Who Can Change Course? An Integrative Review of AI Sovereignty and Collective Learning Capacity

The paper reviews AI sovereignty as a national learning capacity, using France as a case study. It introduces Human‑Centered Learning Mechanics (HCLM) to link inputs such as compute, data, talent, and capital with absorptive capacity and potential institutional losses. The authors connect this framework to neural scaling laws, growth theory, and game‑theoretic mechanisms, offering policy indicators and illustrative scenarios while noting the need for empirical testing.

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