Use common sense before lighting up nuclear plants for Artificial Intelligence

By James J. Devine

A few months ago, Microsoft struck a 20-year deal to purchase energy from a nuclear power plant located about two hours west of Trenton. The facility that will be brought back online to supply power is at Three Mile Island in Pennsylvania, where the worst-ever nuclear accident on US soil occurred in 1979 because one of its reactors had a partial meltdown.

Artificial Intelligence (AI) has rapidly become integral to various industries, powering everything from chatbots to complex data-driven solutions.

While AI’s applications continue to advance, so does its massive energy consumption—an issue that is beginning to raise alarms across the United States and around the world.

With AI’s insatiable appetite for power, and the insatiable greed exhibited in corporate board rooms that seem to dictate government policy today, your family’s life is just not valuable enough to stop the reckless march toward disaster without a fundamental awakening among American voters.

The growing demand for energy to power AI systems could have far-reaching consequences, not only for local economies like New Jersey’s but for the nation and the global fight against climate change.

A significant shift is underway as the proliferation of AI tools—especially large language models (LLMs) such as OpenAI’s ChatGPT—relies heavily on vast computational power.

The energy required to run these AI systems is enormous. In fact, some experts have likened every query to ChatGPT to the energy consumption of a lightbulb running for 20 minutes.

In states like New Jersey, which has seen a growing number of data centers housing AI and tech infrastructure, the impact on energy grids could soon become unsustainable.

The Strain on U.S. Power Grids

The energy consumption associated with AI is now seen as a major challenge for the country’s power grids. Across the U.S., data centers, which host the computing resources for AI, consume a staggering amount of electricity.

According to estimates from energy analysts, AI systems, particularly those involving deep learning and neural networks, can require thousands of kilowatt-hours (kWh) of energy per hour of processing.

For context, the energy needed to train just one AI model can exceed that of an average American household’s energy usage for an entire year.

New Jersey, with its proximity to New York City and its growing tech sector, is seeing a sharp uptick in the number of energy-intensive data centers.

The state’s current grid, which still relies heavily on fossil fuels, faces increasing pressure to meet these surging demands. Already, the state has invested heavily in renewable energy sources, but the transition is slow, and the continued reliance on fossil fuels raises concerns about meeting both energy and environmental goals.

Despite efforts to clean the grid, the challenge of balancing growing energy demands with sustainability goals persists.

The concern is compounded by the expansion of AI, which has been projected to double energy consumption in the U.S. over the next decade if left unchecked.

Without changes, the U.S. could struggle to meet its own clean energy targets set by policies such as the Clean Power Plan and other emissions reductions goals.

Nuclear Power: A Controversial Solution

One of the most contentious debates emerging around this issue is the possible return of nuclear energy as a means to meet the surging demand for electricity.

Nationwide, there is increasing support—particularly from large technology companies—for the expansion of nuclear energy.

With AI’s insatiable appetite for power, the possibility of bringing back nuclear power is once again being discussed, despite the history of environmental and safety concerns tied to nuclear energy.

Many large tech companies, including Google, Microsoft, and Amazon, are now eyeing small modular reactors (SMRs) as part of their long-term energy strategies.

These reactors are seen as more flexible and potentially safer alternatives to traditional large-scale nuclear plants. However, experts caution that the technology remains unproven and fraught with regulatory and safety hurdles.

The U.S. government, under President Biden, has backed the development of advanced nuclear technologies, including funding for SMRs, but the reality of implementing these projects on a large scale remains uncertain.

Even if new reactors can be developed, the process of siting, constructing, and operating nuclear plants could take decades, delaying any potential relief for overburdened grids.

A Global Challenge

The energy consumption of AI doesn’t just affect the U.S. The global implications are profound, especially as more countries race to harness the benefits of AI.

According to the International Energy Agency (IEA), the demand for electricity from data centers worldwide is expected to triple by 2030.

This places an immense strain on global energy supplies, especially in countries like China, India, and the European Union, where growing populations and industrial activities are already pushing the limits of current energy systems.

Countries are seeking ways to balance AI’s promise with the environmental and economic costs of powering these technologies.

In Europe, for instance, countries are leaning heavily into renewable energy sources like wind and solar, but these have limitations in terms of reliability and scalability.

As a result, nuclear power has again become a topic of serious conversation in many parts of the world, particularly in Europe, where countries like France and the UK are already expanding their nuclear fleets.

Global discussions about AI’s energy impact also extend beyond the issue of power generation.

The environmental impact of training AI models, particularly their carbon footprint, is a growing concern. AI firms and governments are under increasing pressure to ensure that the energy used to power these systems comes from clean, renewable sources. As AI continues to grow in prominence, managing its energy demands will become crucial in meeting the world’s climate goals.

Balancing Innovation and Sustainability

The challenge for New Jersey, the U.S., and the world will be finding a way to meet the surging energy demands of AI without sacrificing climate commitments. Solutions may lie in a combination of renewable energy, more efficient AI models, and an ongoing reevaluation of the role nuclear power should play in the energy mix.

For New Jersey, the question is whether the state can continue its progress toward clean energy while accommodating the expanding needs of the tech sector.

Should nuclear energy play a role in this transition? Advocates for small modular reactors are pushing for more flexibility in the state’s energy policy, but they face opposition from environmental groups who remain skeptical of nuclear energy.

Nationally, a broader conversation about the energy needs of the tech industry, AI, and other emerging technologies is necessary.

There is no one-size-fits-all solution. The path forward will require cooperation between government, industry, and environmental organizations to create a sustainable and efficient energy system that can support the technological advances of the future while preserving the planet.

The word from the White House is, “drill, baby drill” but the reality is that the climate crisis is real no matter what Fox News would have us believe.

AI’s rapid growth has brought profound societal benefits but also significant challenges. As the technology continues to expand, its energy consumption will likely be one of the most pressing issues of the coming decade.

While AI has the potential to revolutionize economies and industries, its environmental impact could offset these gains if left unchecked. And some of the smartest people on the planet have warned that it has obviously has some potentially terrifying harmful consequences, but these too are largely ignored by money hungry fools and their minions in government.

The U.S., and New Jersey in particular, must balance the demands of innovation with the imperative to reduce carbon emissions. The role of nuclear energy—whether through advanced, small modular reactors or traditional plants—will undoubtedly be a key part of this ongoing conversation.