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PreprintCC BY 4.0Zenodo

From AI Scaling to AI Governance: Technological Revolutions and the Political Economy of Deployment

  • Sergei A. Strebulaev1
  1. 1Independent Researcher
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Abstract

Perspective / review essay arguing that the relevant change in AI development is not a ceiling on capability but a shift in the economic gradient of deployment. Interprets the shift through Carlota Perez's installation/deployment framework as a transition from product competition to infrastructure competition. Evaluates the Anthropic/METR embedded-evaluator arrangement and the draft bill that would generalize it through an eight-dimension framework that distinguishes observed design features from mechanisms of exclusion and from demonstrated effects. Validates the framework against the EU AI Act's conformity-assessment regime, China's algorithm registration regime, and the UK AI Safety Institute. Includes LaTeX sources, BibTeX bibliography, and Node.js DOCX generation scripts. v3 preprint.

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Cite

BibTeXRIS
BibTeX
@misc{strebulaev2026from,
  title = {{From AI Scaling to AI Governance: Technological Revolutions and the Political Economy of Deployment}},
  author = {Sergei A. Strebulaev},
  howpublished = {Zenodo},
  year = {2026},
  month = oct,
  doi = {10.5281/zenodo.23455871},
  url = {https://zenodo.org/records/23455871},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - From AI Scaling to AI Governance: Technological Revolutions and the Political Economy of Deployment
AU  - Sergei A. Strebulaev
PY  - 2026
DA  - 2026/10/18
PB  - Zenodo
DO  - 10.5281/zenodo.23455871
UR  - https://zenodo.org/records/23455871
AB  - Perspective / review essay arguing that the relevant change in AI development is not a ceiling on capability but a shift in the economic gradient of deployment. Interprets the shift through Carlota Perez's installation/deployment framework as a transition from product competition to infrastructure competition. Evaluates the Anthropic/METR embedded-evaluator arrangement and the draft bill that would generalize it through an eight-dimension framework that distinguishes observed design features from mechanisms of exclusion and from demonstrated effects. Validates the framework against the EU AI Act's conformity-assessment regime, China's algorithm registration regime, and the UK AI Safety Institute. Includes LaTeX sources, BibTeX bibliography, and Node.js DOCX generation scripts. v3 preprint.
ER  -