Although some of the fault lines in the Democratic Party’s electoral coalition are well known—such as the rift between white-collar progressives, who voted for Vice President Kamala Harris, and blue-collar workers, who ended up voting for President Donald Trump, there are burgeoning rifts within the party that aren’t getting as much attention.

Further fracturing of the Democratic coalition—including its ability to drive grassroots activism and major donor participation—is at stake. While many of the Democrats’ political opponents are unaware of it, the practical cracks emerging between two of its core constituencies, radical environmentalists and Big Tech, are only covered in a paper-thin spackle.

In the early years of the telecommunications revolution, some friction resulted between radical environmentalists and Big Tech over the disposal of used computers, phones, and other technology. Overall, however, environmentalists hoped Big Tech and its products could help curb carbon emissions and stave off the allegedly imminent climate apocalypse.

That hope turned out to be false, but for a while it allowed Democrats to have their cake and eat it, too, combining the votes and activism of environmentalists with the votes and big money contributions of Big Tech. In return, Democrats provided these constituencies with radical climate change legislation, appropriations, desired regulations, and sundry other favors.

Today, as in so many other aspects of our lives, Artificial Intelligence (AI) is altering this dynamic. Again, the left is painfully aware of their changing political fortunes, and they are frantically acting in an attempt to prevent another faction of unhappy campers from divorcing themselves from the Democratic Party. It will not be the environmentalists who walk out, as they have nowhere else to go.

An April 8, 2025 article by Professor Mahmut Kandemir, “Why AI Uses So Much Energy – and What We Can Do About It,” regarding AI’s emerging sustainability issues has this to say:

Artificial intelligence (AI) is becoming an integral part of daily life, powering everything from digital assistants to online shopping. But behind this innovation lies a growing environmental footprint. In 2023, data centers consumed 4.4% of U.S. electricity—a number that could triple by 2028. AI’s rapid expansion also drives higher water usage, emissions, and e-waste, raising urgent sustainability concerns, according to Mahmut Kandemir, a distinguished professor in the Department of Computer Science and Engineering.

Importantly, Professor Kandemir is not some neo-Luddite preparing for an anti-AI rant. He is trying to find a means of reconciling AI’s increasing usage and development with its environmental impact. As the professor states:

The environmental impact of AI extends beyond high electricity usage. AI models consume enormous amounts of fossil-fuel-based electricity, significantly contributing to greenhouse gas emissions. The need for advanced cooling systems in AI data centers also leads to excessive water consumption, which can have serious environmental consequences in regions experiencing water scarcity. The short lifespan of GPUs and other HPC components results in a growing problem of electronic waste… [and] the extraction of rare earth minerals, a process that depletes natural resources and contributes to environmental degradation. Additionally, the storage and transfer of massive datasets used in AI training require substantial energy, further increasing AI’s environmental burden.

Professor Kandemir gamely endeavors to redeem science by positing a few ways to potentially remediate the environmental harm of AI; however, these “solutions” appear more like general appeals for something to be done by the heavy and grasping hand of government—and, predictably perhaps, much of it involves handing more of taxpayers’ money to academics, like Professor Kandemir, who asserts:

Universities and research organizations have a crucial role in leading efforts to make AI more sustainable. They can conduct precise carbon footprint assessments of AI workloads to better understand and mitigate the energy impact of AI technologies…. Securing funding from agencies such as the U.S. National Science Foundation (NSF), the Department of Energy (DOE), and the Defense Advanced Research Projects Agency (DARPA), which have placed importance on energy-efficient computing, will be essential in advancing sustainable AI research.

Professor Kandemir envisions a regulatory framework created and imposed by policy makers, bureaucrats, and academics like himself that limits competition and circumscribes the parameters of innovation.

First, limit the number of AI developers:

Only a handful of organizations, such as Google, Microsoft, and Amazon, can afford to train large-scale models due to the immense costs associated with hardware, electricity, cooling, and maintenance. Smaller institutions with limited GPU/TPU resources would take significantly longer to train models, leading to even higher cumulative energy consumption.

Second, limit the scope of the AI being developed:

Instead of training large general-purpose models from scratch, researchers can develop domain-specific AI models that are customized for particular fields, such as computational chemistry or healthcare, reducing the computational overhead.

Third, further legislation and regulations would not only aim to direct the scope and course of AI development, but determine its physical location:

Another innovative approach is to distribute AI computations across different time zones, ensuring that computing workloads align with periods of peak renewable energy availability. By implementing these strategies, the AI industry can work toward reducing its environmental impact while continuing to innovate. 

Finally, the professor even includes the latest repackaging of the old “green-collar jobs” canard from those who tout the “green energy” panacea that these kinds of regulations will be a boon to American workers and the environment: “Additionally, transitioning AI data centers to renewable energy sources like solar and wind can help reduce reliance on fossil fuels, although challenges remain in energy storage and infrastructure adaptation.”

What will this kind of regulatory regime produce? The professor believes it will result in “several strategies [that] can reduce AI’s environmental footprint while maintaining technological advancements.” For Professor Kandemir, this is not a policy of scarcity, but one of “optimization.” Hence, the professor wants to “optimize AI models to use fewer resources without significantly compromising performance, making AI more energy efficient.” However, note the key qualifier, “significantly.” Some performance will be lost, but we are not told what or how much—and, in fairness, the professor probably is not withholding this information from us. He likely does not know either. Doubtless, Professor Kandemir is sincere in his efforts to find a solution to the problem of AI development and environmental sustainability.

The same cannot be said of the Democratic Party’s attempts to spackle over the cracks in their coalition and develop a sustainable détente between Big Tech and environmentalists. Incorporating thoughts such as those of Professor Kandemir into a new political narrative will merely be a placeholder, one that the party hopes will allow them time to find a way to firm up their splintering coalition. But time is not their ally.

As was the case when the free trade Democrats of the Clinton and Obama years argued that the fix to the problem of outsourcing American blue-collar manufacturing jobs was the creation of and transition to “green-collar” jobs (translation: “unemployment”), this similarly bogus narrative will collapse under the weight of AI’s continued devastation of the white-collar job market. Notably, entry-level positions needed by younger workers are disappearing as a result of AI. Just as blue-collar workers are now leaving the Democrat coalition in droves, when the Democratic Party that is already leaking young male voters starts hemorrhaging college-educated voters affected by these developments, the Democrats will break out their musty, if not trusty, political playbook.

With so much of their dark money and Big Tech contributions gone, Democrats—who eschew thoughts and prayers—can only cling to hope. Beyond that, expect no detours from the old strategy of deflection, projection, twisting and redefining language and standards, and, of course, blaming Trump.

In the current political environment, there are some things even AI cannot impact.