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Crossposted from Substack. This post is part of a 30-posts-in-30-days ordeal at Inkhaven. All suboptimalities are the result of that. This is part 2, here is part 1 in my EA mini series!
On my way to my tenth EAG in a decade, my brother-in-law explained effective altruism to me.
At first, he couldn’t quite remember if he’d heard the phrase before. But he searched the corners of his mind until the definition made itself known: “yeah, it's just a bunch of wankers who pretend to have social impact, but all they do is go to conferences and raise money and they’ve never had any impact at all.”
I have never had any chill. I did not develop it in that moment. If anyone is going to say EA is just a bunch of wankers, it's going to be me, newbie.
“That's interesting, Ben, but I think it's a serious misconception — you might not be aware that EA has literally raised billions of dollars for global health charities, which very likely saved hundreds of thousands of children's lives (do you hate children, Ben?) They have literally stopped millions of hens being tortured in cages too small for them [...]
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Two frameworks, one question: whose finances are we talking about, and to what end?
As the development sector gathers at the Skoll World Forum in Oxford this week, against a backdrop of sharp cuts to official development assistance — the US has ended 83% of USAID's programmes, the UK has cut its aid budget by 40%, and the OECD projects an overall ODA decline of 9–17% in 2025 alone, with projected consequences for millions of lives — two financial frameworks are converging in the sector's conversations.
The first is cost-effectiveness: IDinsight has launched a dedicated Cost-Effectiveness Unit and the FCDO's Best Buys evidence summaries are influencing billions in development spending. The second is the “cheap enough” framework developed by the Mulago Foundation, asking whether solutions are structured to scale through government financing rather than perpetual philanthropy. Both feel urgent right now. And together, they open a broader opportunity: to think more holistically about financial frameworks, not just how to maximise impact per dollar, but what among that which is highly cost-effective is also truly scalable and implementable.
These two frameworks are not in tension. They are sequential, and the sector needs both. But to use them well, it [...]
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Outline:
(02:40) Cost-Effectiveness: The Optimisation Tool
(04:45) Cheap Enough: The Scaling Reality Check
(06:47) Five Ways to Think About the Relationship
(07:00) 1. Cheap Enough ⊂ Cost-Effective -- Recommended Approach
(07:36) 2. Cost-Effective ⊂ Cheap Enough
(07:58) 3. Partial Overlap -- the sector default
(08:23) 4. Equivalent -- big-aid context only
(08:47) 5. Mutually Exclusive -- avoid
(09:10) Implications
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We're announcing a new development magazine: In Development.
Our goal is to promote discourse on development without dogma. In other words, we public stories doing deep dives into pressing development issues, backed up by evidence, argument, and experience.
The first piece is by Paul Niehaus, an Economics Professor at the University of California, San Diego, and co-founder of GiveDirectly.
He talks about the complementary role of evidence in the evolution of GiveDirectly, which has recently transferred its billionth dollar. Why did they need evidence? What kind of evidence did they need to convince themselves and others? What were the surprises? Whose preferences does such evidence reveal or promote? What role does ‘power’ play in the generation of such evidence?
We have one article out each week. The next one will have a line of argument that, mildly put, may not agree with today's piece.
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https://indevelopmentmag.com/money-for-nothing-the-roles-of-evidence-in-givedirectlys-journey-to-1-billion-delivered/
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Crosspost.
Picture a knife cutting into your stomach.
Don’t just register the words. Actually take a moment to think about what it would be like. What the first moment it occurred would be like, how the pain would get deeper as the knife cuts more deeply into your flesh, the way the blood would drip down your sides and you would cry out in pain. Intense agony has a way of cutting through idealizations and rationalizations—so that the world is on fire, alight with nothing but pain.
Andy Masley has an article called Animal Suffering Isn’t Pretend. It's easy to go through the world thinking it is pretend, implicitly if not explicitly. It's easy to think of animals as meek little animatronic robots who we shouldn’t be overly cruel to, but merit a somewhat second-class ethical status. They merit nice statements about compassion, rather than any kind of deep sympathy—of imagining things from their perspective. It is easy to go through life never thinking about what it's like to be an animal.
But animal suffering is not pretend. There is something it is like to be an animal going through the myriad horrors we inflict on them. To pick [...]
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This post was crossposted from Dylan Matthew's blog by the EA Forum team. The author may not see or reply to comments.
Subtitle: Try to keep an open mind as the world gets increasingly wild.
The crowd at EAG 2015 (Center for Effective Altruism)In 2015, I went to my first EA (Effective Altruism) Global. It was then on-the-record for journalists, which is a rule that got changed for all subsequent events due to my actions.
My exposure to EA at that time was mostly through people who took high-paying careers in order to “earn to give” to global health charities, which I had written about in the Washington Post. I also knew the movement cared a lot about animal welfare. I was aware that there were people worried about catastrophic risks, and specifically about AI; this had come up in a profile I wrote of Open Philanthropy (my now-employer, albeit under a new name these days). But I still broadly thought of EA as the bednets and cage-free commitments people.
I was really taken aback by how dominant discussions of AI risk were at the event. The marquee panel featured Superintelligence author Nick Bostrom, future If Anyone Builds It [...]
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Outline:
(03:31) What should I learn from bungling this?
(06:43) Listen to the people saying stuff will get weird
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I joined CEA as Director of EA Funds 3 months ago. I have two goals with this post:
For those less familiar, EA Funds channels individual donations to high-impact work through four cause-specific funds: the Animal Welfare Fund (AWF), the Long-Term Future Fund (LTFF), the Global Health and Development Fund (GHDF), and the EA Infrastructure Fund (EAIF). Since EA Funds (re-)became part of CEA in mid-2025, we've been building toward a model with full-time leadership for each fund, strong grantmaking processes, and the strategic clarity to make each fund a solid product for donors who want to do the most good with their giving.
The Animal Welfare Fund is our proof of concept. In just over a year of having full-time leadership, AWF developed a clear 3-year grantmaking strategy, grew from roughly $3M to $10M raised annually, and funded interventions improving welfare for billions of animals across dozens of countries [...]
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Outline:
(00:37) Where EA Funds stands
(03:48) The EA Infrastructure Fund
(06:54) The hire
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Summary
In January 2026, the animal charity Farmkind launched a controversial news campaign advertising their ability to “offset” the impact of non-vegan diets through strategic donations to EA causes. I have now spoken with several non-vegan EAs who use Farmkind (or similar calculators) to buy “offsets” for their diets, and I think the offsetting logic is more powerful than vegans would like to admit. However, I think EAs generally draw the wrong conclusions from this line of reasoning. Even (maybe especially) under hardcore consequentialism I believe there's a very strong case to be made against using “offsets” of any kind. As a vegan advocate now working in animal welfare policy, I feel strongly that the reluctance of many EAs to commit to veganism represents a major missed opportunity for the movement, and an objectively massive source of animal suffering.
How Offsets Work
By going vegan, you can reduce total market demand by something like ~200 animals (excluding shrimp) every year (1). However, due both to the astonishing number of animals killed for food every year and the immense tractability of targeted welfare reforms, going vegan is far from the most effective way to help animals. Farmkind estimates that donating [...]
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Sometimes, people don't say what they actually think, not because saying it would be rude or costly, but because they believe saying it now would be counterproductive. They see that the true claim is outside the Overton window. And they conclude that the strategic play is to say something weaker, something adjacent. That will let you normalize the frame without triggering the immune response. You will redesign the house a bit now so that you can slide the window later. Then, when the ground has shifted, you imagine, the real claim becomes sayable.
Strategic discourse chess?
The above is an attempt at high-dimensional discourse chess. In politics and the world of ideas, it seems that people play it constantly. But building on a recent comment by Rob Bensinger, I want to argue that the conceit behind playing, that we can model how public acceptability shifts and cleverly intervene to steer those shifts, is usually wrong - not in the sense that discourse has no structure, or to argue that framing never matters.
Most people vastly overestimate their ability to predict second- and third-order effects of anything, including strategic speech. And this is a more damaging error than you might [...]
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Outline:
(00:45) Strategic discourse chess?
(02:22) Yes, Overton windows exist, but...
(04:01) ...can they be reliably manipulated?
(05:59) Why would you think this could work?
(07:18) The case of AI Safety
(11:16) Pushing back is also manipulation.
(15:05) Another real-world example: Defund the Police
(17:45) Strategic discourse chess usually underperforms just saying what is true.
(19:59) The obvious conclusion
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Read this career review on the 80,000 Hours website.
Summary
In a nutshell: Who wields power in the US government is a very important determinant of outcomes for many of the world's most pressing problems, including reducing catastrophic risks from AI. The most direct ways to affect who controls the levers of government power are to work on campaigns and run for office. Because election outcomes are so important, and sufficiently tractable, we think electoral work is a great option for many people. However, it can be hard to make an impact in these roles, and the work has material downsides, like low pay and low job security.
Pros:
Cons:
Key facts on fit:
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Outline:
(00:15) Summary
(02:17) Two key paths to impact through electoral politics
(03:10) Why work in US electoral politics?
(03:15) Individuals really can make a difference
(05:01) Why should you run for office?
(07:40) Why should you work for a campaign?
(13:23) Elected leadership matters a great deal
(17:35) Lower-level offices shape higher-level outcomes.
(18:13) Politics is a good option if you expect transformative AI relatively soon.
(19:26) Downsides of working in electoral politics
(19:31) Downsides to running for office
(22:08) Downsides to working on campaigns
(24:20) Would you be a good fit for working in electoral politics?
(24:25) Skills that will help you succeed
(27:05) What experience is useful?
(28:41) What else is helpful?
(29:08) Top roles and where to work
(29:31) Common roles to look for
(29:56) Key places to work
(31:03) Next steps
(32:25) Read next
(32:42) Learn more
(33:08) Acknowledgements
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Based on the last 3 years of AI safety job board postings from 80, 000 Hours, I checked what skillsets are the most sought after in the field, including positions at different types of organisations, and separately, leadership roles. Here are three of the most important findings:
You can find more conclusions at the end of the post.
I believe this analysis may help draw some important conclusions for two main groups: job-seekers and fieldbuilders, in particular those working on improving talent flows and attracting new talent to high-impact positions in AI safety.
IntroductionWhen I joined the Astra Fellowship as a Fieldbuilding Fellow in January, it seemed obvious to me that there must be a lot of knowledge in the field about what we need from AI safety talent pipelines. After all, there are [...]
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Outline:
(00:13) Summary
(01:21) Introduction
(03:05) Skillsets
(06:12) Skillset needs by type of organisation
(06:46) Academia
(07:23) Public Institutions
(09:35) AI labs
(11:16) Non-governmental organisations
(11:56) Leadership roles
(14:00) Limitations
(15:32) Conclusions and implications
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From the publisher's feed