The Safety Culture at the Labs is Broken
https://thezvi.wordpress.com/2026/10/14/the-safety-culture-at-the-labs-is-broken/📌 【Anthropic、OpenAI安全文化檢視】離職吹哨者:業界缺的是其他高風險產業的實戰經驗
TL;DR:OpenAI資深安全研究員David Robinson辭職示警,指出AI安全文化缺乏航空、核電等產業的專業經驗。
當一篇離職公開信的開場白,就是先承認「寫這種辭職吹哨文章已經變成一種套路」,那本身就該讓人警覺:套路背後藏著的問題,恐怕比表面看起來更深。
🤔 安全文化很難,連Anthropic都不夠
評論者TheZvi指出,前沿實驗室需要深厚且穩固的安全文化。Anthropic確實在這方面投入大量心力,與其技術人員對話時,能感受到明顯不同、更強的理解與責任感。但即便如此,作者認為對問題難度的掌握仍顯不足:近期一些互動讓他察覺,Anthropic內部並非人人共享這種文化,存在著「我們營運卓越,能靠邊做邊修,不像那些其他家公司」的心態,彷彿所有問題都只是尋常的技術問題。至於OpenAI,文化問題被認為更深層。本週,David Robinson辭職並吹哨,同時OpenAI也解僱了三名安全研究員,疊加過去的多起事件,以及OpenAI與Anthropic雙方近期都出現的misalignment報告。
🧩 David Robinson是誰?為何他的辭呈特別不一樣
David Robinson在OpenAI任職三年半,是公司任職最久的員工之一。他主筆了公司現行的Preparedness Framework,並主導了12次前沿模型發布的安全報告撰寫,也是Astra系統卡(system card)的主要撰寫人。他在辭職文章中提出兩項訴求:第一,AI公司應該更多借助航空、核電、金融等其他領域已經存在的安全專業知識——他在任職期間,不記得曾遇過有過讓飛機安全飛行、讓核反應爐不熔毀,或讓金融體系穩健成長經驗的同事;第二,在打造明顯更強大的系統之前,需要新的科學研究,確保更強大的模型(及其後繼者)在沒有人監看時仍會做出安全的選擇。他主張前沿實驗室該像核電廠或繁忙機場那樣運作,仰賴多層備援與謹慎、耗時的規劃,讓偶發的人為失誤不至於打開通往災難的門。
💡 業界吵起來了:迭代部署該不該被重新檢討
這篇文章引發不少業界人士公開回應。曾任職OpenAI的Miles Brundage表示,他後悔當年幫忙推廣「迭代部署」(iterative deployment)這個概念,認為這種做法或許在GPT-3時代勉強說得通,但在已有死亡案例與人們憂心滅絕級風險的現在已不合時宜,他特別點名問題在於「帶著已知缺陷出貨」卻無助於真正加速學習,只是加速了出貨。OpenAI的roon則持相反意見,認為迭代部署本身是一次巨大的成功,如果現在因此學到規模化太危險,那正是透過迭代部署這個過程才學到的。OpenAI的Joshua Achiam則回應,David的批評有實質內容,值得認真對待,並形容David是冷靜、思慮周到的人,並非帶著既有的存在風險意識形態進入這份工作。
⚠️ 一篇評論,還沒有具體解方
必須說明的是,這整篇文章本質上是評論與引述業界人士言論的整理,並未提出具體的新制度或技術解方;對於Google、Meta近期分別推出Argon、Wonder後是否會加劇競爭壓力,作者也坦言現在評估還太早。
🎯 給在lab裡做safety工作的工程師
這篇文章的核心訊息值得在前沿實驗室或任何高風險系統上工作的工程師留意:安全報告、框架與承諾固然重要,但沒有紮根的安全文化,規則終究可能被想鑽漏洞的人繞過;從其他已經走過慘痛教訓的高風險產業(航空、核電、金融)借鏡具體的操作實務,而不只是套用抽象原則,可能才是補上缺口的關鍵一步。
🔗 來源
- 標題:The Safety Culture at the Labs is Broken
- 作者/機構:TheZvi(Don’t Worry About the Vase)
- 連結:https://thezvi.wordpress.com/2026/10/14/the-safety-culture-at-the-labs-is-broken/
#AISafety #OpenAI #Anthropic #Whistleblower #AIAlignment #SafetyCulture #AIGovernance #IterativeDeployment #Preparedness #ResponsibleAI
原始資料 Don't Worry About the Vase · 收集於 2026-10-14
摘要原文
We need the frontier labs to have a deep and robust safety culture. Anthropic devotes considerable effort to cultivating and maintaining such a culture. It shows, especially among the members of technical staff. Having conversations with them can be a very different experience than talking to those at other labs, and there is a much greater sense of understanding and responsibility. But even there, the appreciation of the problems and their difficulties seem woefully insufficient. We see various symptoms of that more and more. Recently, while I’ve had some good interactions, I’ve also had interactions that make clear that much of Anthropic does not share that same safety culture, with a lot of ‘oh we will muddle through because we are better at operational excellence unlike those other idiots’ and a belief that all the problems are prosaic. Culture is hard. Then there are OpenAI’s cultural problems, which clearly run deeper. That point was only driven further home this week, with David Robinson resigning to blow the whistle, and OpenAI feeling forced to fire three of its safety researchers , on top of many past problems and incidents. That is on top of additional misalignment reports from both OpenAI and Anthropic. The reports are good things, but what is reported emphasizes that we have big problems that run deep. Thus, the growing consensus that we must find a way to Pace the Frontier and slow the pace of AI capabilities advances. This is potentially made more complicated by what could be increased competitiveness from Google and Meta, with the releases of Argon and Wonder. It is still too early to provide proper assessments there. There is a growing group of lab employees who have felt compelled to quit in protest. New York Magazine had a cover feature interviewing some prominent ones. The most famous is Coxon, who provided the tipping point for the current preference cascade. David Robinson became the latest researcher to resign from OpenAI and sound the alarm about the industry’s utterly irresponsible approach to safety. He also went on The Ezra Klein Show , which gives you a rich idea of where he is coming from. David Robinson was the lead writer for the Astra system card. That could help explain why he felt the OpenAI safety culture was broken. That card is screaming that things are horribly wrong, for those with ears to hear. David is not even that worried about existential risk. His worries are mundane, and he realizes that even on that level OpenAI’s safety culture is deeply broken. As always, we deeply thank him for sounding the alarm. I hope to write his name in these posts many times over the coming months and years. When you have to open your whistleblowing essay about the lack of safety at OpenAI saying it has become a cliche to blow the whistle on the utter lack of safety at OpenAI, there might be a problem with the lack of safety at OpenAI. David Robinson : What I’m about to tell you has, I realize, become something of a cliché: I resigned this week from OpenAI. I led the writing of the safety reports we published with each major launch. Now I’m joining a parade of former colleagues—at OpenAI and the industry’s other leaders—who have decided that the current path is unacceptable. I agree with other recently departed staff that the companies building this technology aren’t being nearly careful enough. But I believe that we need to look deeper than specific rules or new laws. We need to talk about culture. We have to look at rules, and at laws, and also at culture. The more I thought about various potential laws and regulations, or safety and security plans or other commitments, the more I concluded that without a strong safety culture, and without the spirit of the rules, there is no hope. You cannot, in any reasonable way, have rules that cannot be gamed by those determined to game them. Two changes are urgently needed. First: AI companies need to rely more on the safety expertise that already exists in other fields. And second, before we create systems significantly more capable than the ones we have today, we need new science to ensure that more capable models (and their successors) will make safe choices when we aren’t looking. Given today’s risks, frontier labs need to run like nuclear-power plants or busy airports, with layers of redundancy and careful, time-consuming planning, so that the occasional and inevitable human error does not open a door to disaster. Even though, as I detail later, David Robinson is not on the existential risk train, he still understands that alignment is a science problem, and we will need new science. ‘Oh it will not kill literally everyone,’ even if it were true, would not be an excuse to not do the safety work. It should be hard to argue with either of those suggestions. And yet. We have experts in mundane safety and solving prosaic issues. OpenAI does not hire them, and neither to my knowledge do Anthropic or Google or anyone else. After three and a half years at OpenAI, I was among the longest-tenured employees at the company. I led the drafting of our current Preparedness Framework, and oversaw the writing of safety reports on 12 frontier launches. But as far as I know, I never encountered a colleague who had experience making airplanes fly safely or nuclear reactors run without melting down, or helping the financial system grow without collapsing. To be clear, this is a new need: Today and tomorrow’s AI systems are far more capable and dangerous than the systems we were building even six months ago. I disagree only with the final sentence. This is not a new need. You need to prepare for the future, not only for the present. Even setting that aside, mundane safety issues have been crippling AI’s potential utility for years. This is a slam dunk thing to do. Miles Brundage : David’s right. I regret helping spread the idea of “iterative deployment” which maybe briefly made sense in the GPT-3 era but makes no sense at all after many deaths have been tied to AI and as we’re careening towards extinction-level risks. The industry needs to mature ASAP. Elaborating on iterative deployment – obviously you should learn from experience the things that can’t be learned without experience. The issue is when you ship things with *already-known* flaws, in a way that doesn’t actually speed up learning but just speeds up shipping. … Also, as usual it bears repeating that this is not just an OpenAI issue. roon (OpenAI): you shouldn’t regret it. iterative deployment was a massive success. if we’ve now learned that it’s too dangerous to scale much further, we will have learned that lesson thanks to the process of iterative deployment Miles Brundage : So I think part of the issue is people mean tons of different things by it lol if it just means “don’t sit on stuff forever/get some real world experience,” sure, no regrets. It’s the “giving license to sloppiness” part that I should have realized would happen w/ that term. Michael Caley : this is by far the best “I quit my AI job over safety concerns” essay yet because it is the first one that talks about safety concerns in practical terms and that understands “safety” as a topic with extensive literature and best practices in analogous fields Joshua Achiam (OpenAI): David’s critique is substantive and deserves careful consideration. My impression of David from our time overlapping at OpenAI is of a sober and thoughtful person who didn’t approach the work from an ideological lens. This isn’t someone who came in with pre-formed opinions about existential risk; he wasn’t to my knowledge an EA. He was consistently productive, collaborative, and well-reasoned in his approach to safety. The core of his critique – that professional safety engineering practices from other fields haven’t taken enough root in AI safety – is substantial and correct.
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