EA Forum Podcast (All audio)

Per title, it would be great to get much earlier publishing of program, speakers and schedule for these events.

Benefits:

• Can decide if it's an event that makes sense to join
• Can start planning side meetings / events earlier
• Can propose own session ideas taking into account what's already confirmed
• More in line with industry best practices (to attract folks outside EA circles)
• Can reach out to folks who are known to be attending
• etc

Understand it's a big undertaking to get the full program together and coordinating with a lot of volunteers (who have our big thanks!), but having a means to get it out progressively starting earlier would help attendees a lot.

Thanks!

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

Summary

Using historical data from 2015-2024, The Humane League (THL) estimates that each dollar spent on cage-free corporate campaigns has spared approximately two hens from cages. This estimate covers both the acquisition of new corporate commitments and the accountability work required to ensure those commitments are fulfilled across THL's US and Global corporate cage-free efforts.

The calculation draws on:

• Corporate cage-free policy fulfillment data collected by THL
• Estimates of the number of hens spared by each corporate policy THL helped secure
• Historical program cost data, adjusted for inflation and including proportional overhead

It is important to note that this is not an estimate of THL's overall cost-effectiveness. Rather, this analysis covers only THL's corporate cage-free campaigns. Other programs, such as THL's movement building work via the Open Wing Alliance or broiler welfare, are excluded here.

The goal of this analysis is twofold: to inform internal resource allocation, and to offer a transparent, accessible response to one of the most common questions asked by THL supporters. The methodology used prioritizes accessibility over granularity at some points, which are detailed in the “Additional Assumptions & Limitations” section.

While this model is simplified, we are encouraged that the resulting [...]

---

Outline:

(00:13) Summary

(02:27) Methodology & Assumptions

(07:25) Additional Assumptions & Limitations

(10:28) Future Work

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

Cross-posted from Good Structures.

For impact-minded donors, it's natural to focus on doing the most cost-effective thing. Suppose you’re genuinely neutral on what you do, as long as it maximizes the good. If you’re donating money, you want to look for the most cost-effective opportunity (on the margin) and donate to it.

But many organizations and individuals who care about cost-effectiveness try to influence the giving of others. This includes:

• Research organizations that try to influence the allocation or use of charitable funds.
• Donor advisors who work with donors to find promising opportunities.
• People arguing to community members on venues like the EA Forum.
• Charity recommenders like GiveWell and Animal Charity Evaluators.

These are endeavors where you’re specifically trying to influence the giving of others. And when you influence the giving of others, you don’t get full credit for their decisions! You should only get credit for how much better the thing you convinced them to do is compared to what they would otherwise do.

This is something that many people in EA and related communities take for granted and find obvious in the abstract. But I think the implications of this aren’t always fully digested by the [...]

---

Outline:

(03:34) Impact is largely a function of what the donor would have done otherwise.

(04:36) Is improving the use of effective or ineffective charitable dollars easier?

(06:14) How do people respond to these lower impact interventions?

(08:14) What are the implications of paying a lot more attention to funding counterfactuals?

(10:21) Objections to this argument.

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

More than two years ago, Sudan descended into war. What began as a clash between the army and paramilitary quickly became one of the world's worst humanitarian crises. Millions have been displaced. Families are going hungry. Communities are cut off from medicine. Violence and disease spread in silence. And the world keeps looking away, even as the human cost grows daily.

So why are you seeing more about Sudan in the news now? On October 26, the RSF captured El Fasher after an 18-month siege. What followed: 460+ patients and companions killed at a Maternity Hospital. 82,000 people fled on foot. Mass graves visible in satellite imagery.

Since the war began in April 2023: 150,000+ killed (which is most likely undercounted). 13 million displaced, the largest displacement crisis in the world. 30 million people, over half of Sudan's population, need humanitarian assistance. Famine confirmed in El Fasher and elsewhere. Acute malnutrition rates up to 35% in children.

Listen to today's episode of the Daily, where New York Times correspondent Declan Walsh explains how this became one of the worst humanitarian crises in decades.

But here's what makes this different from a "hopeless" crisis. The infrastructure to save lives [...]

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

This is a brief update about what's been happening on the 80k podcast team over the last 6 months, because we’ve undergone quite a few changes. We’re also hiring (more details below).

As background: The podcast has been running for 8(!) years, run and predominantly hosted by Rob Wiblin. Over that time the podcast has grown to ~127,000 subscribers across Spotify, YouTube and Apple Podcasts, the production value and knowledge of how to execute a great podcast have very much improved, and Luisa Rodriguez joined Rob as a host. But, given capacity constraints, 80k hasn’t invested significant resources into testing out ways to substantially scale the podcast's impact. Rob hosted while also needing to manage the team and leading on strategy. Alongside this, he has led projects like selecting and appointing a new board for 80,000 Hours as we spun out of EV. Over the coming year, with me now focused on strategy for the podcast, 80k aims to invest notably more in experimenting with potential ways to grow the podcast team and scale its impact.

There are a couple of reasons we think it's worth investing significant resources into growing the podcast team. The first is [...]

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

Every month, the Forecasting Research Institute asks top computer scientists, economists, industry leaders, policy experts and superforecasters for their AI predictions. Here's what we learned from the first three months of forecasts:

AI is already reshaping labor markets, culture, science, and the economy—yet experts debate its value, risks, and how fast it will integrate into everyday life. Leaders of AI companies forecast near futures in which AI cures all diseases, replaces whole classes of jobs, and supercharges GDP growth. Skeptics see small gains at best, with AI's impact amounting to little more than a modest boost in productivity—if anything at all.

Despite these clashing narratives, there is little work systematically mapping the full spectrum of views among computer scientists, economists, technologists in the private sector, and the public. We fill this gap with LEAP, a monthly survey tracking the probabilistic forecasts of experts, superforecasters, and the public. Expert participants include top-cited AI and ML scientists, prominent economists, key technical staff at frontier AI companies, and influential policy experts from a broad range of NGOs.

LEAP operates on three key principles:

• Accountability: LEAP forecasts are detailed and verifiable, encouraging disciplined thinking and allowing us [...]

---

Outline:

(02:52) The LEAP Panel

(04:55) LEAP Waves 1-3

(05:25) Insights from Waves 1-3

(05:29) 1. Experts expect sizable societal effects from AI by 2040.

(09:03) 2. Experts disagree and express substantial uncertainty about the trajectory of AI.

(09:48) 3. The median expert expects significantly less AI progress than leaders of frontier AI companies.

(13:23) 4. Experts predict much faster AI progress than the general public.

(16:41) 5. There are few differences in prediction between superforecasters and experts, but, where there is disagreement, experts tend to expect more AI progress. We don't see systematic differences between the beliefs of computer scientists, economists, industry professionals, and policy professionals.

(19:34) Future LEAP waves

The original text contained 2 footnotes which were omitted from this narration.

---

First published:

Source:

Linkpost URL:
https://forecastingresearch.substack.com/p/introducing-leap

---

Narrated by TYPE III AUDIO.

---

Images from the article:

Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

This work is my own, written in my spare time, and doesn’t reflect the views of my employer. Less than ~3% of the text is AI-generated. Thank you to Laila Kassam, Haven King-Nobles, Lincoln Quirk, Tom Billington and Harley McDonald-Eckersall for their feedback, which doesn’t imply their endorsement of the ideas presented.

• Most animal advocates want sweeping change — to end factory farming at the very least, and often to go even further. But across the movement, we rarely talk in depth about how we'll actually achieve these kinds of long-term goals.
• Instead, I believe much of the movement has adopted a mindset I call short-term pragmatism: a focus on measurable, near-term wins that has delivered real victories, but which risks leaving us without a path to our ultimate aims. I suspect the convergence towards this mentality is a reaction to another dominant mindset, passionate idealism.
• This post argues that to achieve the long-term goals we truly aspire to, we must think differently. I make the case for visionary pragmatism — a third way that starts with an ambitious end goal and applies clear thinking to achieve it.
• To illustrate how animal advocates can position ourselves as [...]

---

Outline:

(00:32) Summary

(02:00) Introductory Context

(04:04) 1. The problem: our current way of thinking risks long-term failure

(05:24) 1.1. Short-term pragmatism: our dominant mindset

(08:20) 1.2. Why (I think) short-term pragmatism draws us in

(10:18) 1.3. The strategic limitations of short-term pragmatism

(12:12) 2. The solution: visionary pragmatism

(12:33) 2.1. Defining visionary pragmatism

(13:31) 2.2. Six core qualities of visionary pragmatism

(42:02) 2.3. Summarising visionary pragmatism

(42:45) 3. Next steps: cultivating visionary pragmatism

(44:31) 4. Over to you!

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

EA has always had a coolness crisis. The name itself is clunky and overly precise. The logo is fine-but-not-great, and the visual branding has never excited anybody. EA orgs have spent over a decade struggling to tell exciting stories or get serious numbers of social media followers.

In short: It's never been sexy; it's never been cool.

Maybe you don’t think being cool matters. That's a fine opinion if you’re ok with EA being a group of 10,000 people, ~70% male and ~75% white, circularly spending Dustin Moskovitz's money.

But imagine a movement of a million people. A million people donating a percentage of their income to create a community fund as large as Open Phil's. A million people working at high-impact organizations.

Getting to a million people means being cool in public campaigns. It means cool branding and cool social media posts and cool copy in emails. The unfortunate truth is that the attention economy consumes us, and the world is a popularity contest. EAs often have this dastardly intuition that they can convince people just by being right. I once watched an EA tell a man to rip up his backyard grass and [...]

---

Outline:

(03:24) 1. Heroes need villains

(05:10) 2. Please, for God's sake, hire non-EA creative talent

(05:58) 3. Invest in creatives.

(06:59) 4. Learn to drop the caveats

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

Looking back, it appears that much of my intellectual output could be described as legibilizing work, or trying to make certain problems in AI risk more legible to myself and others. I've organized the relevant posts and comments into the following list, which can also serve as a partial guide to problems that may need to be further legibilized, especially beyond LW/rationalists, to AI researchers, funders, company leaders, government policymakers, their advisors (including future AI advisors), and the general public.

---

First published:

Source:

---

Narrated by TYPE III AUDIO.

by Caitlin Tulloch, Senior Director of Research, Learning, and Product at GiveDirectly. Caitlin is an expert in evidence-based policy and cost-effectiveness, and formerly served as Deputy Director in USAID's Office of the Chief Economist.

Summary

• ❌ Cash isn’t a silver bullet and it can’t replace missing or broken systems. It doesn’t pave roads, improve schools, or stock pharmacies.
• 💸 Yet when it comes to reducing poverty, there are no interventions with more consistent evidence for their effectiveness than cash.
• ⚙️ GiveDirectly follows the evidence: we use cash where it works best, and test alternatives when the goal isn’t just poverty reduction.

GiveDirectly has written a lot about what giving people money is consistently very good at (e.g., recipients earn more, spend more, own more assets, and the local economy gets a boost), the myths that aren’t true (e.g, cash doesn’t make people work less or drink more), and the fact that it's what most recipients prefer.

But the fact that cash improves many things doesn’t mean it improves everything. And frankly, that's an unrealistic bar to set.

I’ve spent the last 15 years doing cost-effectiveness analyses across education, health, nutrition, and livelihoods—first at MIT's J-PAL, then [...]

---

Outline:

(01:52) Giving individuals money won't build infrastructure or systems

(05:22) When poverty reduction is the goal, cash works; when the goal is something else, we test

(07:45) This isn't an either/or--it's about using the right tool for the outcome

---

First published:

Source:

---

Narrated by TYPE III AUDIO.