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Curated and popular this week
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This work has come out of my Undergraduate dissertation. I haven't shared or discussed these results much before putting this up. Message me if you'd like the code :)
Edit: 16th April. After helpful comments, especially from Geoffrey, I now believe this method only identifies shifts in the happiness scale (not stretches). Have edited to make this clearer.
TLDR
* Life satisfaction (LS) appears flat over time, despite massive economic growth — the “Easterlin Paradox.”
* Some argue that happiness is rising, but we’re reporting it more conservatively — a phenomenon called rescaling.
* I test rescaling using long-run German panel data, looking at whether the association between reported happiness and three “get-me-out-of-here” actions (divorce, job resignation, and hospitalisation) changes over time.
* If people are getting happier (and rescaling is occuring) the probability of these actions should become less linked to reported LS — but they don’t.
* I find little evidence of rescaling. We should probably take self-reported happiness scores at face value.
1. Background: The Happiness Paradox
Humans today live longer, richer, and healthier lives in history — yet we seem no seem for it. Self-reported life satisfaction (LS), usually measured on a 0–10 scale, has remained remarkably flatover the last few decades, even in countries like Germany, the UK, China, and India that have experienced huge GDP growth. As Michael Plant has written, the empirical evidence for this is fairly strong.
This is the Easterlin Paradox. It is a paradox, because at a point in time, income is strongly linked to happiness, as I've written on the forum before. This should feel uncomfortable for anyone who believes that economic progress should make lives better — including (me) and others in the EA/Progress Studies worlds.
Assuming agree on the empirical facts (i.e., self-reported happiness isn't increasing), there are a few potential explanations:
* Hedonic adaptation: as life gets
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In recent months, the CEOs of leading AI companies have grown increasingly confident about rapid progress:
* OpenAI's Sam Altman: Shifted from saying in November "the rate of progress continues" to declaring in January "we are now confident we know how to build AGI"
* Anthropic's Dario Amodei: Stated in January "I'm more confident than I've ever been that we're close to powerful capabilities... in the next 2-3 years"
* Google DeepMind's Demis Hassabis: Changed from "as soon as 10 years" in autumn to "probably three to five years away" by January.
What explains the shift? Is it just hype? Or could we really have Artificial General Intelligence (AGI)[1] by 2028?
In this article, I look at what's driven recent progress, estimate how far those drivers can continue, and explain why they're likely to continue for at least four more years.
In particular, while in 2024 progress in LLM chatbots seemed to slow, a new approach started to work: teaching the models to reason using reinforcement learning.
In just a year, this let them surpass human PhDs at answering difficult scientific reasoning questions, and achieve expert-level performance on one-hour coding tasks.
We don't know how capable AGI will become, but extrapolating the recent rate of progress suggests that, by 2028, we could reach AI models with beyond-human reasoning abilities, expert-level knowledge in every domain, and that can autonomously complete multi-week projects, and progress would likely continue from there.
On this set of software engineering & computer use tasks, in 2020 AI was only able to do tasks that would typically take a human expert a couple of seconds. By 2024, that had risen to almost an hour. If the trend continues, by 2028 it'll reach several weeks.
No longer mere chatbots, these 'agent' models might soon satisfy many people's definitions of AGI — roughly, AI systems that match human performance at most knowledge work (see definition in footnote).
This means that, while the compa
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SUMMARY:
ALLFED is launching an emergency appeal on the EA Forum due to a serious funding shortfall. Without new support, ALLFED will be forced to cut half our budget in the coming months, drastically reducing our capacity to help build global food system resilience for catastrophic scenarios like nuclear winter, a severe pandemic, or infrastructure breakdown. ALLFED is seeking $800,000 over the course of 2025 to sustain its team, continue policy-relevant research, and move forward with pilot projects that could save lives in a catastrophe. As funding priorities shift toward AI safety, we believe resilient food solutions remain a highly cost-effective way to protect the future. If you’re able to support or share this appeal, please visit allfed.info/donate.
Donate to ALLFED
FULL ARTICLE:
I (David Denkenberger) am writing alongside two of my team-mates, as ALLFED’s co-founder, to ask for your support. This is the first time in Alliance to Feed the Earth in Disaster’s (ALLFED’s) 8 year existence that we have reached out on the EA Forum with a direct funding appeal outside of Marginal Funding Week/our annual updates. I am doing so because ALLFED’s funding situation is serious, and because so much of ALLFED’s progress to date has been made possible through the support, feedback, and collaboration of the EA community.
Read our funding appeal
At ALLFED, we are deeply grateful to all our supporters, including the Survival and Flourishing Fund, which has provided the majority of our funding for years. At the end of 2024, we learned we would be receiving far less support than expected due to a shift in SFF’s strategic priorities toward AI safety.
Without additional funding, ALLFED will need to shrink. I believe the marginal cost effectiveness for improving the future and saving lives of resilience is competitive with AI Safety, even if timelines are short, because of potential AI-induced catastrophes. That is why we are asking people to donate to this emergency appeal
I just looked at the application for the role of content specialist for CEA, which seems to involve a lot of working on this forum.
I noticed that if one indicates they have been personally referred by someone 'involved in effective altruism', one is given the option to skip 'the rest of the application' - which seems like the majority of the substantive information one is asked to give.
This seems overtly nepotistic, and I can't think of a good reason for it - can anyone give one?
The rest of the application seems to be optional also if one indicates that they have not been personally referred by someone. Do you get something different?
https://www.loom.com/share/c0ef87a96a1c4d28bfc0df2e48d7662b
Oh I see, thanks! - I didn't realise this because the statement that appears after indicating you've been personally referred is: "Since you were referred to this position, the rest of the application is optional" which makes it sound like it wouldn't be optional if you weren't referred.
I think that the short hand of "this person vouches for this other person" is a good enough basis for a lot of pre-screening criteria. Not that it makes the person a shoe in for the job, but it's enough to say that you can go by on a referral.
You might say, this is a strange way to pick people, but this is how governments interview people for national security roles. They check references. They ask questions.
I imagine more questions would be asked to the third party who is 'personally referring' the applicant, leading to a slightly different series of interviews anyway. In my experience, people have to work a lot harder to get a job, than to keep one. I know that it's true with everyone that referred me to just about every position. Then if I perform badly it looks poorly on them, but after a certain time, I'm the one referring people onwards, so I have to make my own assessment of if I'm willing to put my reputation on the line.
Yeah but I think it relies too much on a given applicant's estimate of how well CEA knows or how much they trust the connection.
Some reasons could be
a) The purpose of the rest of the questions is to inform the initial sift, and not later stages of the application, and if you have been referred by a trusted colleague, then there is no further use of the optional questions to the initial sift, so it would be a waste of applicants’ time
b) Saving applicants’ time on the initial application makes you likely to receive more applications to choose from
However, these referrals could indeed have a nepotistic effect by allowing networking to have more of an influence on the ease of getting to stage 2.
I was referred to apply to this job by someone who was close to another hiring round I was in (where I reached the final stage but didn’t get an offer).
I can see that this does not feel great from a nepotism angle. However, as Weaver mentions the initial application is only a very rough pre-screening, and for that, a recommendation might tip the scales (and that might be fine).
Reasons why this is not a problem:
First, expanding on Weavers argument:
If the application process is similar to other jobs in the EA world, it will probably involve 2-4 work trials, 1-2 interviews, and potentially an on-site work trial before the final offer is made. The reference maybe gets an applicant over the hurdle of the first written application, but won't be a factor in the evaluation of the work trials and interviews. So it really does not influence their chances too much.
Secondly, speaking of how I update on referrals: I don't think most referrals are super strong endorsements by the person referring, and one should not update on them too much. I.e. most referrals are not of the type "I have thought about this for a couple of hours, worked with the person a lot in the last year, and think they will be an excellent fit for this role", but rather "I had a chat with this person, or I know them from somewhere and thought they might have a 5%-10% chance of getting the job so I recommended they apply".
Other reasons why this could be bad:
1. The hiring manager might be slightly biased and keep them in the process longer than they ought to (However, I do not think this would be enough to turn a "not above the bar for hiring" person into the "top three candidate" person). Note that this is also bad for the applicant as they will spend more time on the application process than they should.
2. The applicant might rely too much on the name they put down, and half-ass the rest of the application, but in case the hiring manager does not know the reference, they might be rejected, although their non-half-assed application would have been good.
tabforacause - a browser extension which shows you ads and directs ad revenue to charity - has launched a way to set GiveDirectly as the charity you want to direct ad revenue to.
It doesn't raise a lot of money per tab opened, obviously, but I'm not using my newtab page for anything else and find the advertising unobtrusive - its in the corner, not taking up the whole screen - if. you're like me in these respects it could be something to add.
Thanks for pointing this out; I'll note that Partners in Health is also available, and GiveWell seems to like them but doesn't think that they beat the GiveWell charity bar, at least when this was written (https://www.givewell.org/international/charities/PIH#:~:text=Partners%20in%20Health%20provides%20comprehensive,network%20of%20community%20health%20workers.). I'd be interested in seeing anything about whether Partners in Health is a better option than GiveDirectly.