This repository accompanies the manuscript “AI Infrastructure Super Highway”, which examines the rapid expansion of AI infrastructure through a comparative analogy with the U.S. Interstate Highway System. The core argument is that AI infrastructure—data centers, energy systems, and network backbones—functions as a large-scale sociotechnical system that shapes culture, governance, and individual autonomy, much like highways did in the 20th century.
Using historical comparison, growth modeling, and scenario analysis, the project explores how accelerated AI infrastructure buildout may create participation defaults that make opting out of AI-mediated life increasingly impractical.
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highway_v_datacenter_growth.ipynb
Compares historical U.S. highway expansion with projected AI data center growth using generalized logistic (Richards) S-curves. -
highway_v_datacenter_transit_growth.ipynb
Analyzes information transit growth (internet vs. data center traffic) alongside highway vehicle-miles traveled.
These notebooks reproduce the quantitative analyses and figures used in the manuscript.
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datacenter_infrastructure_projection.png
Comparative growth trajectories of highway infrastructure and AI data centers. -
datacenter_transit_projection.png
Comparison of external internet traffic and internal data center traffic growth.
These figures illustrate the paper’s central finding: AI infrastructure is expanding on a much more compressed timeline than historical transportation infrastructure.
datacenter_projection_2036_2050.csv
Projection data used for long-range AI infrastructure growth scenarios.
The project frames AI infrastructure and highways as analogous sociotechnical systems along five dimensions:
- Scale and pervasiveness
- Public–private governance
- National security drivers
- Cultural and behavioral standardization
- Opt-out feasibility
The analysis shows that once infrastructure reaches sufficient scale and reliability, participation becomes the default and non-participation carries increasing penalties—social, economic, and political.
While the U.S. highway system unfolded over roughly half a century, AI infrastructure is reaching comparable societal entrenchment within a single decade. This compressed timeline narrows the window for ex-ante governance and increases the risk that long-term environmental, financial, and social liabilities will be socialized after private benefits are captured.
This repository is intended for:
- Researchers studying technological forecasting and infrastructure growth
- Policymakers and planners concerned with AI governance
- Scholars of sociotechnical systems and public infrastructure
- Readers seeking transparency and reproducibility for the accompanying paper
If you use this code or analysis, please cite the associated manuscript:
Frame, J. M., Rapp, J., Olaseinde, A., & Jones, S. AI Infrastructure Super Highway.
Submitted to Technological Forecasting & Social Change.
This project is released under the license included in the LICENSE file.