AI Geofenced Neocartography: Regulation and Resources
The new map of America isn’t political—it’s infrastructural. How natural resources and the collapse of unified federal regulation are remapping America into AI Pilot Zones and AI Free Zones.
You may have heard of Trump’s Big Beautiful Bill and its attempt to unify control of American AI governance at the Federal level. It attempted to strip states and municipalities of the right to regulate AI independently from the national government. It proposed a single, federalized framework to standardize deployment, liability, and compliance. This would’ve ensured that artificial intelligence, in all its forms, could be rapidly integrated into every sector of public life without interference from local constraints, much like how it operates successfully in China. This is in contrast to Trump’s fondness for states rights but would financially and legally benefit the titans of AI who currently advocate for ease in their business practices and sales strategies of everything from Gen AI to self-driving cars to robotics in the US Market. The sweeping, unified vision failed after facing opposition from governors, legal scholars, and civil rights advocates who viewed it as a dangerous violation of federalist principles and who highlighted the potential abuses of such centralized governance. The bill was ultimately stripped of its strict AI clauses which now makes way for state and local autonomy in AI regulation.
Rather than admit defeat, the federal government pivoted its approach and debuted a document titled America’s AI Action Plan. It was released shortly after the Federal language was stripped from the BBB, indicating it was already in process throughout the Bill’s journey in case the language was stripped and it pushed the same centralizing aims but this time, through a different tactic: Federal rewards. Rather than force compliance nationally, it incentivizes national alignment. States that support AI deployment in education, infrastructure, transportation, and labor systems would receive early access to federal funds, cloud compute credits, and public-private innovation partnerships. States that resist, those that hold out for stricter privacy protections, stronger labor laws, or precautionary oversight are not penalized outright, but simply excluded from funding opportunities. The economic incentivization message is loud and clear: fall in line and be rewarded or fall behind.
But this top-down alignment incentive strategy has introduced a new fault line—one that runs not only along the lines of state legislation, but along neighborhoods, campuses, communities and even families and individuals. Americans along with other countries citizens’ around the world are beginning to self-sort along the axis of AI comfort. In turn, some states and cities are on their way to becoming Federal AI Pilot Zones: these will be areas defined by rapid technological absorption, where drone delivery, autonomous vehicles, AI-enhanced law enforcement, and algorithmic governance are normalized, financially incentivized and encouraged. Others could be leaning toward becoming AI Free Zones: places where local laws or collective cultural values resist AI saturation and therefore ban or restrict AI presence in schools, religious spaces, or public infrastructure.
This divide could arise from ideological differences and like minded people gravitating towards one another but these collective ideologies have the power to form very real boundaries in actuality. Legal and regulatory disparities would bring technical, spatial, and potentially geofenced community boundaries. Just as electric scooters are automatically throttled or disabled when they cross invisible boundaries, AI systems, especially embodied ones like wheeled delivery robots or humanoid assistants, could easily be coded to recognize zones of exclusion and drone security or delivery services could be jammed in particular communities. In the near future, we may already see AI geofencing applied to sensitive physical locations like courthouses, hospitals, childcare centers, bathrooms, synagogues and jails. These will be spaces where robots are legally or technically required to shut down, record nothing, or operate with very particular diminished functionalities. Geofencing could emerge not just as a tool of user safety, but as a boundary-making mechanism for civil rights, spatial ethics, and local sovereignty.
On the other hand, cities that lean into AI deployment are being rewarded financially as well as with preferential federal relationships for acting as testing zones. Peachtree Corners, Georgia now functions as a semi-autonomous testbed for last-mile delivery, smart traffic systems, and AI-enhanced public safety. Chandler, Arizona hosts Waymo’s fully autonomous taxi fleet, operating without safety drivers and facilitated by state and federal cooperation. Ann Arbor, Michigan, through its Mcity program in partnership with the U.S. Department of Transportation, serves as a live model for AV integration across campus and urban life. Columbus, Ohio, a past winner of the federal Smart City Challenge, continues to receive national support to develop AI-assisted mobility systems and real-time civic data dashboards. These cities have effectively entered into AI-era public-private federalism, trading early adoption for infrastructure, visibility, and funding.
But even the infrastructure of willing communities has its limits. The AI economy is not merely built on code and policy, but on very real resources. Data centers require enormous power, constant cooling, and close proximity to water and fiber. AI is both software and material, and its footprint demands land, energy, and ecological resources. Just as the port cities of the past reigned supreme, topography, ecology, and geography are once again determining economic destiny, this time with different land and resource necessities. Rivers and harbors once defined mercantile port empires, airports shaped twentieth-century globalism and now, AI’s hubs will be governed as much by physical viability as they are by regulatory permissibility. Cities that lack water cannot cool their data centers. Regions with unstable grids or seismic volatility cannot host robotics infrastructure. Arid states with pro-AI legislation may still find themselves falling behind, not due to lack of vision, ethos or permissibility, but to lack of the massive demands of AI on power and water.
And so, contrary to the wishes of the BBB, America’s AI future will not arrive in one wave. It will unfold as a patchwork, sewn together across a variance of legal boundaries, cultural identities, infrastructure limits, and ecological realities. The federal government’s failure to preempt consistent regulation through the BBB has beckoned a new kind of cartography: one in which intelligence is zoned and unevenly distributed. Some regions will hum with the low latency of autonomous systems while others will deliberately fall quiet, embracing a slower, more analog lifestyle. Others may function like gated communities for intelligence itself, allowing only certain forms of AI in certain times and places. Underpinning it all, is the deciding factor of the land which will provide the physical foundational resources for the infrastructure necessary for the AI embrace. Those who understand this new intersection of law, code, culture, and landscape will shape the next generation of cities, and the next generation of citizenship itself.
Works Consulted
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https://www.whitehouse.gov/ostp
“Ann Arbor’s Mcity: Where Connected and Automated Vehicles Are Tested.” University of Michigan Transportation Research Institute, 2024. https://mcity.umich.edu/
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https://www.transportation.gov/smartcity
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