), and many others — reflects the expertise and innovative spirit that makes Carnegie Mellon uniquely suited to address modern energy and sustainability challenges.

On March 25, Carnegie Mellon University kicked off its Energy Week(opens in new window) event, a gathering which brings together national leaders from industry, government and research to Carnegie Mellon's campus to learn about and share advancements being made around the country. The Scott Institute proudly champions efforts at the intersection of energy, climate, technology and public policy, and the conference serves as its flagship annual event.

But Energy Week is also a chance for the university to spotlight the growing need — and ability — of institutions and individuals to solve problems at the intersection of AI and energy.

How does the Scott Institute leverage energy expertise?

Samaras, director of the Scott Institute, has brought a wealth of experience in engineering and climate action to CMU. Having left the university to serve in the Biden-Harris Administration(opens in new window) from 2021-24, he has seen the landscape of energy innovation from one of the highest offices in the land.

Before returning to Carnegie Mellon, Samaras helped to craft an executive order on artificial intelligence, penning a section that defined how the technology intersects with America’s energy system and the climate.

Now leading the Scott Institute, Samaras said Energy Week serves as a chance for individuals and institutions who interface with energy systems to take a similar approach to the problem. Among them are several from Carnegie Mellon's own campus, such as The Block Center for Technology and Society(opens in new window).

"We hold Energy Week every year, and it was clear to us even last summer that the intersection of AI and energy was going to have broad interest to the community as this year’s topic, but also serve as a way to showcase all the different work that's been happening at this intersection at Carnegie Mellon."

How does Carnegie Mellon strive to address AI and energy imbalance?

”What I've seen at Carnegie Mellon is that people here understand the scale, and they welcome the challenge,” Samaras said.

One of the ways the university has sought to take on the task is through the expertise of The Block Center, which seeks to address the question of how technologies like AI can be harnessed for social good and quality of life improvements.

In 2024, the center published a transition memorandum(opens in new window) in order to help guide incoming policymakers, industry leaders and society as a whole on issues of technological change and its demands.

Among the energy-based challenges the memorandum seeks to address are the difficulty in coordination of industry resources, a lack of transparency in energy and emissions reporting, and the inadequacy of existing metrics for knowing AI’s environmental impact.

How are experts addressing misconceptions about AI and energy?

The relationship between sustainability and artificial intelligence isn't one that simply stops at making AI more energy efficient, Samaras said. 

"I think a lot of people look at this challenge of, ‘How do we get to net-zero climate pollution? How do we ensure that we increase energy resilience? How do we ensure that we increase energy affordability?’ And they look at these challenges as individual silos that need to be tackled by individual disciplines." Samaras said. "Carnegie Mellon doesn't think like that. Carnegie Mellon says, ‘Let's get together and solve this problem and we'll bring together all the different skills and perspectives that we have in the research in the university and beyond.’"

It also requires looking at how AI tools can be used to bolster existing infrastructure and amplify ongoing efforts to solve problems holistically.

The work of individuals like Rayid Ghani(opens in new window), Distinguished Career Professor in the Machine Learning Department(opens in new window) and the Heinz College of Information Systems and Public Policy(opens in new window), is one example of how this cross-disciplinary approach can look.

Ghani often looks at the applications of machine learning and artificial intelligence not exclusively in a climate context, but concerning a wide range of social and economic potential. His research primarily focuses on how to use the technology to promote social good in areas such as public health, economic development and urban infrastructure.

But Ghani said the impact of AI on energy efficiency and sustainability has implications for many of the other areas of research and application that happen at CMU — and taking an approach that centers socioeconomically disadvantaged and impacted people is one of the most important ways the university works to make AI sustainable.

“Working on these problems throughout my career, I realized that they are all connected. A lot of the work I initially did required being opportunistic and seeing where I could make a difference,” he said. “For instance, why do we care about something like clean air? It's not for the sake of the air — it's about the people who are breathing the air. It's not about just any single thing, and so you can’t focus on energy, or the environment and not worry about all the other things that impact people’s health.”

Many experts at Carnegie Mellon approach their chosen subject matter with a similar mindset, and leveraging interdisciplinary expertise is one of the main ways that the Scott Institute has been able carry out its mission.

“The Scott Institute, leading this effort on AI and energy, benefits from continued partnerships with institutes like The Block Center to understand the workforce and social dimensions, CyLab(opens in new window) to understand the cybersecurity challenges, the Carnegie Mellon Institute for Strategy and Technology(opens in new window) to understand the political dimensions, and the College of Engineering’s(opens in new window) Critical Technologies Initiative(opens in new window) to understand supply chain and materials challenges,” Samaras said.