This is a special post for quick takes by Yadav. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.
Curated and popular this week
·
Advanced AI could unlock an era of enlightened and competent government action. But without smart, active investment, we’ll squander that opportunity and barrel blindly into danger.
Executive summary
See also a summary on Twitter / X.
The US federal government is falling behind the private sector on AI adoption. As AI improves, a growing gap would leave the government unable to effectively respond to AI-driven existential challenges and threaten the legitimacy of its democratic institutions.
A dual imperative
→ Government adoption of AI can’t wait. Making steady progress is critical to:
* Boost the government’s capacity to effectively respond to AI-driven existential challenges
* Help democratic oversight keep up with the technological power of other groups
* Defuse the risk of rushed AI adoption in a crisis
→ But hasty AI adoption could backfire. Without care, integration of AI could:
* Be exploited, subverting independent government action
* Lead to unsafe deployment of AI systems
* Accelerate arms races or compress safety research timelines
Summary of the recommendations
1. Work with the US federal government to help it effectively adopt AI
Simplistic “pro-security” or “pro-speed” attitudes miss the point. Both are important — and many interventions would help with both. We should:
* Invest in win-win measures that both facilitate adoption and reduce the risks involved, e.g.:
* Build technical expertise within government (invest in AI and technical talent, ensure NIST is well resourced)
* Streamline procurement processes for AI products and related tech (like cloud services)
* Modernize the government’s digital infrastructure and data management practices
* Prioritize high-leverage interventions that have strong adoption-boosting benefits with minor security costs or vice versa, e.g.:
* On the security side: investing in cyber security, pre-deployment testing of AI in high-stakes areas, and advancing research on mitigating the ris
·
In our recent strategy retreat, the GWWC Leadership Team recognised that by spreading our limited resources across too many projects, we are unable to deliver the level of excellence and impact that our mission demands.
True to our value of being mission accountable, we've therefore made the difficult but necessary decision to discontinue a total of 10 initiatives. By focusing our energy on fewer, more strategically aligned initiatives, we think we’ll be more likely to ultimately achieve our Big Hairy Audacious Goal of 1 million pledgers donating $3B USD to high-impact charities annually. (See our 2025 strategy.)
We’d like to be transparent about the choices we made, both to hold ourselves accountable and so other organisations can take the gaps we leave into account when planning their work. As such, this post aims to:
* Inform the broader EA community about changes to projects & highlight opportunities to carry these projects forward
* Provide timelines for project transitions
* Explain our rationale for discontinuing certain initiatives
What’s changing
We've identified 10 initiatives[1] to wind down or transition. These are:
* GWWC Canada
* Effective Altruism Australia funding partnership
* GWWC Groups
* Giving Games
* Charity Elections
* Effective Giving Meta evaluation and grantmaking
* The Donor Lottery
* Translations
* Hosted Funds
* New licensing of the GWWC brand
Each of these is detailed in the sections below, with timelines and transition plans where applicable.
How this is relevant to you
We still believe in the impact potential of many of these projects. Our decision doesn’t necessarily reflect their lack of value, but rather our need to focus at this juncture of GWWC's development.
Thus, we are actively looking for organisations and individuals interested in taking on some of these projects. If that’s you, please do reach out: see each project's section for specific contact details.
Thank you for your continued support as we
·
Our Mission: To build a multidisciplinary field around using technology—especially AI—to improve the lives of nonhumans now and in the future.
Overview
Background
This hybrid conference had nearly 550 participants and took place March 1-2, 2025 at UC Berkeley. It was organized by AI for Animals for $74k by volunteer core organizers Constance Li, Sankalpa Ghose, and Santeri Tani.
This conference has evolved since 2023:
* The 1st conference mainly consisted of philosophers and was a single track lecture/panel.
* The 2nd conference put all lectures on one day and followed it with 2 days of interactive unconference sessions happening in parallel and a week of in-person co-working.
* This 3rd conference had a week of related satellite events, free shared accommodations for 50+ attendees, 2 days of parallel lectures/panels/unconferences, 80 unique sessions, of which 32 are available on Youtube, Swapcard to enable 1:1 connections, and a Slack community to continue conversations year round.
We have been quickly expanding this conference in order to prepare those that are working toward the reduction of nonhuman suffering to adapt to the drastic and rapid changes that AI will bring.
Luckily, it seems like it has been working!
This year, many animal advocacy organizations attended (mostly smaller and younger ones) as well as newly formed groups focused on digital minds and funders who spanned both of these spaces. We also had more diversity of speakers and attendees which included economists, AI researchers, investors, tech companies, journalists, animal welfare researchers, and more. This was done through strategic targeted outreach and a bigger team of volunteers.
Outcomes
On our feedback survey, which had 85 total responses (mainly from in-person attendees), people reported an average of 7 new connections (defined as someone they would feel comfortable reaching out to for a favor like reviewing a blog post) and of those new connections, an average of 3
I've been meaning to write about what it's like trying to figure out your career direction between 18 and 21 while being part of the EA community—a time that feels, at least for me, like the most uncertain and exploratory part of life. You're not just asking yourself what you want to do, but also grappling with questions about impact and doing the most good, which adds another hard layer to an already complex period.
For anyone at university who's getting introduced to EA and feeling overwhelmed about career decisions, I feel like I want to share some thoughts. I've been there—feeling unsure about whether I was making the "right" choices or if I was doing enough to have impact. I've seen others around that age wrestle with the same questions. I still wrestle with my impact. You have my empathy.
If that's where you are right now, maybe a few scattered pieces of advice from someone a little further down the road could help. I won't turn this into a long essay, but if any of this resonates—or if you want more specific guidance—I'd be happy to expand on these thoughts:
1. 80,000 Hours is not gospel: Of course, they don't claim to be gospel, and explicitly want you to explore different options in your career and provide tools for you to do the thinking. But it's very easy to just default to their listed career options and cause areas. 80,000 Hours won't help you make the right choices if you aren't willing to accept that it's just one piece of your career puzzle. Most people don't just end up working on what they want by default, unfortunately.
2. Think beyond conventional impact paths: On that note, if something doesn't fit neatly into how a typical EA career pans out, that might feel uncomfortable. But that's okay—outside this community, people do all sorts of things in the world. Going to university doesn't automatically prepare you for AI policy work or give you operations skills. You'll probably need to get experience in the outside world that isn't an EA career path, and that can be hard if all you've consumed at university is EA philosophy and its traditional career paths. This is why not pigeon-holing yourself is a good idea (see point 4).
3. Get ready for ego hits: Yes, there's plenty written about how EA jobs are hard to get, but lots of jobs that seem shiny and potentially useful for career capital will reject you—because you're not the only one who wants that shiny job. You might get lucky and end up right where you want to be, but you're probably just like everybody else: inexperienced and trying to make it in the world. Each job application can take weeks of effort. You can make it to interview rounds, all excited about the possibility of doing something you want, only to be rejected because someone else has 10 years more experience than you. This will happen, and it will be hard. You just have to get back up and try again. I found it useful to remind myself every time I got rejected that 'they can reject me, but they can't kill my spirit'—and that helped muster up the motivation to push forward.
4. Don't let EA become your whole life: I switched my degree to be very AI Governance focused (which maybe is paying off), made EA friends, went to EA retreats. It's so enticing because the university EA community tends to be interesting, thoughtful, and ambitious—that's pleasant to be around and can mean your life gets wrapped up in it. Getting invited to EA Global conferences in the Bay Area when you're a twenty-year-old at university hits that status-seeking part of your brain hard. People think it's really cool, and it feels good when they do. I wish I could say I was above caring what others think, but my brain (like most people's) is wired to chase social validation at times. While there's plenty of advice out there about letting go of status-seeking—and you should definitely work on that—I think it's important to acknowledge how these dynamics can pull you deeper into making EA your whole identity. I strongly suggest building yourself in other communities and finding interests outside the movement. This advice might seem obvious to any adult, but when you're at university finding your people, and those people happen to offer both intellectual stimulation and status boosts, it's really easy to stick to the comfortable option.
5. Don't dismiss grades—they're part of the bigger picture: I absorbed some wrong advice about grades not mattering through the rationality community. But they do matter: not just for masters applications, but as a signal to employers about your ability to work hard and follow through. Even if EA jobs don't always list grade requirements, having good grades demonstrates competence and work ethic. More importantly, engaging deeply with your subject teaches you how to tackle difficult problems and work systematically—skills that matter regardless of where you end up. And actually trying with your degree and doing well can make university a much more pleasant experience.
Hope that's useful to somebody.
Thank you for writing this! I wish I had internalized some of these points more while I was at university, and guess others will feel the same.
One thing in particular that I recognized is viewing 80,000 Hours (and the EA community more broadly) as offering definitive answers, rather than tools and questions. Looking back, I realize I maybe fell into that mindset. I almost expected that if I just followed the "right" path they laid out and worked as hard as I could, I’d maximize my impact. That was, of course, a very soothing thought, drastically simplifying the complexity of my career choice. But it was also very wrong, and I'm grateful that this quick take is now there to point this out :)
I run frequently, and it would be nice to eventually see more GiveWell-recommended charities represented at marathon events in the UK. For example, I didn't get a place through the ballot for the London Marathon, but I could still obtain a charity place. However, I don't find any of the available charities particularly appealing to fundraise for, and I wish orgs like the Against Malaria Foundation were offered instead.
The value to the charity consists of both the funds counterfactually raised through the race and the value of the fundraising leads generated through the runner's activity. I'm curious about what BOTEC someone who knows more about the marathon-fundraising model than I might come up with. My off-the-cuff guess is that, to make the effort cost-effective enough, the charity would need a critical mass of runners who were (a) sufficiently invested in the charity to appear credible to their networks (vs. using it more as a way to gain entry) and (b) could tap wealthy-enough fundraising networks to generate significant post-race expected value.
I am now trying to make YouTube videos explaining AI Governance. Here is a video on RSPs. The video has a few problems, and the editing is sometimes choppy. This can be a fun hobby, and I could improve on skills that seem useful to have. The first is having the confidence to talk to a camera. If you have feedback, here is a form.
For a first video, I thought it was surprisingly good! :) I appreciate that you speak clearly, the script is pretty short and to the point, and honestly I thought the editing was way better than most of YouTube (you cut enough to keep it moving, but not too much as to be being annoying or distracting). There were a couple times I felt like you could have edited it down more. I liked the infographic cut-ins, and you could probably add slightly more visual aids before it gets to be too many.
I'm glad you enjoy making them, and I encourage you to keep doing it!
(I am mostly articulating feelings here. I am unsure about what I think should change).
I am somewhat disappointed with the way Manifund has turned out. This isn't to critique the manifund team or that regranting as an idea is bad, but after a few months of excitement and momentum, things have somewhat decelerated. While you get the occasional cool projects, most of the projects on the website don't seem particularly impressive to me. I also feel like some of the regrantors seem slow to move money, but it could be that the previous problem is feeding into this.
Suggestion: Enlarge the font size for pronouns on EA Global/EA retreat name cards
There was a period when I used they/them pronouns and was frequently misgendered at EA events. This likely occurred because I present as male, but regardless, it was a frustrating experience. I often find it difficult to correct people and explicitly mention my preferred pronouns, especially in socially taxing environments like EAGs or retreats. Increasing the size of the pronouns on name cards could be helpful.
I'd like to get opinions on something. I'm planning to experiment with making YouTube videos on AI Governance over the next month or two. Ideally, I want people to see these videos so I can get feedback or get told that I've said something incorrect, which is helpful for correcting my own model around things.
I'd share these videos by posting on the EA Forum, but I'm unsure about the best approach:
a) Posting on the frontpage feels like seeking attention or promoting for views, especially since I'm new to video-making and don't expect high quality initially.
b) Posting as personal blog posts seems less intrusive, as only those who opt to see personal posts will see them. This feels like I have "permission" to make noise and is less intimidating.
C) Putting them in my quick takes section, which is currently my default, would be even more out of the way.
Given my account's karma, my posts typically start with 4 or 5 karma and stay on the frontpage for a few hours by default. I think the forum has improved a lot recently - there's less volume of posts and more interesting discussions. I don't want to create noise each time I make a video.
However, each video is relevant to the EA community. If people don't like a video, it'll naturally move off the front page fairly soon. I'm more likely to get views if I don't make it a personal blog post or update my quick takes. These views are important to me because they mean more interesting feedback and a higher likelihood that I'll improve at making videos. (Also given I am only human, more views and engagement means more motivation to keep making things).
I'd appreciate others' opinions on this. I recognise that part of my hesitation probably stems from a lack of confidence and fear of others' opinions, but I don't think these are necessarily good justifications for my decision.
If it were me, I would default to posting them as quick takes. I think that would get them more visibility than a personal blog post (not sure), and quick takes are a good fit for asking for feedback on more early stage things.
But I am somewhat biased because I'm pretty scared to publish frontpage posts, and I don't want to discourage you from posting it there, especially if you are willing to put in some additional effort to make it valuable for frontpage readers (such as by including a written version of the contents, or by asking for specific feedback in the post, or framing your post as a discussion about the video topic that people can continue in the comments). As you say, in the worst case, if it doesn't get many upvotes, it will fall off pretty quickly.
On another note, I think the Forum isn't currently that well-suited for sharing video content, so if you have suggestions for how we can do better there, let me know! :)
I wonder if anyone has examined the pros and cons of protesting against AI labs? I have seen a lot of people uncertain about this. It may be useful to have someone have a post up, having done maybe <10 hours of thinking on this.
I'm doing some thinking on the prospects for international cooperation on AI safety, particularly potential agreements to slow down risky AI progress like CHARTS. Does anyone know of a good website or resource that summarizes different countries' current views and policies regarding deliberately slowing AI progress? For example, something laying out which governments seem open to restrictive policies or agreements to constrain the development of advanced AI (like the EU?) versus which ones want to charge full steam ahead, no matter the risks. Or which countries seem undecided or could be persuaded. Basically, I'm looking for something that synthesizes various countries' attitudes and stated priorities when it comes to potentially regulating the pace of AI advancement, especially policies that could slow the race to AGI. Let me know if you have any suggestions!
Not exactly what you're looking for (because it focuses on the US and China rather than giving an overview of lots of countries), but you might find "Prospects for AI safety agreements between countries" useful if you haven't already read it, particularly the section on CHARTS.