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In January, I wrote about the EA Forum Team's shift in direction. Since then, our usage metrics have been pretty stable, nice! 😊 (Compare to 2024 where the metrics were going steadily downward the whole year.)
When I wrote that post, my role was focused on the EA Forum, and I had intended to spend the majority of my effort on the EA Forum. However, my role and my team are in flux right now, primarily in order to better align with CEA's strategy. I’m currently running the CEA Online Team, and so far in 2025 we've broadly been spending a smaller portion of our resources on the EA Forum over time[1]. I think we need to be careful, because I still believe strongly in what I wrote in my previous post, and I have a worry that reducing the resources we spend on the EA Forum does risk [...]
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Outline:
(01:40) Site improvements
(01:44) Updated notifications
(02:16) Draft comments
(03:00) Users can run their own polls
(03:24) Tweaks to voting
(04:00) Redesigned user menu
(04:32) New Made me laugh react
(05:12) Forum events
(05:15) Forum events calendar
(05:26) Ways the world is getting better
(06:02) Draft Amnesty Week
(06:32) Existential choices debate week
(07:12) DIY debate week
(07:31) Team updates
(07:58) Other updates
(09:07) Want to help the EA Forum?
(10:28) Share your feedback
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To recap, first, we face an epistemic challenge beyond uncertainty over possible futures. Due to unawareness, we can’t conceive of many relevant futures in the first place, which makes the standard EV framework ill-suited for impartial altruistic decision-making. And second, we can’t trust that our intuitive comparisons of strategies’ overall consequences price in factors we’re unaware of with enough precision. We’ll need to evaluate these consequences with a framework that explicitly accounts for unawareness, that is, unawareness-inclusive expected value (UEV).
Here, I’ll more specifically unpack the UEV model, and argue that we can’t compare the UEV of any given strategy with another. If so, we don’t have a reason to choose one strategy over another based purely on [...]
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Outline:
(01:33) Unawareness-inclusive expected value (UEV)
(05:46) Comparing strategies under the UEV model
(07:48) Reasons to suspend judgment on comparisons of strategies' UEV
(09:18) Problem 1: Modeling the catch-all, and biased sampling
(14:18) Problem 2: Severe underspecification of coarse hypotheses
(17:33) Case study revisited: Sign indeterminacy of AI safety interventions due to unawareness
(18:20) What we're missing: Outcome robustness and implementation robustness
(20:45) The problem in detail
(26:59) Appendix B: Formalism for unawareness-inclusive expected value
(28:42) Appendix C: Incomparability and positive interventions
(33:29) References
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TL;DR
The main thing I expect busy people want when receiving an EAG cold message is:
My recommended message structure:
This advice is for messaging busy people, who will get more requests than they have time for, and need to prioritise, for less established people you can be way more chill.
I’m writing this because I think cold emails can be really valuable, and I hope this gives you the confidence to reach [...]
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Outline:
(00:12) TL;DR
(01:18) Introduction
(01:57) What should the message convey?
(02:40) Should you send a cold message?
(03:47) Recommended Message Structure
(07:26) Stylised Examples
(07:30) Example 1
(08:18) Example 2
(09:14) Final note
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I think it's easy to get disenchanted when writing posts or comments on blogs. I've particularly noticed this for the EA Forum and LessWrong.
Engagement can be highly random, and often rewards behaviors not correlated with quality. For example, posts like "10 more reasons to dislike Sam Altman" will often do a lot better than "My theoretical exploration of a new idea regarding AI policy"[1]
It's incredibly easy to have excellent work be completely ignored. I've experienced extreme frustration of this from some of my own posts, and have seen a lot of anger by others who feel unappreciated. I know many strong thinkers who quickly give up on writing anywhere.
But while it's tough to stand out in these crowds, I think it's also true that even a low-percentile post can have more value than many other things one can do with [...]
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https://ozziegooen.substack.com/p/a-defense-of-mid-tier-ealw-writing
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Crosspost from my blog.
Content warning: this article will discuss extreme agony. This is deliberate; I think it's important to get a glimpse of the horror that fills the world and that you can do something about. I think this is one of my most important articles so I’d really appreciate if you could share and restack it!
The world is filled with extreme agony. We go through our daily life mostly ignoring its unfathomably shocking dreadfulness because if we didn’t, we could barely focus on anything else. But those going through it cannot ignore it.
Imagine that you were placed in a pot of water that was slowly brought to a boil until it boiled you to death. Take a moment to really imagine the scenario as fully as you can. Don’t just acknowledge at an intellectual level that it would be bad—really seriously think about just [...]
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(This sequence assumes basic familiarity with longtermist cause prioritization concepts, though the issues I raise also apply to non-longtermist interventions.)
Are EA interventions net-positive from an impartial perspective — one that gives moral weight to all consequences, no matter how distant? What if they’re neither positive, nor negative, nor neutral?
Trying to reduce x-risk, improve institutions, or end factory farming might seem robustly positive. After all, we don’t need to be certain in order to do good in expectation. But when we step back to look at how radically far-reaching the impartial perspective is, we start to see a deeper problem than “uncertainty”. This problem is unawareness: many possible consequences of our actions haven’t even occurred to us in much detail, if at all.
Why is unawareness a serious challenge for impartial altruists? Well, impartiality entails that we account for all moral patients, and all the most significant impacts [...]
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Outline:
(08:03) Bird's-eye view of the sequence
(08:34) Introduction to unawareness
(12:03) Unawareness vs. uncertainty
(16:45) Why not just do what works?
(19:00) Case study: Severe unawareness in AI safety
(19:23) Vignette
(23:14) Where this leaves us
(24:42) Acknowledgments
(25:20) References
The original text contained 12 footnotes which were omitted from this narration.
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Confidence: Medium, underlying data is patchy and relies on a good amount of guesswork, data work involved a fair amount of vibecoding.
Intro:
Tom Davidson has an excellent post explaining the compute bottleneck objection to the software-only intelligence explosion.[1] The rough idea is that AI research requires two inputs: cognitive labor and research compute. If these two inputs are gross complements, then even if there is recursive self-improvement in the amount of cognitive labor directed towards AI research, this process will fizzle as you get bottlenecked by the amount of research compute.
The compute bottleneck objection to the software-only intelligence explosion crucially relies on compute and cognitive labor being gross complements; however, this fact is not [...]
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Outline:
(00:35) Intro:
(02:16) Model
(02:19) Baseline CES in Compute
(04:07) Conditions for a Software-Only Intelligence Explosion
(07:39) Deriving the Estimation Equation
(09:31) Alternative CES Formulation in Frontier Experiments
(10:59) Estimation
(11:02) Data
(15:02) Trends
(15:58) Estimation Results
(18:52) Results
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Mental illness (including struggles that don’t meet a specific diagnosis) is a serious public health burden that affects a large proportion of people. This is true within EA as well as in the general population. In EA, as in any community, it's important for us to try to support those who are struggling.
We sometimes see the theory that EA causes unusually bad mental health, but the evidence lightly points toward EA being good or neutral for the wellbeing of most people who engage with it.
Most respondents say EA is neutral or good for their mental health
There have been surveys done specifically about mental health and EA (2019, 2021, 2023), but these didn’t aim to be representative of the EA population. The largest and most representative source is the EA Survey 2022, where most respondents indicated neutral or positive effects of their EA involvement on their [...]
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Outline:
(00:41) Most respondents say EA is neutral or good for their mental health
(02:51) Why might EA be good for wellbeing?
(04:40) Why might it be bad?
(05:25) Correlation and causation
(05:59) Other fields also affect wellbeing
(06:45) EA isnt one-size-fits-all
(07:47) Resources
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Over the last year and a half, Farmed Animal Funders (FAF) shifted our strategy to leverage our positioning and maximize impact. This post updates the wider EA community on our work and how you can get involved.
Summary:
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Outline:
(00:25) Summary:
(01:37) What is Farmed Animal Funders?
(02:29) How is Farmed Animal Funders helping animals?
(03:53) Bespoke Philanthropic Advising
(05:27) Other High-Impact Giving Opportunities
(07:41) Metafundraising
(08:27) How You Can Help
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Ambitious Impact's Charity Entrepreneurship program has now been running for over 5 years, launching more than 50 charities across animal welfare, global development, mental health, education, and many other cause areas. We’re incredibly proud of the work of our founders and the organisations they have built, yet we take far too little time to celebrate their achievements.
In light of this, we’re delighted to share a collection of updates in this post from some of our charities, written by the organisations themselves. We’ve organised updates by rough cause area to make it easier for readers with specific interest areas to jump to the charities working in those spaces.
To pick a few of many highlights:
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Outline:
(01:57) Mental Health
(02:00) Vida Plena (2022 Cohort)
(04:56) Kaya Guides (2022 Cohort)
(07:36) Maternal Health
(07:40) Access to Medicines Initiative (2024 Cohort)
(10:29) NOVAH (No Violence At Home) (2024 Cohort)
(12:26) Lafiya Nigeria (2023 Cohort)
(15:14) Education
(15:17) Learning Alliance (2024 Cohort)
(17:54) Early Child Health
(17:58) Taimaka (2024 Cohort)
(19:39) HealthLearn (2023 Cohort)
(21:28) Spiro (2023 Cohort)
(23:49) Healthy Futures Global (2023 Cohort)
(25:40) Health Policy
(25:43) Concentric Policies (2023 Cohort)
(27:01) Research
(27:04) CEARCH (2022 Cohort)
(28:09) Animal Welfare
(28:12) Shrimp Welfare Project (2021 Cohort)
(31:05) FarmKind (2024 Cohort)
(31:19) Fish Welfare Initiative (2019 Cohort)
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From the publisher's feed