AI Sovereignty: National Learning Capacity as a Strategic Lever
In brief
- AI sovereignty hinges on transforming distributed resources into coordinated, evaluated capabilities.
- Institutional losses (administrative duplication, regulatory uncertainty) undermine investment efficiency.
- The framework provides policy indicators and illustrative scenarios to measure public policy impact.
This paper introduces a theoretical framework to assess a country's AI sovereignty through its collective learning capacity. It examines how distributed resources (compute, data, talent) can be converted into operational capabilities, integrating economic and machine learning concepts.
What it changes for you
- Public SectorGovernments must align policies with collective learning capacity indicators to strengthen AI sovereignty.
This summary gives you the essentials. The full article, its figures and quotes are on cs.AI updates on arXiv.org.
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