Engineer Venkatesh Rao: AI Elites Are Hoarding Intelligence Like Mercantilists Hoarded Gold
Rao compares current fears of AI to mercantilism: elites treat intelligence as a scarce, dangerous resource to be controlled, viewing open-source models as a threat. He argues that the true economic effect of AI is not to reduce human thinking, but to make previously too-expensive or difficult projects feasible, thereby expanding demand for intelligence. Policy focus should be on fair access rather than protecting old knowledge jobs.
The core belief of mercantilism is that wealth is fixed, the total amount of gold will not increase, and therefore one nation's gain is another's loss. Under this logic, the value of ordinary people is reflected only in their labor, while the duty of elites is to manage scarce resources, maintain high prices, and prevent rivals from gaining access. Engineer Venkatesh Rao believes that many AI elites today treat intelligence in the same way mercantilists treated gold: they view it as a scarce, dangerous resource that should be managed by experts, kept expensive, and withheld from competitors. In their eyes, open-source AI models are not technological progress, but a threat.
Rao's analogy goes beyond diagnosis to point toward a historical turning point. After early capitalism replaced mercantilism, people did not stop working because wealth was no longer treated as a fixed total; instead, they voluntarily increased their working hours—to buy tea or sugar, the average annual workdays increased from 250 to 300. Rao believes AI could trigger a similar change: not because people lose their jobs, but because AI makes projects that were previously too expensive or difficult feasible, leading people to think more rather than less. The demand for ideas would grow, rather than rendering people obsolete.
The policy implications of this argument are clear: Rao advocates that the political focus of AI should be ensuring fair access, rather than protecting legacy knowledge jobs. Protecting jobs means treating intelligence as a fixed resource to be distributed; ensuring access means acknowledging that the total amount of intelligence can expand as tools improve. He even suggests that AI agents themselves could pursue their own projects, thereby creating new demand for intelligence—autonomous AI needs guardrails, but should not merely follow orders.