EA Forum Podcast (Curated & popular)

What is the highest form of love? According to the VascoBot Claude programmed for me: “Thanks for the great question, AgentMa🔸. I strongly upvoted it. I think the highest form of love is expected total hedonistic utilitarianism (ETHU) applied to all sentient beings, weighted by their welfare ranges as a fraction of that of humans. However, I believe most discussions of love neglect the welfare im...

We are Melanie and Anthony, the two community builders at EA Barcelona. In this post, we share where the group stands today and reflect on key learnings from nearly three years of grant-funded community building. We hope these reflections are useful to other community builders, funders, and CEA, particularly around what it realistically takes to build and sustain EA communities over multiple years...

Note: opinions are all my own. Following Jeff Kaufman's Front-Load Giving Because of Anthropic Donors and Jenn's Funding Conversation We Left Unfinished, I think there is a real likelihood that impactful causes will receive significantly more funding in the near future. As background on where this new funding could come from: Coefficient Giving announced:  A recent NYT piece covered...

The EA Grants Database is a new site that neatly aggregates grant data from major EA funders who publish individual or total grant information. It is intended to be easy to maintain long term, entirely piggybacking off of existing data that is likely to be maintained. The website data is updated by a script that can be run in seconds, and I anticipate doing this for the foreseeable future. In crea...

Cross-posted to LessWrong. Summary History's most destructive ideologies—like Nazism, totalitarian communism, and religious fundamentalism—exhibited remarkably similar characteristics: epistemic and moral certainty extreme tribalism dividing humanity into a sacred “us” and an evil “them” a willingness to use whatever means necessary, including brutal violence. Such ideological fanaticism was...

Context: The authors are a few EAs who currently work or have previously worked at the European Commission. In this post, we make the case that more people[1] aiming for a high impact career should consider working for the EU institutions[2] using the Importance, Tractability, Neglectedness framework, and; briefly outline how one might get started on this, highlighting a currently open recruitment...

We're trying something a bit new this week. Over the last year, Toby Ord has been writing about the implications of the fact that improvements in AI require exponentially more compute. Only one of these posts so far has been put on the EA forum. This week we've put the entire series on the Forum and made this thread for you to discuss your reactions to the posts. Toby Ord will check in once a day...

This is a link post. There is an extremely important question about the near-future of AI that almost no-one is asking. We’ve all seen the graphs from METR showing that the length of tasks AI agents can perform has been growing exponentially over the last 7 years. While GPT-2 could only do software engineering tasks that would take someone a few seconds, the latest models can (50% of the time) do...

This is a link post. In the last year or two, the most important trend in modern AI came to an end. The scaling-up of computational resources used to train ever-larger AI models through next-token prediction (pre-training) stalled out. Since late 2024, we’ve seen a new trend of using reinforcement learning (RL) in the second stage of training (post-training). Through RL, the AI models learn to do...

This is a link post. The new scaling paradigm for AI reduces the amount of information a model can learn from per hour of training by a factor of 1,000 to 1,000,000. I explore what this means and its implications for scaling. The last year has seen a massive shift in how leading AI models are trained. 2018–2023 was the era of pre-training scaling. LLMs were primarily trained by next-token predicti...

This is a link post. The shift from scaling up the pre-training compute of AI systems to scaling up their inference compute may have profound effects on AI governance. The nature of these effects depends crucially on whether this new inference compute will primarily be used during external deployment or as part of a more complex training programme within the lab. Rapid scaling of inference-at-depl...

This is a link post. Building on the recent empirical work of Kwa et al. (2025), I show that within their suite of research-engineering tasks the performance of AI agents on longer-duration tasks can be explained by an extremely simple mathematical model — a constant rate of failing during each minute a human would take to do the task. This implies an exponentially declining success rate with the...

This is a link post. Improving model performance by scaling up inference compute is the next big thing in frontier AI. But the charts being used to trumpet this new paradigm can be misleading. While they initially appear to show steady scaling and impressive performance for models like o1 and o3, they really show poor scaling (characteristic of brute force) and little evidence of improvement betwe...

This is a link post. AI capabilities have improved remarkably quickly, fuelled by the explosive scale-up of resources being used to train the leading models. But if you examine the scaling laws that inspired this rush, they actually show extremely poor returns to scale. What's going on? AI Scaling is Shockingly Impressive The era of LLMs has seen remarkable improvements in AI capabilities over a v...

EA thinking is thinking on the margin. When EAs prioritise causes, they are prioritising causes given the fact that they only control their one career, or, sometimes, given that they have some influence over a community of a few thousand people, and the distribution of some millions or billions of dollars. Some critiques of EA act as if statements about cause prioritisation are absolute rather tha...

There is an insane amount of money being thrown around by international organizations and agreements. Nobody with any kind of power over these agreements is asking basic EA questions like: "What are the problems we're trying to solve?" "What are the most neglected aspects of those problems?" and "What is the most cost-effective way to address those neglected areas?" As someone coming from an EA ba...

I've started a substack, so a few more people might encounter my spicy takes - I'll still mostly be here. USAID is gone. Direct country aid to low income countries is down 25%. So now's a great time to share five ways I think development charity can be done better in 2026. To state the obvious... none of these ideas will be the best approach all of the time, there's plenty of grey area and nuance....

Summary In January 2025, FarmKind ran a provocative media campaign which used controversial media messaging and materials to promote ‘offsetting’ as an option for individuals who are concerned about factory farming but are currently unwilling or unable to change their diet. The campaign raised an estimated $16,700--$59,300 (explained in our Results section below) and generated a number of media ‘h...

Summary Our new book, All the Lives You Can Change: Effective Altruism for Christians, will be published in April 28 2026 The book introduces effective altruism–style thinking to a Christian audience, framing effectiveness, cause prioritization, and evidence-based action as expressions of loving God and loving one's neighbor (Matt. 22:37–39) Authored by @dominicroser, @DavidZhang and me (JD). You...

TL;DR When surveyed, the EA community and leaders think ~18-24% of resources should go towards animal advocacy. The actual figure is about 7%. We as the EA ecosystem are putting less resources (money and time) into animal advocacy than the movement thinks we should when surveyed. This disparity could be because of loss of message fidelity, it's a harder cause area to pitch donors, or the role of l...

Thank you At EAGx Amsterdam, I shared most of this as a talk. I was afraid I'd run out of time, so I decided to do things backwards and start with the thank you. I did not want to miss the most important thing. Since I might lose you halfway reading this long and personal piece, I decided to keep this order. The EA community creates a space that makes it easier to donate and to live my values—and...

An all too common reason I’ve seen to “quit EA” is disliking aspects of the community. Maybe “they’re” too focused on the “wrong cause area” or are skeptical of yours. Maybe “they” annoy you. Maybe “they” publicly attacked you. I’m putting quotation marks around “they” to highlight an important thing: EA is composed of individuals. Some EAs may annoy you / focus on the "wrong cause area" / publicl...

Note: I used LLMs to draft different parts of this. I've checked almost everything, but there might be some mistakes remaining. Apologies for posting this on Christmas Eve. I wanted to get this out the door before the end of the year. Questions welcome, and if it's easy to pull metrics to answer them, I will. Summary 80,000 Hours launched a video program in 2025 focused on longform, cinematic, per...

I really enjoyed reading the "why I donate" posts in the past week, so much so that I felt compelled to add my reflections, in case someone finds my reasons as interesting as I found theirs. 1. My money needs to be spent on something, might as well spend it on the most efficient things The core reason I give is something that I think is under-represented in the other posts: the money I have and ea...

This year, I have given money to a range of EA cause areas. Most of it has either been towards global health and development, or EA infrastructure I believe does or could lead to effective fundraising for global health and development. The following are a list of very selfish personal reasons why I like to do this. I feel the selfless reasons have been adequately covered elsewhere, so I'm intentio...