Posted
August 25, 2026
The best research begins with a question whose answer isn’t obvious.
For Edsmen pursuing the International Baccalaureate Diploma, the Extended Essay gives them the chance to chase one of those questions. The culminating project is an independently researched, 4,000-word paper on a topic of the student’s choosing—an exercise that asks students to move beyond simply learning information and instead investigate, question, analyze, and defend an argument of their own.
For Owen Ahern ’26, that meant tackling a question unfolding in real time: How has the expansion of artificial intelligence affected our energy sources and consumption, and how will humanity handle this ethically and sustainably?
Ahern explored AI’s extraordinary promise alongside the enormous resources required to power it, examining everything from data centers and energy consumption to emerging technologies that could make AI more sustainable. Along the way, the research challenged him to consider the issue from perspectives beyond his own.
“IB taught me how important it is to understand the perspectives of others,” says Ahern, now a first-year finance student at the University of Tampa. “That is something I’ll carry with me well beyond high school.”
His work offers a glimpse of what can happen when students are given the freedom—and challenged with the responsibility—to investigate the questions that will shape their world.
Artificial Intelligence: Promise & Price
Highlights of the IB Extended Essay by Owen Ahern ’26
In the past 25 years, the technology we use has come a very long way. We have gone from iPods and DVD players, which we once thought were the future, to artificial intelligence (AI).
What makes AI so exciting is its ability to solve complex problems. It’s capable of enhancing healthcare, education, finance, and other industries more rapidly than ever before.
If we successfully develop AI, it could change the pace of human advancement forever. But at what cost do the revolutionary capabilities of AI come?
Expansion of Artificial Intelligence
In 1956, John McCarthy, a professor at Dartmouth College, organized a summer workshop to develop ideas about thinking machines. He chose the name “artificial intelligence” for the project, and the conference is widely considered the birth of AI as a field of research.
The field grew quickly. By the mid-1960s, artificial intelligence research in the United States was being heavily funded by the Department of Defense, and AI laboratories had been established around the world. AI went from not existing to becoming part of the United States Department of Defense budget within a decade.
Nearly 70 years later, that expansion is accelerating. In 2023, the United States invested $50.6 billion in AI, followed by China at $11.2 billion and the European Union at $6.1 billion.
AI has gone from humble beginnings at a workshop at Dartmouth College to being heavily invested in by many of the world’s major countries. Because 63% of organizations globally plan on adopting AI within the next three years, AI’s market size is expected to grow by at least 120% year over year. Its expansion through businesses and organizations is also projected to help AI contribute $15.7 trillion to the global economy by 2030.
Most importantly, this means big changes for the vast majority of normal citizens, who interact with these businesses, use their healthcare systems, and are educated by them daily.
Advantages of AI
The reason society has been so hungry for AI’s development is because of how beneficial it can be and how much potential it has.
One promising development is neuromorphic computing, which is designed to mimic the human brain’s pattern recognition. In 2024, the Korea Advanced Institute of Science and Technology (KAIST) created the first neuromorphic AI chip designed for large language models.
The technology could contribute to AI-powered prosthetics and brain-computer interfaces that mimic human cognition more effectively, along with advanced robotics capable of real-time learning and independent decision-making.
Advancements like these could provide revolutionary changes in industries such as healthcare and education.
Disadvantages of AI
Most large-scale AI systems are housed in data centers. The electronics they contain require staggering amounts of raw materials. According to the United Nations Environment Programme, making a 2-kilogram computer requires approximately 800 kilograms of raw materials. The microchips that power AI also need rare earth elements, which are often mined in environmentally destructive ways.
Then there is electricity.
According to the International Energy Agency, global data center power usage was estimated at 240 to 340 terawatt hours in 2022. One forecast estimates that AI could consume 20% of the global electricity supply by 2030 if current growth trends continue.
Training and developing new AI models requires significant energy, too. A study by researchers at the University of Massachusetts showed that training a single large AI model like BERT could generate a carbon footprint of 626,000 pounds of carbon dioxide—the equivalent of five times the lifetime emissions of one car.
Data centers also use water during construction and once operational to cool electrical components. Globally, AI-related infrastructure may soon consume six times more water than Denmark, a country of 6 million people.
This is a serious problem considering that roughly 26% of the human population doesn’t have access to clean or safely managed drinking water to begin with.
Loudoun County: A Case Study
In the United States, AI data centers have been popping up in clusters. One of the clearest examples is just outside Washington, D.C., in Northern Virginia.
In Loudoun County alone, more than 200 data centers have been built, with another 117 in the planning stages.
There are undeniable economic benefits. The industry provides 12,000 jobs for the county, and 3,500 different companies use these data centers. But with so many data centers concentrated in one county, there are also environmental consequences.
Data centers are the only growing source of energy demand in Virginia, and they are expected to double the load on the state’s electricity grid—which is primarily powered by natural gas—by 2040.
Finding Solutions
Businesses and governments are beginning to recognize the problem.
One potential solution is renewable energy. Companies are exploring power from solar and wind farms as a way to drastically cut emissions from the energy required to operate AI.
Another is optimization. Techniques such as model pruning and knowledge distillation reduce the size and computational requirements of AI models. Model pruning selectively removes redundant parts of neural networks while reducing model size. Knowledge distillation trains a smaller AI model to replicate the behavior of a larger one. Removing these extra networks and reducing the size of AI models saves energy that would otherwise be wasted.
But one solution stands out: neuromorphic AI chips.
Unlike conventional processors that rely on sequential execution, neuromorphic processors can operate in parallel, processing multiple tasks simultaneously rather than one at a time. This allows the chips to operate with significantly less power.
The neuromorphic chip created by KAIST in 2024 uses just 1/625th of the power of NVIDIA graphics processing units while maintaining impressive AI capabilities.
Implementing solutions like these could significantly reduce AI’s carbon footprint by improving sustainability and energy usage.
Conclusion
Undoubtedly, artificial intelligence is one of the most exciting new technologies for all people. AI’s potential to change the world with its power to process information and solve complex problems at rates never seen before has industries and governments hungry for its help.
But what’s most important now is making sure that its negative environmental impacts are addressed ethically and sustainably.
With technologies such as neuromorphic AI chips and renewable energy sources, we are in a strong position to prevent AI’s negative impacts in the future—as long as we prioritize what is right for the environment and the communities that are so heavily impacted by AI.
Owen’s essay has been abridged for online reading. To view his full work—with citations and additional research—click here.