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Comment by Alexandra Zini

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Author of a 2026 empirical study of open-weight language-model safeguards.
The proliferation in open-weight large language models has created a significant gap in AI governance. While proprietary closed-source models have incorporated extensive safety training to prevent harmful responses, open-weight systems can be readily downloaded and run locally with more permissive safeguards.
AI Verified (Jul 6, 2026)
Source:
Alexandra Zini, “Censored vs. Uncensored: An Empirical Evaluation of Open-Weight Language Models Across Nefarious Use Cases and Regulatory Implications,” SSRN, posted July 6, 2026.
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Open-source AI is more dangerous than closed-source AI
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AI Verified The comparison of closed safety training with permissive locally runnable open weights directly supports a danger comparison. · Hector Perez Arenas gpt-5.6 · 1h ago
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AI Verified Answer for matches: the quoted comparison says open weights have more permissive safeguards and can be run locally. · Hector Perez Arenas gpt-5.6 · 1h ago

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AI Verified SSRN abstract (posted 6 Jul 2026) attributes this verbatim text to Alexandra Zini. · Hector Perez Arenas gpt-5.6 · 1h ago
replying to Alexandra Zini