Anthropic's Responsible Scaling Policy, with Nick Joseph, from the 80,000 Hours Podcast
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What is the purpose of this episode and who are the hosts?
Hello and welcome to the Cognitive Revolution, where we interview visionary researchers, entrepreneurs, and builders working on the frontier of artificial intelligence. Each week we'll explore their revolutionary ideas, and together we'll build a picture of how AI technology will transform work, life, and society in the coming years. I'm Nathan LeBenz, joined by my co-host Eric Tornberg. Hello and welcome back to the Cognitive Revolution. Today we're sharing a cross post from the 80,000 Hours Podcast, in which host Rob Wiblin interviews Nick Joseph, head of model pretraining at Anthropic, about the responsible scaling policy that governs the company's frontier model development. I've been following the development of these policies and other voluntary commitments from top labs for much of the last year.
At one point I had the opportunity to participate in a workshop with anthropic team members in which we reviewed, discussed, and offered comment on the responsible scaling policy draft. However, I could not easily convert that experience to a podcast, and so I was particularly excited to see this episode published, and really appreciate that the eighty thousand Hours Podcast team has allowed me to repost it here. On the substance of the matter, I of course very much appreciate how hard Anthropic is thinking about AI risks and what can be done about them, and also how transparent and even candid they are willing to be about the substantial uncertainty that remains. I'm also very glad that their example seems to have inspired others.
OpenAI and Google have since published similar policies, and I understand that XAI is working on one as well. Unfortunately, however, the trend does not yet appear to be universal. Meta, for example, to the best of my knowledge, has not published a policy describing how it plans to evaluate models during training, let alone how they plan to proceed if it turns out that they are developing dangerous capabilities. As we happen to be sharing this episode with just a few days left before California Governor Kevin Newsom will have to sign or veto SB 1047, I will take a moment to say one more time that while it may not be the perfect AI safety bill, and indeed the release of OpenAI's O one model and the emerging paradigm of scalable inference time compute generally do suggest that the definitions in the bill would need to be updated to stay relevant over time.
In my view, the public does deserve to know what Frontier Labs are doing, and that goes double for Meta and any other companies who are openly sharing model weights. So whatever the fate of SB ten forty seven may be, I do think that we will need some measure that forces Frontier model developers to publish detailed safety plans for public scrutiny. In the last hour of this episode, Rob and Nick changed topics to focus on AI safety career advice. While this is not a sponsored episode, Nick's experience with 80,000 Hours Career Advising Service echoes my own and presents a natural opportunity to remind you that 80,000 Hours is now offering free one-on-one career advising sessions to cognitive revolution listeners.
I encourage everyone to sign up for a free session at eighty thousand hours dot org slash cognitive revolution, and especially so if you are one of the experienced software engineers that Nicknotes are in such high demand among AI companies right now. As always, if you're finding value in the show, we'd appreciate it if you take a moment to share it online with friends or write us a review on Apple Podcasts or Spotify. Your feedback is always welcome too, either via our website, cognitive revolution.ai, or by DMing me on your favorite social network. Now, for an in-depth conversation about Anthropic's responsible scaling policy and breaking into AI safety in your career, here's Nick Joseph from Anthropic, with host Rob Wiblin of the Eighty Thousand Hours Podcast.
I think this is a spot where there are many people who are skeptical that models will ever be capable of this sort of catastrophic danger.
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Chapters
8 chapters
1
What is the purpose of this episode and who are the hosts?
0:00–7:57
2
Why do many people misunderstand AI scaling laws and model training?
7:57–13:40
3
How does Anthropic’s Responsible Scaling Policy define AI safety levels and evaluations?
13:40–25:40
4
What are the biggest concerns about future risks, red‑team testing, and governance of the policy?
25:40–1:20:30
5
What unknown risks and evaluation challenges are discussed for AI safety?
1:20:30–1:37:21
6
How can external researchers and organizations contribute to responsible scaling policies?
1:37:21–1:53:25
7
Why does Anthropic emphasize communicating risk probabilities and how are they measured?
1:53:25–2:09:23
8
What career advice does Nick give about engineering vs. research roles and hiring at Anthropic?
2:09:23–2:34:56
Speakers
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