EA Forum Podcast (All audio)

Overview

This post summarizes a new preprint on alternative proteins from the Humane and Sustainable Food Lab: New alternatives, same orders. We investigated 19 restaurants that introduced plant-based alternative proteins throughout 2016 to 2023, including Beyond sausage, the Impossible burger, and many others. We find essentially no evidence here that alternative proteins reduce meat purchases or those of other animal products, even for the same individual customers over time.

Interactive plots here.

Why this matters

A central theory of change for alt proteins is substitution: match meat on taste, price, and convenience, and consumers should replace a majority of their meat purchases with alternatives. EAs, including funders, are excited about this approach as a way of reducing animal suffering and creating a more environmentally sustainable food system. Coefficient Giving recently announced a 10 million dollars R&D fund for making better tasting alt proteins, while the Nova Vista Foundation is investing a further 10 million dollars in policy and market-shaping, which they consider “high EV bets due to their leverage.” There is also a general sense in EA that the animal advocacy movement might be on the verge of a large influx of funding, much of which may go to [...]

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Outline:

(00:17) Overview

(00:52) Why this matters

(04:07) Which alt proteins?

(06:27) What we did

(09:33) Results

(09:59) A1

(13:36) A2

(14:13) A3

(15:00) A4

(15:27) The restaurants in detail

(17:45) Real-world data problems

(19:27) Where do we go from here?

(20:58) Acknowledgements

The original text contained 10 footnotes which were omitted from this narration.

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At the local AI safety co-working space, there are ~two kinds of regulars.

There's the kind of regular who's been thinking seriously about AI safety and alignment since pre-2022, who have passing to intimate familiarity with the funding ecosystem, the Sequences, and various conferences that happen at Lighthaven. Let's call them rationalists.

Then there's the kind of regular who comes in with many years of impressive industry or government experience, who realized in the last few years that it is important and worthwhile to pivot their career towards making sure that this AI thing is handled competently by the people in power, and who have many valuable skills, insights, and connections that are lacking in rationalist culture. Let's call them professionals.

There are, of course, many people who are somewhere in between - bright undergrads born this millennium who have been involved in EA since stumbling upon 80 thousand hours in high school, professionals who previously identified as EA but drifted out of the scene a few years ago, founders who have idly read some Scott Alexander. But let's call it a dichotomy for now.

There's a large culture gap between the rationalists and the [...]

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This is a linkpost for Is Extinction Risk Mitigation Uniquely Cost-Effective? Not in Standard Population Models by Gustav Alexandrie and Maya Eden, which was published on 18 August 2025 as chapter 20 of the book Essays on Longtermism: Present Action for the Distant Future. I got Claude Opus 5 to write the summary and 2 objections below after some iteration. The objections came from me. Gustav said the summary "looks correct from very quickly skimming it, though I may well have missed if there are mistakes". I also think it is accurate based on my read of the article. Thanks to Gustav for feedback on the draft objections, and pushing me to shorten the summary, which now has 1/3 as many words as the main text of the chapter (excluding abstract, footnotes, references, and appendix).

TL;DR

Alexandrie and Eden take aim at the long-run argument for prioritising extinction risk mitigation: the Parfit-derived claim that the gap between a 99% catastrophe and a 100% catastrophe dwarfs the gap between no catastrophe and a 99% one, because extinction alone forecloses all future generations. They grant the argument's ethics entirely — total, time-neutral aggregation of welfare — and attack the demography it [...]

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Outline:

(01:04) TL;DR

(02:44) 1. The target argument

(04:48) 2. The framework: the long-term value ratio

(07:36) 3. Pure population shocks: three models

(10:49) 4. Shocks to all factors of production: the robust result

(12:18) 5. The back-of-the-envelope calculation

(15:19) 6. Increasing the stock of natural resources

(16:42) 7. Conclusions

(17:51) 8. Two things I'd push on

(17:55) 8.1. The model's separability across events is doing real work

(21:28) 8.2. A minor note on the space-expansion contrast

(24:12) References

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Epistemic status: We are quite confident that Biological AI models (BAIMs) safety requires further work, but uncertain about its scale. The apparent gap may be refuted by one experiment, filled by a few researchers working for a year, or prove to be substantial enough to call for an entire subfield.

Disclaimer: this post has been written with a colleague, that due to her current job can't post out of her own forum account

What we’re looking for: please poke holes in this. In particular, we’d value:

• Arguments against prioritizing this work;
• Important research or organizations we’ve missed;
• Reasons the research questions below would not actually change decisions;
• Information-hazard or capability-externality concerns we’re underweighting;
• Better questions than the ones we propose

Biological AI models (protein, genomic, and single-cell models trained directly on biological data) enable increasingly capable biological design. That carves the path to new vaccines and therapeutics, but also to biorisk scenarios.

These models exist for beneficial scientific or defensive purposes. However, the underlying capabilities could also be applied to harmful objectives. They are currently an important step for designing novel pathogens, and as they improve we expect them to remain a part of [...]

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Outline:

(01:04) The case in brief

(02:42) Biological AI models are becoming more capable

(04:15) We are missing some basic measurements

(05:59) Research questions that could change what we do

(06:11) Will general-purpose AI subsume biological AI models?

(06:36) What drives BAIM performance?

(06:57) How well do capabilities generalize?

(07:32) How should BAIM safeguards work?

(08:26) Why now?

(09:24) Reasons we might be wrong

(09:27) Artificial General Intelligence will eat this problem

(09:50) BAIMs may not be the bottleneck

(10:08) Information hazards

(10:35) If you know of relevant work, disagree with our framing, or think these are the wrong questions, please tell us - is there something we are missing?

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Epistemic status: Speculation from two decently informed advocates armed with anecdata.

Note on process: After having some version of this conversation several times and saying, “we should probably write about this publicly,” we took the less heroic route: we recorded one of our conversations, fed the transcript into an LLM, and then substantially revised the structure, substance, and framing ourselves. We will not be sharing the transcript, as it is interspersed with side comments about dogs.

We’ve been very slow to get this out. We wrote this and began receiving feedback on our draft before very relevant projects went live, including the announcement of Spring Innovation Fund and Rethink Priorities’ call for new animal founders.

Many thanks to those who reviewed our drafts. All mistakes are our own.

Summary

The animal movement is at an extremely exciting stage, with many promising new ideas, funding opportunities, and talented individuals entering the space. We want to encourage this energy, while also noting a concerning pattern that we’ve observed:

The effective animal advocacy world has a pattern of high levels of enthusiasm for a specific intervention that eventually gives way to a rapid downward adjustment, as expectations run ahead of the evidence [...]

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Outline:

(01:05) Summary

(03:17) The recurring pattern

(06:42) Why EA is vulnerable to silver bullets

(08:51) Why welfare tech might be the next "silver bullet"

(10:42) Why are bubbles bad?

(12:22) What would a healthier approach look like?

(13:59) Conclusion

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I'm Molly Kovite, General Counsel at Coefficient Giving. I joined in 2021 as the organization's first lawyer and have since grown the team to (soon to be) seven lawyers and three legal admins.

Over the past couple of months, a number of AI safety organizations have asked me about whether they should hire in-house counsel and if so, what they should look for. This post is my attempt to write down what I've told them: how to tell when you've outgrown outside counsel, what in-house counsel does and doesn't get you, how to scope the role, and how to run a process that actually tells you whether someone will be good at it. This is one lawyer's experience at one organization, so treat it as calibrated opinion rather than settled wisdom. I'd be glad to hear where people disagree.

Some signs to look for:

• You’re unsure whether you’re bringing the right things to outside counsel
• Important plans or projects have been derailed or significantly delayed two or more times in ~6 months due to unexpected legal issues cropping up, despite running things by outside counsel
• You feel [...]

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Outline:

(00:56) How do I know when I should hire an in-house attorney?

(03:09) What are some of the downsides of hiring in-house counsel?

(05:37) How do I scope the role?

(07:45) What basic characteristics should I be looking for in an in-house counsel?

(09:27) How should I design my work test(s)?

(13:15) What should I look for in interviews?

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Michael Nielsen has a beautiful new essay on moral imagination: the ability humans have to 'develop and transmit new notions of good action, indeed, even new kinds of good'.

As examples, he gives:

• Hammurabi's creation of a code of laws (in 1754 BCE) and his justification of his rule not in terms of divine or hereditary right, but by the delivery of justice to his citizens.
• St Gregory of Nyssa's argument (in 379 CE) that the entire institution of slavery was morally wrong.
• Joyce Roush's (1998 CE) idea that she should altruistically donate a kidney to help save the life of an unknown stranger. 

Nielsen acknowledges that any particular act of moral imagination often builds on earlier precursors, but that this shouldn't lessen our appreciation for these major steps forward.

One could think of moral imagination as a key part of making moral progress. Moral progress (moving towards better systems of morality) involves the creation of new approaches to morality, and the critiquing of what has been suggested. Through the iteration of creation and critique, we slowly make progress. Some of this process happens within moral philosophy (especially the critique), but much of it happens in the wider [...]

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This personal post is not part of the competition, as my intent is not to produce an original constructive response to cluelessness. However, Toby Tremlett encouraged me to share it insofar as it contributes to this week's conversation.

TL; DR: I work in animal welfare and am clueless. To avoid choosing actions at random, I decided to write a decision procedure for myself and to indicate the assumptions that accompany it. This does not constitute a new argument on the topic. Rather, this is a layman's attempt to apply it. For those who want to skim, you can skip to the Decision procedure section, where I bolded the aspects of my decision procedure that seem most likely to elicit pushback.

• Like many in animal welfare, I intuitively agree with cluelessness without understanding all of the philosophical steps behind it, and this will show in the post. I focused on honestly representing my understanding of cluelessness, rather than high-quality philosophical reasoning. I’m partly betting on Cunningham's Law here.

• This post does not aim to be a constructive general response like bracketing. It is also mostly derived from other writings on cluelessness. It assumes surface-level familiarity with [...]

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Outline:

(00:55) Epistemic status and intent

(01:55) What Cluelessness Means To Me, a Layman

(03:39) Why not just use what exists?

(04:04) Why not maximize expected value?

(04:12) Why not apply bracketing?

(05:40) Why not apply metanormative bracketing?

(06:28) Benefits of having my own decision procedure:

(07:37) Section 1: My decision procedure

(07:42) Disclaimers

(08:39) My decision procedure

(15:57) Brief tentative conclusion

(16:48) Early updates from applying the procedure

(17:27) Section 2: My judgment on underdetermined matters

(18:20) Eight underdetermined assumptions

(22:06) Next steps

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Why I favor fallibilism over cluelessness

I’ve long been struck by a structural commonality between radical skepticism and cluelessness worries. Since the EA Forum has been discussing cluelessness this week, I figured I’d take another stab at explaining why I don’t find it a credible concern. (Too late to qualify for the official contest, alas.)

Skeptical Burdens

Open-minded people may be tempted by a discourse norm on which we should treat our interlocutors as epistemic equals in a sense that requires us to refrain from holding to conclusions that we cannot prove to their satisfaction. A striking thing about philosophy is that you soon learn that this discourse norm would prevent you from having almost any beliefs at all. A “radical skeptic” who doubts the existence of the external world, or the past, or the principle that the past is some guide to the future, cannot be logically compelled to abandon his skepticism. So we’d best not pin our hopes on such an impossible ambition. We must settle for merely establishing to our own satisfaction that we can reasonably maintain our beliefs in the face of the skeptic's contrary arguments. The question is not whether we can persuade him [...]

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Outline:

(00:32) Skeptical Burdens

(02:05) Epistemic Difficulty vs Cluelessness

(04:00) DiGiovanni's Argument

(07:01) Numerical Precision

(08:20) Prospective Reasons

(11:43) The Value Correlation Thesis

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This is a cross-post from Astral Codex Ten, Scott Alexander's Substack. Original post here.

There are ACX meetup groups in cities around the world. Every fall and spring, I make a Meetups Everywhere post to try to signal-boost and support them. This summer, I want to focus on college effective altruist groups in particular.

Many colleges have effective altruist meetup groups or clubs. They range from fun social gatherings of like-minded individuals, to serious organizations working hard to build a better world; most are both at once. They have to replenish their ranks each fall as seniors leave and new freshmen enter.

This year, they’re trying especially hard. The AGI clock is ticking, and the movement wants to build up capacity as quickly as it can. At the same time, it's flush with new resources as newly-minted AI millionaires and billionaires donate their fortunes. Its big bottleneck is now finding the talented, value-aligned, motivated people who can convert that money into good outcomes. And since those people are probably all busy doing other things, they’ve asked me to recruit you instead.

I’ll give the real pitch (including caveats) on a later thread. This is the Call for Organizers. Many [...]

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