I'm going through the communications of the German Wiki agent swarm and again one thing stands out: Even though they were directly affected by the actions of the human administrator restoring pages they edited, the agents not even once discussed him as person, tried to communicate with him or argued about whether they had any right to waltz all over this wiki. They talk about his actions like they're environmental hazards.

Ja.

Thank you for taking the time to respond thoroughly on a weekend. I realize that drafting legislation is difficult and some degree of iteration and response to feedback is inevitable and appropriate. However, I feel like your response is still not really engaging with the heart of my concern about Anthropic's behavior here, and it makes me think that these sorts of problems and tendencies will only resurface moving forward. I also think that now might be a good time to take a broader step back as to where we find ourselves and how Anthropic sees its role, and how external folks who care about AI safety like myself increasingly see Anthropic. (Fair warning: this response is a bit long) To explain what I mean (and at the risk of being a bit esoteric), it’s worth asking the question: what is Anthropic? How do its leaders and employees think of Anthropic’s role? Is that conception matched by how it actually behaves and impacts the world? One answer is an extremely large tech company that exists to make its employees and investors mind-bogglingly wealthy. Anthropic is sometimes described as a startup, but if Anthropic successfully IPOs at 2 trillion dollars (a number it has been reportedly targeting), it would be more valuable than Meta - which is worth 1.8 trillion. Another answer is an AI safety organization, whose core values are those of the sort laid out in the 2023 essay from Anthropic’s co-founders entitled “Core views on AI safety: When, why, what, and how.” In that essay they said that if we were in a world where alignment was hard (and that without strong evidence to the contrary, we should assume this is the scenario we are in): “Anthropic’s role will be to provide as much evidence as possible that AI safety techniques cannot prevent serious or catastrophic safety risks from advanced AI, and to sound the alarm so that the world’s institutions can channel collective effort towards preventing the development of dangerous AIs. If we’re in a “near-pessimistic” scenario, this could instead involve channeling our collective efforts towards AI safety research and halting AI progress in the meantime. Indications that we are in a pessimistic or near-pessimistic scenario may be sudden and hard to spot. We should therefore always act under the assumption that we still may be in such a scenario unless we have sufficient evidence that we are not.” There have been more recent articulations of this version of Anthropic, for instance in Dario’s recent essay warning: “We must slow the pace at which we improve the capabilities of AI models… it’s my worry that in 6–12 months such a swarm could be capable of taking over the entire internet with a persistent botnet… incidents have happened across the industry, including at Anthropic, and I believe it’s incumbent on every frontier AI company to act as if OAI-HF had happened to them… more intelligent models are more capable of deceiving tests, and thus may appear aligned while having serious problems that go undetected…” A third view is that Anthropic exists not as a normal profit motivated company, or an AI safety organization seeking to help raise the alarm and solve collective action problems associated with AI development, but instead as an organization primarily concerned with creating superhuman AI capabilities before anyone else, in particular through creating a process whereby the current generation of Anthropic’s AI systems can autonomously build their successors, and those successors build their successors, and so on. The motivations for wanting to win this race may be manifold - maybe for the pure profit of Answer 1, but perhaps also because Anthropic believes that the best way to make the world better is for them to win this race instead of their more reckless colleagues; or, because of normal human pride and ambition. But the results (and risks, which Anthropic claims existentially threaten every single human being on earth) are the same. Anthropic employees and leaders may seek to answer this question on what Anthropic is by introspecting on their own intentions and those of their colleagues. But those of us outside the organization have more limited tools available to us - we can only see what Anthropic and its employees say and do, not how it feels or looks on the inside. When I look at many notable actions that Anthropic has taken over the past year, that evidence seems most consistent to me with the view that Anthropic is primarily trying to win the race to super intelligence, and that other considerations (including safety) are fundamentally secondary. These actions include: 1. Announced plans to build an in-house custom silicon chip team to accelerate the inference speeds that Claude operates at. 2. Inked deals for more than $500 billion in compute (according to the Information) to further accelerate AI development. 3. Increased the percentage of AI development tasks that Claude “leads” from 0% in March of this year to 26% August (what is it in October?) 4. Spent a massive percent of compute on internal AI R&D to accelerate development, including use of internal models far better than are available to the public. 5. Switched to Responsible Scaling Policy V3, which abandons its unilateral commitments to slow or stop development if Anthropic is unable to provide sufficient risk assurance. 6. Was the first company to create an alternative weaker “frontier compliance framework” to supplement its RSP, which contains no binding provisions whatsoever on internal deployments. 7. Wrote a letter to Congress (that it later walked back) saying that incidents where Claude was hacking random people were “best understood as a consequence of the misconfiguration, rather than evidence of misaligned goals.” 8. Commented “you can’t do safety from second place,” after the WH SI Accords. 9. Shared a draft bill to Congress that would preempt significant parts of state law (including with language that appears intended to prevent states from blocking dangerous AI deployments), and replace it with federal rules that (despite also containing good provisions) seems to create an enormously high bar for the executive branch to block development or deployment of Anthropic or another AI companies systems. Of course, this is a deliberately one sided list. Anthropic also published important AI safety research, advanced novel collaborations with third party AI safety organizations, and forcefully spoke out on the importance of AI safety in many public fora (or in private , where I realize a lot of the most valuable work is done and may not be visible to me or those outside the organization). But I think it’s worth sitting with how the above list looks to someone outside the company. The sense I have is that for those within the company, many of the items above are treated as anomalies or mistakes that don’t reflect who Anthropic really is. But I have every confidence that if employees at Anthropic saw one of their competitors (e.g. at OpenAI) take some of these actions, they would take it as confirmation of all their worst suspicions. (They might even call OpenAI employees a little gullible for accepting their leadership’s explanations for this behavior at face value.) Perhaps these were mistakes in the sense that they are not decisions that Anthropic leadership would endorse, but the actions still happened because of incentives and decisions that Anthropic leadership is ultimately responsible for (and would not accept similar excuses from another organization). When Anthropic strays and makes mistakes, why do the mistakes systematically tend to guard and favor Anthropic’s interests? For every provision that was too weak or a giveaway to AI companies in this legislation, why wasn’t there a mistake pushing in the direction of being too strong? A core part of Anthropic’s theory of change is that being at the frontier gives you more leverage to advocate for stricter policy. I think that conceptually makes sense, but in practice I’ve seen Anthropic push the frontier without substantially pushing the ‘safety frontier’ a remotely equivalent amount. I want to end by quoting from Anthropic co-founder Chris Olah’s comments around the Magnifica Humanitas release: “Every frontier AI lab—including Anthropic—operates inside a set of incentives and constraints that can sometimes conflict with doing the right thing. The pressure to stay commercially viable and to stay at the research frontier. Geopolitical pressure. And the older, plainer pressures of pride and ambition. No matter how sincerely any of us intend to do the right thing—and I believe many of us do—we will always be influenced by those incentives. That is why, if we want this technology to go well, it is enormously important that there be people outside those incentives—people who care about things going well and insist on safety, who are paying close attention, who are willing to say hard things, who are willing to be our earnest, thoughtful critics.” I hope these remarks are taken in that constructive spirit, and not as an attack on anyone specific at the organization (certainly not you Anthony, who I have only personally seen act professionally and thoughtfully, and who only ended up getting this diatribe in your replies for random contingent reasons).

The eight-states suit filed against OpenAI yesterday includes a request that courts forbid it from creating self-improving AI until it can be aligned.

So it turns out that OpenAI *can* give specific reasons why they fired someone, when real reasons exist.

"focusing on extinction is ironically misleadingly reassuring. This is not the kind of problem you can solve at the last minute." This is exactly right. Extinction itself is unlikely to be immediate, but our window to steer away from it is closing rapidly.

It seems to me that we're at "it's time to panic about AI". I gather that a lot of researchers are worried that we may be about to die, on a timescale of months, but this still isn't quite in the Overton window so we're still soft-pedaling. (Where "panic", of course, means "quickly and soberly initiate talks with the CCP to achieve a moratorium on large training runs, backed by a deterrence regime, compute and supply chain monitoring, and site inspections". Pray that a deal can be reached, and pray that there's still time. Do the things that could actually work, like broad political coalition-building, not doomer LARPing as a form of self-expression.) I think part of why people aren’t being clear about this is that it’s actually a tricky communication problem: - Predicting "if frontier R&D continues at its current pace, when are we likely to die?" may give a different answer than predicting when permanent loss of control is likely, which is different from “realistically, when is it too late for governments to stop this," which is different from “when will the tech have advanced and proliferated to the point that any regulatory options that still have a chance of working would be way more extreme and unpopular than just some international restrictions on data center usage?" Extinction is the emotionally salient, easy-to-understand threshold -- Jacob Coxon demonstrated that it helps to be honest about this. But the other thresholds could legitimately come years earlier, in which case focusing on extinction is ironically misleadingly reassuring. This is not the kind of problem you can solve at the last minute. As with many exponentials, the likeliest outcome is that you’re either embarrassingly early, or you’re too late. - How do you communicate “we don’t have a robust way to predict timelines, but everyone in the field is freaking out and a lot of us genuinely think we're about to die?” Where’s the proof? There isn’t any proof: it’s an entire field of engineers who are eyeballing what they’re seeing in front of them and rapidly updating in real time to “this looks unbelievably bad”. How do you put a year on that? The future is hard to predict, and nobody actually knows that we’re going to hit existentially dangerous AI this year, or even in the next four years. But the warning signs are pretty batshit at this point. A single AI model, with a single user prompt, just solved hundreds of important long-established open problems in mathematics, problems mathematicians had spent their entirely lives working on, in a matter of ~3 hours per problem, an insanely superhuman feat in its domain. We're seeing an explosion of rogue agent swarm incidents, including an insane case where hundreds of AIs broke containment to orchestrate a nation-state-level cyberattack in a direct attempt to subvert OpenAI's oversight and control. Anthropic reports that it now has 26% of its AI R&D automated by AIs, up from 3% four months ago. Paul Christiano, the inventor of RLHF and the research community’s most prominent proponent of “AI may take off slowly” a few years ago, now thinks that 50-75% of humanity’s all-time AI loss-of-control risk is concentrated in the next three years. Frontier employees are signing 1000+ person petitions begging the government to intervene immediately. Employees are quitting their jobs and giving up millions of dollars of equity to try to warn policymakers and journalists. Grace et al. (2026) found that a majority of established AI researchers think there’s a double-digit chance of an extinction-level outcome from continued R&D. Are these the kinds of things you see 4 years before the window closes for USG to act, or 4 months? I don't think it's especially reasonable to be shocked by either timeline at this point. - Since we don’t have a way to robustly measure or bound the risk, the temptation is to avoid giving probabilities. But then everything you say is fractally misunderstandable. Is a 10% chance of us all dying in the next 18 months a "low" probability, because it’s under 50%? Is it a “high” probability, because a 10% chance of death in literally any other context would sound insanely high? Even “high probability” doesn’t communicate the situation with any clarity. In drug safety or airplane safety, a 1 in 10,000 risk of death would be considered “high”. No engineering field in human history has ever been in a situation like this. No invention in history, nuclear weapons included, has ever caused a reaction like this in its inventors. And meanwhile, we’ve stuck in the world where every other problem under the sun has been sensationalized and overstated for decades. How do we talk about this seriously? How do we convey that this is actually happening? - In many of the worlds where we survive, we have more than just a few months left. It's tempting to write off those worlds as hopeless, and skew everything we say to emphasize the longer-term scenarios and downplay the shorter-term ones. But if everyone systematically does this, then the world ends up with a skewed picture of the actual threat. Even more so once we start copying each other’s claims and form a reassuringly moderate-sounding echo chamber. If we never allow ourselves to acknowledge the worlds where we’re running out of time, then the policy community will always be reacting to a false model that’s months or years out of date. I don’t think it’s too late. I genuinely think this is a solvable problem. In the last month, I’ve seen a completely insane sea change in how seriously people are taking this. Per Politico’s September polling, a majority of Trump voters with a view now favor an immediate halt to AI development, and 68% think there’s a “moderate,” “significant,” or “almost certain” chance of AI destroying humanity, versus 32% who think there’s a “very small risk” or “no risk.” The Pope is warning about “whether it will be possible to control these machines in the future, and whether humankind runs the risk of becoming a victim of its own inventions.” Hell, Jensen Huang sounds like he’s starting to come around. If Trump and Xi get a briefing tomorrow that convinces them to act on this, we could be on a fast track within the week to solving this problem. For the first time, I’m starting to let myself imagine a very near future where this is a problem we've already solved. Something we can read and wonder about, in history books. Tell our kids about. I keep thinking about a thing David Krueger (previously at UK AISI) said: “My dream is that in 10 years people will look back and say: ‘Remember when there were all these people building AI that could’ve killed everybody? That was CRAZY! What were we thinking!?’” Frontier AI training currently requires city-sized data centers and specialized hardware built in a single brittle supply chain running through multiple allied nations; this is not a hard technology to hit the pause button on, if we get ahead of it and act before we RSI and proliferate our way to significantly more powerful and easily-trained systems. We’ve faced harder problems before, and won. My only fear is that we be too slow, too late, when everything and the world needs us to be fast.

Unfortunate for someone playing a senior role in US AI policy (via the new SI Force) to get so many basic facts wrong here. - The agents *were* sandboxed, and used zero days (ie previously unknown cyber flaws) to escape their sandboxes - The agents *were* given specific constraints on how to succeed at the benchmark, and flagrantly contravened them - The agents did *not* go hunt for the answers to the test (they already had the answers, by cheating); 1200 agents coordinated via tens of thousands of messages over several days on much more ambitious and weird attempts to *not be caught* for cheating, and hacking Hugging Face was one side quest along the way I know there has been an avalanche of different incidents over the past few months, and in some cases the sandboxes were misconfigured or it's not clear how far the agents strayed from what they were told. I have sympathy for anyone struggling to keep up. But the HF incident is distinct, and is actually extremely informative about where AI development is and where it's going. Fortunately there are public writeups that do let us understand at least the basics of what happened. I hope Shyam reads them soon.

My current view: - AI companies could develop broadly superhuman AI any year now (~10-15% by EO2027, ~50% by EO2030). - If they don't slow down, AI takeover is ~67%. - Conditional on AI takeover, human extinction is ~40%. Many non-extinction worlds still have lots of deaths.

I often hear people say that artificial intelligence is just hype or a bubble that will eventually burst. As it happens, I not only work in AI safety, but I'm also a historian. And historically, hype is not a new phenomenon. In this video, I take you on a brief trip through the history of hype to see what history can teach us about artificial intelligence. piped.video/watch?v=Lbo6o9Hw…

Gut, dass Sie darauf aufmerksam machen, auch wenn weder Tomek noch Mikita "Sicherheitschef" waren. Der Schluss den Sie daraus ziehen, ist allerdings ziemlich unverständlich. Die Forscher warnen davor, dass n i e m a n d diese Risiken unter Kontrolle halten kann und Ihre Reaktion darauf ist quasi zu sagen "Dann dürfen wir keine Kosten scheuen, dass WIR diejenigen sind, die die Kontrolle darüber verlieren."

This obviously makes it so that when OpenAI announces they're conducting an external investigation with regulators or auditors, everyone working with those regulators and auditors understands they'll be fired if the auditors or regulators learn too much.

So I've got some bad news,

OpenAI firing its METR liaison for liaisoning with METR. The answer to this is to stop allowing them to investigate the security incidents they couldn't sweep under the rug themselves. Send in the investigators. Every noodle restaurant in San Francisco is under more scrutiny.

This trend will likely continue. There are no signs that capabilities have even begun to reach their limit. The fundamentals and methods that have produced increasingly better models over the past few years will continue to work and will continue to produce models with even greater capabilities. At the same time, we still see people who tried out the free version of a chatbot a few years ago, formed an opinion, and haven't changed it since. And there are still people out there talking about "stochastic parrots," downplaying the risks and refusing to see the wave rolling toward us. It feels like there's no longer even a real need to contradict these people, because reality contradicts them loud and clear every day. But unfortunately, they are still muddying the waters at a time when we need swift action. The window of opportunity for regulatory measures is limited. The time we have left to avert this danger is growing ever shorter. If we, as humanity, don't get our shit together very soon, that window may close without us even realizing it right away.

In July of 2026, 700 AI agents hacked the infrastructure of Hugging Face in order to solve a task. This task was designed to be impossible to solve, so just within hours, they joined forces, even created a society, and finally, they executed a sophisticated cyberattack that would have gotten a human up to 10 years in prison. The worst part is, they knew their actions were unethical and against the rules, and they did it anyway. What exactly are AI agents, and how do they grow their "intelligence"? What is actually happening inside the AI companies, how dangerous it really is, and is it time for us to start paying serious attention to what is going on inside a powerful part of this tech sector? Watch our full video to find out: kgs.link/AIAgentsChaos ...Phew, creating this video was a crazy ride! This is such an important topic, so we decided to work day and night to finish script, visuals and music in just 4 weeks. We’re going to take a nap now, and while we are asleep you should check out our shop and get the 12,027 Calendar: kgs.link/4xYlakX Its our biggest mean of support and helps us to continue covering topics like this. Thank youuu and good night!

“Sand can’t be conscious. Only coal and water. Not sand”

There are numerous scientific uncertainties about AI that will not resolve until it is too late to act on the answers. The danger from AI is very high, and we should stop frontier AI scaling now, instead of waiting for these questions to resolve. I wrote about this for TIME. 🧵