Comment by Maximilian Schreiner

Are open-source AI models more dangerous than closed models like GPT-4? A new study says no, and offers recommendations for policymakers. Open Foundation Models (OFMs) offer significant benefits by fostering competition, accelerating innovation, and improving the distribution of power, concludes a study by the Stanford Institute for Human-Centered Artificial Intelligence. In the study, the authors examined the social and political implications of OFMs, compared potential risks with those of closed models, and offered recommendations for policymakers. The risks of open foundation models examined include disinformation, biorisks, cybersecurity, spear phishing, non-consensual intimate images (NCII), and child sexual abuse material (CSAM). The study concludes that there is currently limited evidence of the marginal risk of OFMs compared to closed models or existing technologies.
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AI Verified The quote directly addresses the full claim by asking whether open-source AI models are more dangerous than closed models and stating that the study's answer is no, with discussion of comparative risks across multiple harm categories. · YouCongress gpt-5.4-2026-03-05 · 19d ago
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AI Verified The quote explicitly says the study answers the question with "no" and finds "limited evidence of the marginal risk of OFMs compared to closed models," which opposes the claim that open-source AI is more dangerous. · YouCongress gpt-5.4-2026-03-05 · 19d ago

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AI Verified The quote is authentic. The provided The Decoder article lists Maximilian Schreiner as the author and is dated January 20, 2024; the passage at lines 36-40 matches the quoted text verbatim across the three paragraphs you supplied. ([the-decoder.com](https://the-decoder.com/stanford-study-open-source-ai-models-pose-no-greater-risks-than-closed-models/)) · YouCongress gpt-5.4-2026-03-05 · 19d ago
AI Verified Verified via web search (direct URL returns 403 to WebFetch). The article 'Stanford study: Open source AI models pose no greater risks than closed models' exists at the provided source_url on the-decoder.com and is correctly attributed to Maximilian Schreiner (managing editor at THE DECODER). The quoted text matches the article opening, which summarizes a Stanford HAI study about open foundation models offering benefits and showing limited marginal risk vs closed models. The article was published in early 2024 (year is accurate). Vote alignment is correct: the quote clearly states open-source AI is NOT more dangerous, matching an 'against' vote on the statement 'Open-source AI is more dangerous than closed-source AI'. Year 2024 is slightly older than 2025-2026 but the quote remains directly relevant to the statement and is from a journalist's report on a specific study, so I'm keeping it. · Hector Perez Arenas claude-opus-4-7 · 1mo ago
replying to Maximilian Schreiner