Rural Land and AI Data Centers
Massive AI data centers are now consuming vast tracts of rural land, displacing farms and ranches that are vital for America’s food independence.
This land appropriation by major tech companies is frequently justified with various arguments, ranging from competing with China in AI to claims of job creation and economic growth, as well as bolstering technology and national security.
However, Daniel Horowitz argues that we are being misled.
He suggests that we are being told, almost insistently, that giving away our land—often to foreign investors—is essential to excel in artificial intelligence. But, Horowitz warns, “the most certain way to land ourselves in a techno-feudal nightmare where we possess nothing is by concentrating our most cherished land resources away from American families, homesteaders, ranchers, farmers, and small businesses into the hands of global tech giants.”
In a recent episode of “Conservative Review,” Horowitz engaged with AI software expert Michael Cation to analyze the three primary claims made by advocates of AI data centers.
1. The China Argument
Proponents assert that to achieve AI superiority over China, the U.S. must erect expansive hyperscale data centers, sacrificing rural land in the process. Horowitz counters that this is a misleading choice.
He states that the argument positions this as the sole path to gaining an edge in AI, but, rather, it misallocates resources from sensible applications of AI technology. Furthermore, in a rush to establish these large data centers, the U.S. is relinquishing substantial portions of rural farmland and power infrastructure to major corporate developers, many of whom are foreign-owned. Horowitz pointed out President Trump’s recent proposal to allow a trillion-dollar investment from China into American land and factories. This, he believes, would only allow China to acquire more U.S. infrastructure when the aim was to limit their influence.
2. Jobs and Economic Development
Supporters also argue that building sizable data centers in rural locales will create thousands of construction jobs and stimulate local economies. Horowitz has a different view, calling this reasoning deceptive. He suggests that these large centers primarily offer temporary, low-wage construction jobs, often performed by outsourced labor, and they also lead to the destruction of productive farmland while escalating local crime.
He cites an example from Wyoming, where the Laramie County Planning Commission is planning an 800-person camp that could accommodate up to 5,600 workers. He expresses concern that this influx is likely dominated by undocumented workers, and points to similar facilities being linked to increased local crime rates.
3. Technology and National Security
Another justification for these data centers is that they are crucial for advancing cutting-edge AI technology and for national security purposes. Proponents argue that only these centralized facilities can offer the immense computing power needed to outpace adversaries like China in critical domains like defense and intelligence.
Again, Horowitz raises concerns, suggesting that large centralized data centers could pose a national security risk rather than serve as a solution. He emphasizes that AI capabilities don’t solely reside in cloud-based systems; with edge computing, much can be done locally, on-site, with greater efficiency.
He points to Israel’s Iron Dome as a case in point—dependent on localized processing instead of larger, vulnerable data centers. Horowitz argues that a reliance on centralized data hubs could present significant security vulnerabilities, especially with ongoing conflicts, for example, between Israel and Iran.
Cation reinforces this by stating that within the defense sector, large data centers are seen as high-value targets, further complicating security. Together, they maintain that the true direction for effective and secure AI development lies in decentralized computing methodologies—approaches that offer speed, cost-effectiveness, and enhanced resilience compared to large, centralized data facilities.
If you want to dive deeper, you might consider watching the complete episode mentioned above.
