Trump Touts AI as Bigger Than Oil, but an 82-Year-Old Writer Asks: Is It Artificial Unintelligence?

Artificial Intelligence or Artificial Unintelligence?

Trump’s Vision and a Quiet, Generational Skepticism Collide

Former President Donald Trump recently elevated artificial intelligence to a status few technologies have ever held, calling it potentially bigger than the internet and even bigger than oil. It was a statement of supreme confidence—one that aligns with an administration that has treated AI as a strategic national asset worthy of massive deregulation and investment. Yet just as Washington leans into the AI boom, an 82-year-old writer has asked an uncomfortable question: does this rush into artificial intelligence make any sense at all?

The contrast between Trump’s boosterism and the writer’s plain-spoken skepticism crystallizes a deeper, and far from resolved, global debate. Are governments and markets overhyping AI before its risks, costs, and limits are fully understood?

Promises of Scale, Shaky Foundations

Trump’s comparison of AI to oil—a resource that reshaped geopolitics and fueled modern economies—is not hyperbole isolated to one politician. The Trump administration’s AI policy has repeatedly framed the technology as an engine of extraordinary economic transformation, one that demands light-touch regulation to stay ahead of global competitors. The underlying belief is that generative AI, machine learning, and automation will unlock productivity gains that rival or surpass the internet revolution.

But the 82-year-old writer’s commentary, published in opinion pages, cuts against that narrative with a lifetime of perspective. The core worry, distilled, is that the AI industry may be building magnificent solutions to problems that don’t meaningfully exist—or that the promised gains will simply concentrate power and wealth while introducing profound social harms.

Reality Check: Hype Versus Utility

Scrutiny of AI’s real-world impact is growing. Productivity statistics remain stubbornly flat across advanced economies despite a decade of corporate AI investment. The consulting firm McKinsey’s own research shows that while AI adoption has surged, most organizations report only modest or very localized efficiency improvements, not the step-change transformation that “bigger than oil” implies. Meanwhile, researchers at the National Institute of Standards and Technology have painstakingly documented the brittleness of even the most celebrated AI systems—their tendency to fail unpredictably, to perpetuate bias, and to require enormous, environmentally costly computing power that few companies can afford.

Energy costs alone provide a stark reality check. Training a single large language model can consume as much electricity as hundreds of homes use in a year, and the data centers underpinning the AI boom are now rivaling entire nations in their power demands. The International Energy Agency recently flagged that AI-driven data center expansion could double electricity demand in some regions by 2030, a fact that sits awkwardly beside any promise of a net benefit to society.

Political Acceleration, Societal Friction

Policy momentum is running faster than oversight. The current U.S. government has actively promoted AI deregulation, removed barriers to rapid deployment, and leaned on agencies to adopt AI tools even before rigorous testing frameworks are mature. The result is an environment in which AI is pushed into critical domains—healthcare, hiring, criminal justice, warfare—while the guardrails remain provisional at best.

The social costs are not abstract. Labor economists forecast that generative AI could automate tasks equivalent to hundreds of millions of jobs globally, with the most severe disruption striking administrative, legal, and creative roles—the very middle-class occupations that long seemed insulated. Misinformation and deepfake capabilities are advancing faster than detection tools, undermining public trust in everything from election results to courtroom evidence. And market power continues to concentrate among a handful of tech giants whose AI models depend on closed systems and proprietary data, raising antitrust questions that regulators are only beginning to entertain.

The Generational Lens

“Does the rush toward AI make any sense at all?”

The question from the 82-year-old writer is more than a rhetorical flourish. It represents a generational lens that values caution, lived experience of technology cycles, and a gut-level impatience with the breathless claims of tech evangelists. Previous transformative technologies—nuclear energy, social media, even the internet itself—were sold as unambiguous goods before their darker consequences became clear. AI, with its unique capacity to replicate and amplify human judgment, may be the first technology that demands hard questions before, not after, the damage is done.

None of this suggests that AI lacks genuine value. Medical imaging, climate modeling, and materials science are already benefiting from advanced AI. The tension is not between progress and stagnation; it is between a sober, evidence-based rollout and a speculative gold rush fueled by political and corporate interests.

The OECD AI Policy Observatory, which tracks national AI strategies across more than 60 countries, has repeatedly cautioned that most nations lack the infrastructure to monitor AI’s societal impacts in real time. Without that capacity, the “bigger than oil” dream risks becoming a bubble inflated by rhetoric, leaving the public to absorb the costs of an overheated experiment.

As Trump’s camp doubles down on AI supremacy and the skeptics refuse to be dismissed, the world is watching a policy experiment with no clear controls. Whether the end result is artificial intelligence or artificial unintelligence may depend less on the technology itself and more on the humility with which we wield it.