Quick takes

I sometimes say, in a provocative/hyperbolic sense, that the concept of "neglectedness" has been a disaster for EA. I do think the concept is significantly over-used (ironically, it's not neglected!), and people should just look directly at the importance and tractability of a cause at current margins. Maybe neglectedness useful as a heuristic for scanning thousands of potential cause areas. But ultimately, it's just a heuristic for tractability: how many resources are going towards something is evidence about whether additional resources are likely to be impactful at the margin, because more resources mean its more likely that the most cost-effective solutions have already been tried or implemented. But these resources are often deployed ineffectively, such that it's often easier to just directly assess the impact of resources at the margin than to do what the formal ITN framework suggests, which is to break this hard question into two hard ones: you have to assess something like the abstract overall solvability of a cause (namely, "percent of the problem solved for each percent increase in resources," as if this is likely to be a constant!) and the neglectedness of the cause. That brings me to another problem: assessing neglectedness might sound easier than abstract tractability, but how do you weigh up the resources in question, especially if many of them are going to inefficient solutions? I think EAs have indeed found lots of surprisingly neglected (and important, and tractable) sub-areas within extremely crowded overall fields when they've gone looking. Open Phil has an entire program area for scientific research, on which the world spends >$2 trillion, and that program has supported Nobel Prize-winning work on computational design of proteins. US politics is a frequently cited example of a non-neglected cause area, and yet EAs have been able to start or fund work in polling and message-testing that has outcompeted incumbent orgs by looking for the highest-v

As a community builder, I've started donating directly to my local EA group—and I encourage you to consider doing the same. Managing budgets and navigating inflexible grant applications consume valuable time and energy that could otherwise be spent directly fostering impactful community engagement. As someone deeply involved, I possess unique insights into what our group specifically needs, how to effectively meet those needs, and what actions are most conducive to achieving genuine impact. Of course, seeking funding from organizations like OpenPhil remains highly valuable—they've dedicated extensive thought to effective community building. Yet, don't underestimate the power and efficiency of utilizing your intimate knowledge of your group's immediate requirements. Your direct donations can streamline processes, empower quick responses to pressing needs, and ultimately enhance the impact of your local EA community.

I'm a 36 year old iOS Engineer/Software Engineer who switched to working on Image classification systems via Tensorflow a year ago. Last month I was made redundant with a fairly generous severance package and good buffer of savings to get me by while unemployed. The risky step I had long considered of quitting my non-impactful job was taken for me. I'm hoping to capitalize on my free time by determining what career path to take that best fits my goals. I'm pretty excited about it.  I created a weighted factor model to figure out what projects or learning to take on first. I welcome feedback on it. There's also a schedule tab for how I'm planning to spend my time this year and a template if anyone wishes to use this spreadsheet their selves. I got feedback from my 80K hour advisor to get involved in EA communities more often. I'm also want to learn more publicly be it via forums or by blogging. This somewhat unstructured dumping of my thoughts is a first step towards that.

I'd love to see an 'Animal Welfare vs. AI Safety/Governance Debate Week' happening on the Forum. The risks from AI cause has grown massively in importance in recent years, and has become a priority career choice for many in the community. At the same time, the Animal Welfare vs Global Health Debate Week demonstrated just how important and neglected the cause of animal welfare remains. I know several people (including myself) who are uncertain/torn about whether to pursue careers focused on reducing animal suffering or mitigating existential risks related to AI. It would help to have rich discussions comparing both causes's current priorities and bottlenecks, and a debate week would hopefully expose some useful crucial considerations.

I'm currently facing a career choice between a role working on AI safety directly and a role at 80,000 Hours. I don't want to go into the details too much publicly, but one really key component is how to think about the basic leverage argument in favour of 80k. This is the claim that's like: well, in fact I heard about the AIS job from 80k. If I ensure even two (additional) people hear about AIS jobs by working at 80k, isn't it possible going to 80k could be even better for AIS than doing the job could be? In that form, the argument is naive and implausible. But I don't think I know what the "sophisticated" argument that replaces it is. Here are some thoughts: * Working in AIS also promotes growth of AIS. It would be a mistake to only consider the second-order effects of a job when you're forced to by the lack of first-order effects. * OK, but focusing on org growth fulltime seems surely better for org growth than having it be a side effect of the main thing you're doing. * One way to think about this is to compare two strategies of improving talent at a target org, between "try to find people to move them into roles in the org, as part of cultivating a whole overall talent pipeline into the org and related orgs", and "put all of your fulltime effort into having a single person, i.e. you, do a job at the org". It seems pretty easy to imagine that the former would be a better strategy? * I think this is the same intuition that makes pyramid schemes seem appealing (something like: surely I can recruit at least 2 people into the scheme, and surely they can recruit more people, and surely the norm is actually that you recruit a tonne of people" and it's really only by looking at the mathematics of the population as a whole you can see that it can't possibly work, and that actually it's necessarily the case that most people in the scheme will recruit exactly zero people ever. * Maybe a pyramid scheme is the extreme of "what if literally everyone in EA work

AIxBio looks pretty bad and it would be great to see more people work on it * We're pretty close to having a country of virologists in a data center with AI models that can give detailed and accurate instructions for all steps of a biological attack — with recent reasoning models, we might have this already * These models have safeguards but they're trivial to overcome — Pliny the Liberator manages to jailbreak every new model within 24 hours and open sources the jailbreaks * Open source will continue to be just a few months behind the frontier given distillation and amplification, and these can be fine-tuned to remove safeguards in minutes for less than $50 * People say it's hard to actually execute the biology work, but I don't see any bottlenecks to bioweapon production that can't be done by a bio undergrad with limitless scientific knowledge; on my current understanding, the bottlenecks are not manual dexterity bottlenecks like playing a violin which require years of practice, they are knowledge bottlenecks * Bio supply chain controls that make it harder to get ingredients aren't working and aren't on track to work * So it seems like we're very close to democratizing (even bespoke) bioweapons. When I talk to bio experts about this they often reassure me that few people want to conduct a biological attack, but I haven't seen much analysis on this and it seems hard to be highly confident. While we gear up for a bioweapon democracy it seems that there are very few people working on worst-case bio, and most of the people working on it are working on access controls and evaluations. But I don't expect access controls to succeed, and I expect evaluations to mostly be useful for scaring politicians, due in part to the open source issue meaning we just can't give frontier models robust safeguards. The most likely thing to actually work is biodefense. I suspect that too many people working on GCR have moved into working on AI alignment and reliability issues and

Is anyone in EA coordinating a response to the PEPFAR pause? Seems like a very high priority thing for US-based EAs to do, and I'm keen to help if so and start something if not.

After following the Ukraine war closely for almost three years, I naturally also watch China's potential for military expansionism. Whereas past leaders of China talked about "forceful if necessary" reunification with Taiwan, Xi Jinping seems like a much more aggressive person, one who would actually do it―especially since the U.S. is frankly showing so much weakness in Ukraine. I know this isn't how EAs are used to thinking, but you have to start from the way dictators think. Xi, much like Putin, seems to idolize the excesses of his country's communist past, and is a conservative gambler: that is, he will take a gamble if the odds seem enough in his favor. Putin badly miscomputed his odds in Ukraine, but Russia's GDP and population were 1.843 trillion and 145 million, versus 17.8 trillion and 1.4 billion for China. At the same time, Taiwan is much less populous than Ukraine and its would-be defenders in the USA/EU/Japan are not as strong naval powers as China (yet would have to operate over a longer range). Last but not least, China is the factory of the world―if they should decide they want to do world domination military-style, they can probably do that fairly well while simultaneously selling us vital goods at suddenly-inflated prices. So when I hear China ramped up nuclear weapon production, I immediately think of it as a nod toward Taiwan. If we don't want an invasion of Taiwan, what do we do? Liberals have a habit of magical thinking in military matters, talking of diplomacy, complaining about U.S. "war mongers", and running protests with "No Nukes" signs. But the invasion of Taiwan has nothing to do with the U.S.; Xi simply *wants* Taiwan and has the power to take it. If he makes that decision, no words can stop him. So the Free World has no role to play here other than (1) to deter and (2) to optionally help out Taiwan if Xi invades anyway. Not all deterrents are military, of course; China and USA will surely do huge economic damage to each other if China