The choice between hoarding gold and pouring capital into artificial intelligence is a false one, according to a new essay in American Thinker — and the real question is whether either can be sustained without the institutional guardrails to keep it honest.
In a piece published October 18 under the headline “Which is better: Gold or AI?,” writer David DeMay frames the debate as a civilizational fork in the road: two “complementary but frequently competing responses to capital and uncertainty.” One preserves what already exists. The other bets on what might yet be built. Neither, he argues, can stand on its own.
Howard Hughes as a cautionary tale
DeMay opens with an unexpected pairing. Howard Hughes, he writes, spent his career proving that present limitations need not dictate future possibilities — in aviation, engineering, manufacturing and industrial scale, ambition bent the world to its will. But the later Hughes offers what DeMay calls “a sobering counterpoint”: a man who withdrew into isolation as the sheer scale of his empire outgrew conventional governance.
Elon Musk, in DeMay’s telling, invites a similar comparison. His ventures stretch across electric vehicles, aerospace, communications and artificial intelligence, each one pushing to radically outstrip national resource constraints. DeMay sees both men as a distinctly American phenomenon — the individual whose technological imagination grows powerful enough to challenge established institutions.
From that comparison comes the essay’s central question: what happens when the acceleration of technological capability begins to outrun the institutional architecture required to sustain it?
The global split: compute versus reserves
DeMay argues that the two trajectories are already visible on the world stage in revealing proportions. American technology companies, he notes, are committing extraordinary resources to computational infrastructure. Meanwhile, state-driven models are simultaneously developing advanced technological capabilities and accumulating physical gold.
His read on that divergence is pointed: the distinction is not between nations that innovate and nations that merely preserve. It is about the priorities each assigns to future productivity versus existing reserves. The tension between gold and compute, he writes, “cannot be resolved by raw speed or passive storage alone.”
When the machine consumes more than it creates
The essay’s most concrete warning concerns what happens as automated systems take a larger role in interpreting information and executing decisions. Unmonitored complexity, DeMay argues, becomes an increasingly consequential threat. When semantic drift turns identification into deletion, or when capital is squandered on redundant algorithmic activity, a system can consume more resources than it creates.
That is the line he draws between computational capacity and what he calls productive compute — a distinction that separates raw processing power from output that actually returns something to the civilization paying for it.
DeMay does not land on blind acceleration or fearful preservation as the answer. The resolution, in his view, requires structural accountability: an architecture that separates interpretation from execution, prevents uncertain meanings from acquiring unauthorized operational power, and keeps computational velocity tethered to measurable, productive outcomes.
His closing formulation is compact enough to serve as the essay’s thesis. “Gold preserves yesterday’s wealth,” DeMay writes. “Artificial intelligence may create tomorrow’s. Accountability determines whether promises are realized.”
The long-term prosperity of any civilization, he concludes, depends on its ability to transform the resources of the present into a durable, productive and well-governed future — before the engine outruns its foundation.
Why the argument lands now
The essay arrives at a moment when the capital flowing into AI infrastructure has become one of the defining economic stories of the decade, and when several governments have been steadily building gold reserves alongside their domestic technology pushes. DeMay’s framing treats those two moves not as opposites but as different answers to the same problem of uncertainty — one backward-looking, one forward-looking, both incomplete without a governance layer that neither market enthusiasm nor central bank caution naturally supplies.
Whether that governance layer is achievable, or whether the Hughes parallel is a warning Musk’s empire will eventually have to reckon with, is left open. But DeMay’s broader point is that the choice between gold and AI is less interesting than the question of who is accountable when either one goes wrong.
Source: www.americanthinker.com — https://www.americanthinker.com/blog/2026/10/which-is-better-gold-or-ai/