The Open-Weight Paradox: Why Restricting Access to AI Models May Undermine the Safety It Seeks to Protect
The governance of open-weight artificial intelligence (AI) models has been framed as a binary choice: openness as risk, restriction as safety. This paper challenges that framing, arguing that access restrictions, without governed alternatives, may displace risks rather than reduce them. The global concentration of compute infrastructure makes open-weight models one of the most viable pathways to sovereign AI capacity in the Global South; restricting such access deepens asymmetries while driving proliferation into unsupervised settings. This analysis proposes that hardware-layer governance, including chip-level attestation mechanisms such as FlexHEG, trusted execution environments, confide...
| Authors | Vinicius Santana Gomes |
|---|---|
| Primary category | cs.CY |
| Published | 19 April 2026 |
| Last updated at source | 19 April 2026 |
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