Charbel-Raphael Segerie
https://crsegerie.github.io/
Living in Paris
Updates:
The global call for AI red lines got 300 media mentions, and was picked up by the world’s leading newswires, AP & AFP, and featured in premier outlets, including Le Monde, NBC, CNBC, El País, The Hindu, The NYT, The Verge, and the BBC.
Yoshua Bengio, presented our Call for Red Lines at the UN Security Council: “Earlier this week, with 200 experts, including former heads of state and Nobel laureates [...], we came together to support the development of international red lines to prevent unacceptable AI risks.”
Thanks!
As an anecdote, some members of my team originally thought this project could be finished in 10 days after the French summit. I was more realistic, but even I was off by an order of magnitude. We learned our lesson.
This paper shows it can be done in principle, but in practice curren systems are still not capable enough to do this at full scale on the internet, and I think that even if we don’t die directly from full autonomous self replication, self improvement is only a few inches away, and is a true catastrophic/existential risk.
Thanks!
Yeah, we were aware of this historical difficulty, and this is why we mention “enforcement” and “verification” in the text.
This is discussed in the Faq quickly, but I think that an IAEA for AI, which would be able to inspect the different companies, would help tremendously already. And there are many other verification mechanisms possible e.g. here:
I will see if we can add a caveat on this in the Faq.
If random people tomorrow drop AI, I guarantee you things will change
Doubts.
Why would random people drop AI? Our campaign already generated 250 mentions and articles in mass media, you need this kind of outreach to reach them.
Many of those people are already against AI according to different surveys and nothing seems to happen currently.
We hesitated a lot between including the term “extinction” or not in the beginning.
The final decision not to center the message on “extinction risk” was deliberate: it would have prevented most of the heads of state and organizations from signing. Our goal was to build the broadest and most influential coalition possible to advocate for international red lines, which is what’s most important to us.
By focusing on the concept of “losing meaningful human control,” we were able to achieve agreement on the precursor to most worst-case scenarios, including extinction. We were advised and received feedback from early experiments with signatories that this is a more concrete concept for policymakers and the public.
In summary, if you really want red lines to happen for real, adding the word extinction is not necessary and has more costs than benefits in this text.
Thanks a lot!
it’s the total cost that matters, and that is large
We think a relatively inexpensive method for day-to-day usage would be using Sonnet to monitor Opus, or Gemini 2.5 Flash to monitor Pro. This would probably be just a +10% overhead. But we have not run this exact experiment; this would be a follow-up work.
This is convincing!
If there is a shortage of staff time, then AI safety funders need to hire more staff. If they don’t have time to hire more staff, then they need to hire headhunters to do so for them. If a grantee is running up against a budget crisis before the new grantmaking staff can be on-boarded, then funders can maintain the grantee’s program at present funding levels while they wait for their new staff to become available.
+1 - and this has been a problem for many years.
I find it slightly concerning that this post is not receiving more attention.
By the time we observe whether AI governance grants have been successful, it will be too late to change course.
I don’t understand this part. I think that it is possible to assess in much more granular detail the progress of some advocacy effort.
Strong upvote. A few complementary remarks:
Many more people agree on the risks than on the solutions—advocating for situational awareness of the different risks might be more productive and urgent than arguing for a particular policy, even though I also see the benefits of pushing for a policy.
The AI Safety movement is highly uncoordinated; everyone is pushing their own idea. By default, I think this might be negative—maybe we should coordinate better.
The list of orphaned policies could go on—for example, at CeSIA, we are more focused on formalizing what unacceptable risks would mean, and trying to trace precise red lines and risk thresholds. We think this approach is: 1) Most acceptable to states, since even rival countries have an interest in cooperating to prevent worst-case scenarios, as demonstrated by the Nuclear Non-Proliferation Treaty during the Cold War. 2) Most widely endorsed by research institutes, think tanks, and advocacy groups (and we think this might be a good candidate policy that should be pushed in a coalition). 3) Reasonable, as most AI companies have already voluntarily committed to these principles during the International AI Summit in Seoul. However, to date, the red lines have been largely vague and are not yet implementable.
P(doom|Anthropic builds AGI) is 15% and P(doom|some other company builds AGI) is 30% --> You need to add to this the probability that Anthropic is first and that the other companies are not going to create AGI if Anthropic already created it. this is by default not the case
I’m going to collect here new papers that might be relevant:
Why Do Some Language Models Fake Alignment While Others Don’t? (link)
I was thinking about this:
Perhaps this link is relevant: https://www.fanaticalfuturist.com/2024/12/ai-agents-created-a-minecraft-civilisation-complete-with-culture-religion-and-tax/ (it’s not a research paper, but neither you I think?)
Voyager is a single agent, but it’s very visual: https://voyager.minedojo.org/
OpenAI already did the hide-and-seek project a while ago: https://openai.com/index/emergent-tool-use/
While those are not examples of computer use, I think it fits the bill for a presentation of multi-agent capabilities in a visual way.
I’m happy to see that you are creating recaps for journalists and social media.
Regarding the comment on advocacy, “I think it also has some important epistemic challenges”: I’m not going to deny that in a highly optimized slide deck, you won’t have time to balance each argument. But also, does it matter that much? Rationality is winning, and to win, we need to be persuasive in a limited amount of time. I don’t have the time to also fix civilizational inadequacy regarding epistemics, so I play the game, as is doing the other side.
Also, I’m not criticizing the work itself, but rather the justification or goal. I think that if you did the goal factoring, you could optimize for this more directly.
Let’s chat in person !
I’m skeptical that this is the best way to achieve this goal, as many existing works already demonstrate these capabilities. Also, I think policymakers may struggle to connect these types of seemingly non-dangerous capabilities to AI risks. If I only had three minutes to pitch the case for AI safety, I wouldn’t use this work; I would primarily present some examples of scary demos.
Also, what you are doing is essentially capability research, which is not very neglected. There are already plenty of impressive capability papers that I could use for a presentation.
For info, here is the deck of slides that I generally use in different context.
I have considerable experience pitching to policymakers, and I’m very confident that my bottleneck in making my case isn’t a need for more experiments or papers, but rather more opportunities, more cold emails, and generally more advocacy.
I’m happy to jump on a call if you’d like to hear more about my perspective on what resonates with policymakers.
See also: We’re Not Advertising Enough.
What’s your theory of impact by doing this type of work?
We need to scale this massively. CeSIA is seriously considering to test the Direct Institutional Plan in France and in Europe.
Relatedly, I found the post We’re Not Advertising Enough very good, and making a similar point a bit more theoretically.
Right, but you also want to implement a red line on a system that would be precursors to this type of system, and this is why we have a red line on self-improvement.