Gustavo Lacerda, surfing the Pareto frontier (@gusl) header
Gustavo Lacerda, surfing the Pareto frontier (@gusl) profile picture

Vibemetafuturologist. Formerly @Metaculus, @Google, @Columbia Stats, @CMU. Judgmental Forecasting, Interpretability, CompCogsci, Causality.

Berlin, Berkeley, Brasil
Joined March 2008
Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)Photo by Gustavo Lacerda, surfing the Pareto frontier (@gusl)
Sometimes I wish we had a richer language for describing our senses. I have a blog post about why this is difficult for senses other than sight and sound: gusl.substack.com/p/linguist…
Replying to @relic_radiation
the power of language to render things distinguishable. english is lacking words to describe sensory realms of experience. I admire sanskrit for all extra words it has, that make sensory navigation more coherent & reproducible. I might simply start using it, tbh
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*rubs eyes* I can't tell anymore is this real or just a Don't Look Up outtake?
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Here's a secret I've kept for 22 years: When I was in college, whenever I was assigned a difficult math problem that I couldn't solve, I Googled it to look for the answer--and when I found one, I had no qualms about copying it down in my homework. It didn't feel like cheating, because that's never been the part of math that appealed to me. When I found a solution online, I loved reading through it. Seeing the clever ideas that take down a hard problem was almost like watching a slow-mo video of Usaine Bolt running: I enjoyed the aesthetic beauty of seeing something that I could never achieve myself but which I could still appreciate. And I loved zooming in on all the details, delighting in the spectacular power on display. It never felt like cheating because my goal in math was to learn math, and reading solutions I found online helped me learn math, whereas staring at a blank page did not, and trying problems and getting them wrong was often even worse. I was not a good problem solver, so a large number of problems went nowhere for me. On the other hand, I've always been drawn to communication. So when I found a solution online, I tried to translate it into my own words, my own understanding. Was this to avoid getting caught? Perhaps. But it was more than that--I genuinely enjoyed, and learned from, the process of digesting math that was above my level and trying to put my own spin on it. I've been thinking back on this college experience because of what AI is doing to math today. So many people I see online are fretting that AI is solving hard problems, leaving it unclear what humans should do. And saying that AI is undercutting learning because to learn math one must wrestle with problems. Perhaps I'm an outlier here, but I just don't see it that way. I think that by being a poor problem solver my whole life, and by being more interested in story-telling and exposition, I have unwittingly been preparing myself for the AI math singularity for many years! Regarding teaching: I really don't think we need to solve problems to learn math--because that's never how it worked for me anyway. I think we can still teach all the beautiful concepts and theories and tell all the stories than animate math, and even show people how to do calculations and how to solve problems, but then just as I used Google 20 years ago, I think we can let our students use AI however they wish but we should have students verbally explain ideas, concepts, calculations to us--or do so in writing but without access to devices. Let students use AI the way I used Google: to show them mathematics that they can then digest and internalize. Regarding research: Nearly every paper I've published in my career has been coauthored, and in all these collaborations I was largely the one who focused on asking questions, finding examples to illustrate our ideas, and extracting a story from our results to develop into the introduction. My collaborators all helped me with these things too, but they also were way better at calculations and solving problems, so I let them take the lead on those fronts. I wouldn't have gotten anywhere in math were it not for these powerhouse collaborators. What I'm thinking now is that I can increasingly use AI for those functions, while the parts that were my focus are more solidly on the human side of things, for now at least (you can't train for them with reinforcement learning the way you can the problem solving and proving parts of math). So, maybe it's just luck, but I feel like AI is doing the parts of math that I never liked and was never good at, and letting me soar higher into the parts I love despite my limited abilities. I suspect there are plenty more people like me. We needn't be quiet--I'm not ashamed to confess my weakness and disinterest in problem solving. Perhaps by me confessing it, it will be easier for you to do so as well. Regarding the overall feeling of unease and disorientation many mathematicians have been expressing lately, here's my view (apologies in advance for a stretched metaphor). I feel like we have a map of the night sky with hundreds, perhaps thousands, of dark patches, and a telescope was just invented that we can point at these and illuminate many (but not all!) of them. Lots of people worry what will be left for astronomers to do as we've spent thousands of years mapping the cosmos. But many of the images from this telescope are difficult to interpret, so that's one thing for us to work on. And those dark spots that remain dark despite pointing the telescope at them--they take on an increased import and awe, for we must now wonder at why some remain dark while others do not. And with this more complete map of the cosmos we can work toward grander challenges such as uncovering the laws of physics holding this night sky together, contemplating the origins and future of the universe, looking for the larger patterns that we never previously had enough data for. In other words, what's left for us is all the things that I find truly exciting, much more so than the tedious work of filling in missing patches of our map. Above all, there is the incredible, beautiful, challenging, and deeply personal/human act of finding stories in all this space exploration and all this new data. What a wonderful time to be a mathematician!
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The lightcone needs you to lock in son
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But as more work is handed to AI—including AI safety research—these judgment calls are the main levers for people's own values to influence outcomes. If people defer to AI without noticing, then "human in the loop" might provide less assurance than people expect.
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For those who don’t know, ETH is the hypothesis that 3SAT needs exponential time. Very surprising and consequential that it is false.
An internal model at OpenAI has produced a claimed refutation of ETH! Russell Impagliazzo, Mohan Paturi, and I have been asked to help organize an open and independent examination of this claim. 1/4
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🚨ATENÇÃO: Nos ajude a fiscalizar as canalhices de prefeitos bolsonaristas!
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Gustavo Lacerda, surfing the Pareto frontier retweeted
URGENTE Por todo Brasil, estamos vendo ataques ao direito ao voto. Falta de ônibus nas linhas, violação da gratuidade, metrôs e trens mais lentos, etc. Isso é o bolsonarismo. A negação das liberdades democráticas e da livre escolha popular.
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Uploading my CV changed the answer to ~1700.
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😂 I asked Claude: "How far would I need to travel back in time to be the world's top mathematician?" A: ~1600
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Uploading my CV changed the answer to ~1700.
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The Alignment Journal publishes research on the scientific foundations of understanding, predicting, and steering artificial intelligent systems. As of today, submissions are open to everyone. What we do differently: - We pay reviewers, with bonuses for speed and insight. - Review discussion is confidential, but every accepted paper is published with a “review summary” to distill the insights generated. - Each paper is judged against our acceptance bar, not against other submissions. - Papers under review are listed publicly, and researchers can nominate themselves to review, so each paper can reach the reviewers who know the topic best. We seek work that builds theoretical or otherwise principled analyses of agency, robustness, incentives, interpretability, generalization, and long-term behavior, and whose significance survives the deletion of any particular model, dataset or benchmark. Empirical investigations of such ideas are welcome, and negative results are encouraged. We are especially interested in approaches that could apply to future superintelligent systems that interact and self-improve. You can submit your preprint in any format. Submissions are rolling and open now on the website. If you are instead interested in reviewing or serving as an action editor (basically: an area chair), create an account on our website. Links to submit, our scope and the reasoning behind the Journal are in the reply ⬇️
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One of my friends who's a math professor got ~1860.
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I'm seeing the Overton window shift this month. More & more of my sources are starting to say out loud: Hey Anthropic/OpenAI, you could just stop unilaterally! That'd be good! You're not playing 11-dimensional chess or a classic prisoner's dilemma, you're playing Russian Roulette
I think we should stop AI progress now, first unilaterally by key AI companies and then scaling up to more US companies and then China via international agreements. The reason for now is not that current AI models are the ones that could kill everyone, but because the coordinate steps take time. Immediate action means we have more time for the second steps. When I tell this story to AI company folk, the typical response is "Yes pausing is good, but we should wait until the last minute when the very next model will be dangerous, and stop then." What I realized recently is that this is being implicitly way more optimistic about government speed than I am (and I joined the UK government and was happy there for 2.5 years). They are imagining a world where, the moment the danger is imminent, a bunch of international coordination can happen on a dime. Which is entirely inconsistent with their actual views about government! I'm the one that is more optimistic about government; why am I the one advocating for more time cushion to let the government story play out?
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Very good intro to AI X-risk arguments.
Many people with relevant expertise think there's a real chance that AI could kill us all in the not too distant future. Others disagree. I've written a post, aimed principally at mathematicians, detailing my struggles to decide what to make of this. gowers.wordpress.com/2026/10…
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I think we should stop AI progress now, first unilaterally by key AI companies and then scaling up to more US companies and then China via international agreements. The reason for now is not that current AI models are the ones that could kill everyone, but because the coordinate steps take time. Immediate action means we have more time for the second steps. When I tell this story to AI company folk, the typical response is "Yes pausing is good, but we should wait until the last minute when the very next model will be dangerous, and stop then." What I realized recently is that this is being implicitly way more optimistic about government speed than I am (and I joined the UK government and was happy there for 2.5 years). They are imagining a world where, the moment the danger is imminent, a bunch of international coordination can happen on a dime. Which is entirely inconsistent with their actual views about government! I'm the one that is more optimistic about government; why am I the one advocating for more time cushion to let the government story play out?
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Anthropic has made a lot of costly sacrifices out of conviction. At the same time, I have found the cynical view of Anthropic outperforming the optimistic view, in many ways, over the last year, when I try to predict what the company will do. You would do poorly to model Anthropic as only caring about its stock price. That's clearly wrong! But the costly sacrifices are mostly for things - China, biosecurity - that Dario is personally highly motivated by, and it's much less clear which costly sacrifices have been made on behalf of "humanity not losing control to AI" or "crucial decisions about the fate of humankind being made by everybody, even at the cost of them being made less well-according-to-leadership". Takeover in particular is something Dario seems less worried about than many of his employees. But the employees who are more worried than him about losing control have great confidence he'll make strategic sacrifices for this goal, on the strength of the sacrifices he's made for goals he seems much more convinced are a real problem. As for crucial decisions being made by everybody - Anthropic has made some efforts at this. But because making this happen would be insanely difficult, for Anthropic to actually achieve it they'd have to make truly heroic efforts at it, instead of distracted and cross-pressured ones. When Anthropic was founded, its creators took for granted that they should not be trusted alone with - that no one should be trusted alone with - the power that building a superintelligence would imply. But everyone has a plan until you get punched in the face. Their rapid growth and especially this year’s events seem to have shaped Anthropic in a more defensive, less pluralistic, less liberal direction, which scares me given that it also has brought them a lot closer to AGI. The recent safety bill was really reflective of this. It does not suggest a company that is trying to get policymakers to make the decisions Anthropic's technical staff think are coming up. It kind of suggests a company that thinks the best thing that can be hoped for from the executive is that it enforce the export controls and not get in the way. A lot of people don't seem to even want Congress to pass a bill! And like, frequently that is the best thing that can be hoped for from Congress, yet - I think that the typical person in Anthropic still regards themselves as having a lot of duties to all of humanity, to liberal and pluralistic institutions, etc. But almost every effort that Anthropic originally made to set hard constraints to which they are subject (rather than being subject mostly to their best judgment), they have subsequently come to regret as ill-conceived, and while they could have replaced them with better-conceived hard constraints, they haven't. They've largely replaced them with something that rests on their judgment more. (I think the embedded evaluators are a counterexample and I am glad of them.) The gap between the capabilities of models used internally and publicly seems to me to be growing (I think it should ideally be as close as possible to zero). Anthropic does not, broadly, seem to me to have good institutional governance - guarantees that allow its auditors independence, strong contractual protections for its workers (I'd like them to be able to go on strike if they thought it was a good idea, honestly). Incident reporting is happening on a best-judgment basis. And you can be like, that's because this is all insane and happening really fast and we're doing our best! And yeah, the thing that needs to happen is very difficult. But it does still need to happen and it doesn't look like Anthropic's on track to do it. And it's also not fully clear that Anthropic leadership agrees with me that there's a real issue here. No external criticism is every very convincing, right, when you have secret information and a set of factual beliefs that everyone else thinks are insane. I have more context on Anthropic than almost anyone and yet I cannot phrase my worries about Anthropic in a way that rings true to the people who work there - perhaps because I am wrong, or perhaps because they are very busy and very tired and do very little other than work, which creates conditions where it is hard for people to communicate, or learn, or change their minds, or reconstruct this flawed and mangled criticism into a form that would resonate like this one does not. But man, I think that the admirable sacrifices Anthropic has made in a few areas it really believes in (bio, China) do not reassure me it'll do the extremely hard work to get things right in a few other areas that it seems to have a lot more internal or leadership disagreement about (alignment, takeover, disempowerment). And so I don't expect things to go well.
Thank you for this, @_NathanCalvin. I appreciate and am a fan of the investigative work you’ve done on behalf of AI safety and believe your comments are coming from a constructive, honest place, and that it benefits the public to have people whose job is to scrutinize the actions of frontier AI companies. I think something would be wrong if companies of the size of Anthropic didn’t get harshly criticized basically every day; strong antibodies against corporate power are a healthy feature of a free society, and especially so when issues of the gravity of the one we’re facing are at play. I also do agree that some of the examples you cite were mistakes by Anthropic. That said, I disagree with the thrust of your post. At the core, a good fraction of the things you criticize are consequences of Anthropic’s basic theory of change that we have held for many years. Our strategy has always been what I’ve called the “race to the top” — by showing how it’s possible to build the technology responsibly, we can raise the bar for the entire industry. The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier; that’s one lesson I’ve learned repeatedly. And looking at that strategy as a whole, I’m proud of our track record and stand by it. I believe that if we take a list of things that Anthropic did in the past year that were pro-safety and commercially costly to us, they far outweigh the list you’ve made, while at the same time I also disagree with some of the items on your list. Here are some things Anthropic has done, in the same period you’ve cited (the last year), which were very costly to us commercially while having strong safety benefits: 1. We played a key role in SB53 (and other state laws), at a time when doing so was politically perilous to the company and AI regulation was very unpopular. We in fact argued for a stronger version of SB53 than was ultimately passed; there were a lot of stakeholders and we were not the limiting factor in the strength of the bill that was passed. 2. We have very strong biological safeguards on our models, because we’ve seen concerning results in bio uplift trials and even seen and blocked potential attempts to misuse our models for bioweapons (as seen in our threat intelligence report from a few weeks ago). This is a very serious threat that we want to have zero tolerance for. But having very low false negatives means having significant false positives (despite months of effort on our part to improve the classifiers), enough so that biologists joke about how restrictive our classifiers are, and competitors sometimes sell against us by touting their more permissive bio capabilities. This has been very painful to us in an area where we care a lot about supporting an ecosystem of Claude users (biomedical science; and it is particularly frustrating to me as a biologist), but it’s the right thing to do and we intend to keep doing it. 3. Similarly, we first had Mythos-class models in February but didn’t make them generally available until June (when we had stronger cyber safeguards in place). We only offered them to a limited set of partners in order to focus on cyberdefense. It would have been much more economically rational to simply release the model to everyone. We likely sacrificed a significant chunk of a several-month model lead. But because of this, many companies secured their cyber infrastructure before the deluge of widely available cyber-capable models. Of course there are ways it could have gone better or been run better, but this was what we were aiming to do. 4. I advocated forcefully and publicly, in my essay Policy on the AI Exponential in June of this year, for the government to have the power to block model releases. Back then this was still outside or maybe on the edge of the Overton window, though I understand the window has moved since then. We were attacked intensely for this. 5. I don’t want to re-ignite conflict, but the events of February 2026 are a strong example. It is clear that our public stance could have seriously damaged the company’s future. 6. We’ve continued to advocate for export controls on chips and chipmaking equipment to China, because we think it allows democracies to negotiate from a position of strength on AI safety agreements. We’ve done this despite problems it’s created for us with industry partners who hold very different views and on whom we are very dependent. 7. As far as I’m aware we were the first, and still only, frontier company to restrict the sale of AI services to PRC-controlled companies, including those operating through third countries (otherwise a major loophole). We’ve therefore forfeited significant short-term business to prevent fueling AI platforms and applications that would help the CCP’s military and intelligence services. We are also cracking down on distillation; generally, distillation is not a major threat to us commercially, but like chip exports it has concerning national security and safety implications, so we expend significant energy and company resources to address it. 8. As you mentioned, we’ve put out a lot of reports, announcements, long model cards, public advocacy, etc, all trying to inform the public about the risks of AI. These involve a level of detail and effort that would be implausible for a purely profit-maximizing company. 9. Just this week, we announced we were putting 5% (and possibly more over time) of the company into a public benefit fund. All of these decisions came with very substantial costs to us. To be fair, those that involved holding back or restricting access to frontier capabilities also had a broader cost — for example, the public might otherwise have benefitted from faster progress in biology, so I am not saying that our decisions were without tradeoffs — but they were not driven by profit-seeking. For each decision, you can come up with ulterior motives that could have driven us — I think it is a general truth that any decision, on any topic, can always be portrayed as a nefarious scheme. But most of those end up being pretty farfetched or don’t fully make sense if you actually examine them closely. For example, it is deeply implausible that it would be a shrewd business move to block a large swath of research biology in order to do the work ourselves and compete with our customers; we expect the benefit to the ecosystem to greatly exceed the work Anthropic does itself, and for the two to complement each other. It is not in Anthropic’s interest to be perceived as unfriendly to biologists. Our Life Sciences Verification Program, which gives vetted biology professionals access to our models, also refutes this idea. Of course, a different set of people will see this and make a different criticism: that Anthropic shouldn't be making decisions about who gets access to what in the first place. I agree, in the sense that ideally the government would be making these decisions, and that’s why we advocate for regulation. But for now we are forced to make them, and enabling bioterrorism isn’t a better option. I think that even if I conceded every item in your list, I would happily hold up mine next to it; I don’t think it’s a close call. That is of course partly subjective and different things are important to different people. Maybe one way you could object is that several of the items above relate to AI misuse and not loss-of-control; if you think the latter is much more important than the former, that might change your calculus. But this is not Anthropic’s view — we view both as serious issues. You can also disagree with our decisions, as many have, but they are consistent. But I also disagree with at least some of your list. Several items don’t represent a deviation from Anthropic’s strategy or values at all, once we postulate the “race to the top” strategy that requires being a frontier AI company. Your items 1-4 are all simply examples of what it means to compete at the frontier, and we stand by them, both in the sense that they are transparently ordinary things to do as part of that strategy, and that we stand by the strategy as a whole. To be fair, there are important questions worth confronting (and that we are confronting) about what to do when the AI-driven acceleration gets fast enough that it is hard for safety to keep up. We are nearing that point and that’s what’s driving some of our thinking about “pacing.” But 1-4 are actions taken before that point and should be perfectly expected based on Anthropic’s strategy as a company. Of course it is possible to disagree with that strategy, but that’s a more fundamental disagreement that you could have had any time over the last few years. I agree we could have handled your items 7, 8, and 9 better. All fall into the category of “rhetoric or policy communication that wasn’t carefully written or resulting from fast-changing circumstances not propagating from one team to another fast enough.” This kind of thing happens a lot in large organizations (Anthropic is over 5,000 people), and doesn’t even necessarily represent a failure or mistake of any single person. I am of course the CEO, and I take responsibility. The volume of communication from Anthropic is enormous and if these are the worst examples, I think we’re frankly doing pretty well, though I will continue to work hard to make sure we do even better. Your 5th item (the change to our RSP) is the most substantive item, and people can debate this, but I think that the old, more rigid RSP created a lot of situations where we were technically required to do something that required a lot of effort but in retrospect wasn’t very important for safety, as well as not covering some of the most important things. Our current RSP’s focus on transparency brought things like risk reports and roadmaps, and its emphasis on independent external review laid the groundwork for even more intensive embedded evaluation, all of which I think have been valuable in driving a race to the top. In the original announcement in September 2023, we described the RSP as an “early iteration that we [would] build on” and said that “rapid iteration…will almost certainly be necessary.” I understand that changing plans is always a move that creates justifiable scrutiny — I just don’t think we ever represented that we wouldn’t do so. Relating to your 6th item (having an FCF in addition to our RSP), I know our intent is to meet the letter and spirit of our regulatory obligations (via our FCF) while also remaining able to experiment with more novel approaches to risk management that go beyond what the law currently requires (via our RSP). I promise to look into it further, as it’s a complex issue and it is possible we are not weighing the considerations in the right way. Overall, although Anthropic has made plenty of mistakes as an organization — including some of the items on your list — I feel that we have repeatedly taken serious and substantive actions counter to our bottom line and that there is a significant negativity bias distorting assessments like the one you are making above. We’ll always try to do better but, again, I am extremely proud of our track record and stand by it. I will have more to say soon about how we are going to further live our values in this moment of rapid change.
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Gustavo Lacerda, surfing the Pareto frontier retweeted
voces n tem noçao do poder de convencimento de comparar o flavio com o collor pras pessoas mais velhas esse video ta causando panico na velharada da minha familia
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Gustavo Lacerda, surfing the Pareto frontier retweeted
This essay by @rufusknuppel is genuinely brilliant. I'll be reading everything he writes from here on out. thenewcritic.com/p/coxon-day
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