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The Board of Effective Altruism UK is pleased to announce the appointment of a new Director, Gergő Gáspár.
EA UK works to support and strengthen the effective altruism community across the UK, helping people increase their impact. Gergő joins EA UK at a time when there is growing demand for strong infrastructure to support the UK EA ecosystem.
BackgroundGergő's academic background is in psychology, and he has been working in community building and fieldbuilding roles since 2019. He began by organising a university group called EA ELTE, which later grew into EA Budapest and eventually into EA Hungary, a national group. He moved into full-time community building work in 2021 as this work scaled. In 2022, he founded AI Safety Hungary.
For the past two years, Gergő has also been a part-time Director at the European Network for AI Safety (ENAIS), working on coordination and capacity-building across Europe. In parallel, he co-founded Amplify, an EA-aligned digital marketing agency focused on supporting fieldbuilding organisations. He also writes the blog Building Capacity, which focuses on fieldbuilding strategy, careers, and marketing in EA and adjacent spaces.
Earlier in his career, Gergő was a volunteer charity analyst and analysis coordinator at SoGive [...]
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Outline:
(00:34) Background
(01:44) Focus at EA UK
(02:02) A note from Gergő
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For the last couple of years, EA Organization Updates has been a monthly series hosted on the forum. It doesn't normally get very much attention. Previous to that it was part of the EA Newsletter until the newsletter got far too long to host it.
Now we're trying something new. Instead of asking organisations to write in to us, editing and posting their updates, we're asking them to write directly here on the forum, where you can interact with them. If this goes well, we'll continue the series as a monthly thread which stays up for a week.
Note that this thread will be less gate-kept, curated and endorsed than the previous series. This is a positive (content isn't restricted to the organisations we have asked to write something) and negative (if the thread proves popular, we might have to spend moderation capacity removing irrelevant updates). We'll keep an eye on this trade-off.
You can see previous updates on the “EA Organization Updates (monthly series) topic page. Notice that there's also an “organization updates” tag, where you can find more news and updates that are not part of this consolidated series.
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If someone I manage sends me a 10-page document to review, then it might take me 20-60 minutes to review. It's therefore a somewhat meaty task, that would be easy to delay.
But before doing the full review, I think it's good to spend 2-5 minutes giving high-level comments, as soon as possible.
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https://newsletter.samepagemanagement.org/p/unblock-quickly
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I'm Dom Jackman. I founded Escape the City in 2010 to help people leave corporate jobs and find work that matters. 16 years later, 500k+ professionals have used the platform - mostly people 5-15 years into careers at places like McKinsey, Deloitte, Google, the big banks - who feel a growing gap between what they do all day and what they actually care about.
I'm not from the EA community. I'm writing this because I think there's a real overlap between the people I work with and what the EA talent ecosystem actually needs. I want to test that before investing serious time in it.
What I've noticed
Reading through talent discussions on this forum, there's a consistent theme: the pipeline is strongest for early-career people. 80,000 Hours does great work for students and recent grads. Probably Good provides broad guidance. BlueDot, MATS, Talos build skills for specific cause areas.
But mid-career professionals with real commercial experience keep coming up as underserved. The "Gaps and opportunities in the EA talent & recruiting landscape" post nails it: these people "don't have 'EA capital,' may be poorly networked and might feel alienated by current messaging." The post calls for "custom entry [...]
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Outline:
(00:51) What Ive noticed
(01:40) What I see every day
(02:28) What Im thinking about building
(03:24) Honest questions
(04:39) Not looking for funding
(04:58) Artifacts
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By Robert Wilbin | Watch on Youtube | Listen on Spotify | Read transcript
In early 2025, after OpenAI put out the first-ever reasoning models — o1 and o3 — short timelines to transformative artificial general intelligence swept the AI world. But then, in the second half of 2025, sentiment swung all the way back in the other direction, with people's forecasts for when AI might really shake up the world blowing out even further than they had been before reasoning models came along.
What the hell happened? Was it just swings in vibes and mood? Confusion? A series of fundamentally unexpected and unpredictable research results?
Host Rob Wiblin has been trying to make sense of it for himself, and here's the best explanation he's come up with so far.
This episode was recorded on January 29, 2026.
Video and audio editing: Dominic Armstrong, Milo McGuire, Luke Monsour, and Simon Monsour
Music: CORBIT
Camera operator: Dominic Armstrong
Coordination, transcripts, and web: Katy Moore
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Project for Awesome (P4A) is a charity video contest running from February 10th to February 18th, 2026. The public can vote on videos supporting various charities, and the ones with the most votes receive donations. Thanks to the support of the EA community, several EA charities won substantial donations in recent year. Last year, ProVeg International received more than $38,000.
Please help generate additional donations for EA charities again this year with just a few clicks! Voting is open until Wednesday, February 18th at 11:59 AM EST. You can find more information about P4A in this EA Forum post.
On the P4A website, there are numerous videos showcasing different charities, including several EA charities. Feel free to watch the videos and cast your votes.
Here's how it works:
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Outline:
(01:59) List of videos about EA charities
(02:09) Against Malaria Foundation (Vote here )
(02:14) Allied Scholars for Animal Protection (Vote here )
(02:19) Animal Welfare Observatory (Vote here )
(02:23) Centre for Governance of AI (Vote here )
(02:28) Ethical Seafood Research (Vote here )
(02:32) FarmKind (Vote here )
(02:36) Faunalytics (Vote here )
(02:40) GiveDirectly (Vote here )
(02:44) Giving Green (Vote here )
(02:48) Good Food Fund (Vote here )
(02:52) Good Food Institute (Vote here )
(02:56) International Campaign to Abolish Nuclear Weapons (Vote here )
(03:02) International Centre for Animal Rights and Ethics (Vote here )
(03:08) Lafiya (Vote here )
(03:11) Machine Intelligence Research Institute (Vote here )
(03:17) New Roots Institute (Vote here )
(03:21) ProVeg International (Vote here )
(03:25) Sinergia Animal (Vote here or here )
(03:30) Spiro (Vote here )
(03:34) The Humane League (Vote here )
(03:38) Veganuary (Vote here or here )
(03:42) Wild Animal Initiative (Vote here )
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TL;DR
In 2025, we grew engagement with CEA's programs by 20–25% across every tier of engagement, reversing two years of moderate declines in engagement. We did so without substantially increasing costs or lowering the quality or bar for our programs.
This post reviews CEA's work on growing the EA community, which is only one of our strategic goals. See more on our other strategic goals here. We plan to accelerate our growth even further, and we're hiring across multiple teams to make that happen. Join us!
Summary
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Outline:
(00:17) TL;DR
(00:57) Summary
(05:08) Why grow?
(07:10) 2025. review
(08:04) Our growth model and 2025 targets
(08:45) Our results
(09:18) Tier 2: Exploring EA
(11:02) Tier 3: Actively Involved with EA
(12:34) Tier 4: Committing to Impact
(14:21) Tier 5: Actualizing Impact
(17:17) Changes in our spending
(19:05) Maintaining the quality of our programs while we scale
(20:42) 2026. plans
(22:06) What does this all mean?
(24:16) Acknowledgements
(24:51) Join us
(25:04) Appendices
(25:07) Our model and targets
(25:11) Building the model
(27:25) Setting the goals
(29:38) Changes in our spending
(33:31) G.R.O.W. principles
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I would like to thank David Thorstadt for looking over this. If you spot a factual error in this article please message me. The code used to generate the graphs in the article is available to view here.
Introduction
Say you are an organiser, tasked with achieving the best result on some metric, such as “trash picked up”, “GDP per capita”, or “lives saved by an effective charity”. There are several possible options of interventions you can take to try and achieve this. How do you choose between them?
The obvious thing to do is look at each intervention in turn and make your best, unbiased estimate of how each intervention will perform on your metric, and pick the one that performs the best:
Image taken from hereHaving done this ranking, you declare the top ranking program to be the best intervention and invest in it, expecting that that your top estimate will be the result that you get. This whole procedure is totally normal, and people all around the world, including people in the effective altruist community, do it all the time.
In actuality, this procedure is not correct. The optimisers curse is [...]
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Outline:
(00:26) Introduction
(02:17) The optimisers curse explained simply
(04:42) Introducing a toy model
(08:45) Introducing speculative interventions
(12:15) A simple bayesian correction
(18:47) Obstacles to simple optimizer curse solutions.
(22:08) How Givewell has reacted to the optimiser curse
(25:18) Conclusion
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Linkpost URL:
https://open.substack.com/pub/titotal/p/the-best-cause-will-disappoint-you?r=1e0is3&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
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Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
This is an update to Agent Economics: a BOTEC on feasibility. Toby Ord pointed me to Gus Hamilton's Weibull reanalysis of the METR data. Hamilton finds that a declining hazard rate (Weibull with κ ≈ 0.6–0.9 for SOTA models) may fit the data as well as Ord's constant hazard rate, producing a much fatter survival tail that changes the economics. This post presents both models and extends the analysis in two directions: a quantitative treatment of verification cost as the binding constraint under the Weibull model, and a systematic examination of the economic conditions under which a genuinely dangerous autonomous agent could actually operate. His full comment is in the Appendix.
Summary. The original post modelled agent cost per successful outcome scaling exponentially with task length under Ord's constant hazard rate, while human cost scales linearly. This update incorporates Hamilton's Weibull alternative, under which agent costs scale as a stretched exponential rather than a pure exponential. The cost wall is gentler, but it is still a wall. The dominant parameter remains the agent's reliability horizon (T₅₀). The available data does not yet show the shape of the reliability decay (κ) improving with model scale, though the sample is small [...]
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Outline:
(05:04) The setup
(06:58) The model
(09:09) Results: base case under both models
(10:54) Three key findings
(10:58) Finding 1: cost reductions cannot beat the superlinear growth
(12:18) Finding 2: the half-life is the whole game, and κ is the hidden variable
(16:06) Finding 3: verification cost is the binding constraint
(19:11) The case that κ is an architectural property
(19:34) The empirical evidence
(20:44) The theoretical argument
(23:40) What this means
(24:15) The timeline at κ = 0.70: five years of autonomous agent economics
(24:39) The T₅₀ trajectory
(25:11) The viability map over time
(26:29) Milestone 1: One-week bounded tasks viable for companies (April 2027, ~14 months away)
(27:05) Milestone 2: Two-week bounded tasks viable (November 2027, ~21 months away)
(27:42) Milestone 3: Self-sustaining agent-verifier pair can attempt to bootstrap (late 2027 onwards)
(30:33) Milestone 4: Month-long autonomous plans become non-trivially reliable (mid 2027 to early 2029)
(31:42) Milestone 5: State actor parallel-agent capability (already emerging, scales with T₅₀)
(33:07) Milestone summary at κ = 0.70
(33:28) The central question: can an autonomous ASI agent emerge?
(33:54) Condition 1: sufficient task complexity
(35:03) Condition 2: sufficient autonomy
(38:28) Condition 3: the human-in-the-loop and its fragility
(41:48) Condition 4: operating beyond intended scope
(42:03) 4a: Deceptive alignment
(43:05) 4b: The self-sustaining agent
(46:33) 4c: Reckless deployment
(48:26) How κ changes everything
(50:41) What this means for the investment thesis
(53:21) What happens if the bubble bursts?
(53:25) What happens if the bubble bursts?
(53:59) The telecom parallel
(57:39) When might the correction hit?
(01:06:14) The T₅₀ growth rate is the variable that matters
(01:07:50) Inference cost: the telecom asymmetry
(01:10:10) The self-sustaining pair is nearly unkillable
(01:11:59) The paradox
(01:16:13) The bust and the κ breakthrough
(01:17:58) Conclusion
(01:21:57) Caveats and limitations
(01:26:53) Appendix A: Can a coalition of pairs overcome the κ ceiling?
(01:31:24) Appendix B: Ords comment
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TL;DR:
Job titles are temporary. Movements last longer to achieve a common goal. When we anchor our identity in the mission rather than a single organisation, we collaborate more openly, make better decisions, and move faster toward ending factory farming. That's why I think we should have a movement role in addition to our current organizational role.
Acknowledgements: thanks to Aaron Boddy and Haven King-Nobles for your feedback on this post!
Introduction
Many people in nonprofits anchor their identity to their job title.
“Comms lead.”
“Policy manager.”
“Executive Director.”
But job titles are temporary.
Movements are not.
A job role is what you are accountable for inside a specific organisation.
A movement role is the kind of value you create for the cause over time, across roles and organisations.
Your movement role should guide your decisions.
Your job role should be one expression of it, for now.
This connects with ideas of ecosystem thinking: the belief that movements strengthen when organisations share insights and support one another.
This is not about disloyalty
Thinking in movement terms does not mean doing your job badly, caring less, or being half-committed.
You still owe your organisation competence, follow-through [...]
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Outline:
(00:43) Introduction
(01:28) This is not about disloyalty
(02:37) How this already shows up in the movement
(05:00) What this mindset changes
(06:23) How to choose a movement role
(08:22) A practical prompt
(08:54) I'd love to hear from you:
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Linkpost URL:
https://open.substack.com/pub/notingthemargin/p/dont-just-have-a-job-role-have-a
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