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I'm putting together Metaculus' first animal-focused forecasting tournament, and am reaching out to ask for your support in making this happen.
What is it?
This tournament will generate probabilistic forecasts on decision-relevant questions affecting animals, from alternative proteins and animal welfare policy to AI impacts and wild animal welfare. The goal is to help funders, researchers, and organizations in our community make more informed strategic decisions.
Why it matters
Most forecasters will be from outside the animal movement, bringing fresh perspectives to questions we care about. Better forecasts can lead to better prioritization of interventions and ultimately better outcomes for animals.
How you can help
I'm raising funds on Manifund to create a prize pool that will incentivize quality forecasting. The minimum funding goal is $3,000, with an ideal goal of $15,000.
You can support here.
For more context, I previously posted a call for questions for this tournament.
Any support, whether funding or spreading the word, would be hugely appreciated! Very happy to answer any questions in the comments.
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Outline:
(00:19) What is it?
(00:41) Why it matters
(00:57) How you can help
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Key regulators have agreed to let the company kill its profit caps and restructure as a for-profit — with some strings attached
This is the full text of a post first published on Obsolete, a Substack that I write about the intersection of capitalism, geopolitics, and artificial intelligence. I’m a freelance journalist and the author of a forthcoming book called Obsolete: Power, Profit, and the Race to Build Machine Superintelligence. Consider subscribing to stay up to date with my work.
This morning, the Delaware and California attorneys general conditionally signed off on OpenAI's plan to restructure as a for-profit public benefit corporation (PBC), seemingly closing the book on a fiercely contested legal fight over the company's future.
Microsoft, OpenAI's earliest investor and another party with power to block the restructuring, also said today it would sign off in exchange for changes to its partnership terms and a $135 billion stake in the new PBC.
With these stakeholders mollified, OpenAI has now cleared its biggest obstacles to a potential IPO — aside from its projected $115 billion cash burn through 2029.
While the news initially seemed like a total defeat for the many opponents of the [...]
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Outline:
(00:12) Key regulators have agreed to let the company kill its profit caps and restructure as a for-profit -- with some strings attached
(02:07) The governance wins
(08:16) No more profit caps
(11:54) Testing my prediction
(13:22) A political, not a legal, question
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https://www.obsolete.pub/p/the-end-of-openais-nonprofit-era
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The best approach to take to hiring differs by industry.
This means that best practice differs across startups, think tank, a video production, non-profits, academia, and news outlets will all have different practices. The practices that work best in the EA ecosystem will be different again – but unfortunately the effective altruism organisation landscape is much smaller than all of those, and so people haven't written books on how to do it.
I have been working as a hiring manager and sometimes grant maker in this space for over ten years, and I have developed some views on which practices work well in this industry. And I’ve noticed that others have (semi-)independently converged on these!
Below I've written out a few of the ones which I follow. I’ve especially tried to list those which might seem most surprising to people coming from industries like the ones listed above.
I’m trying to do a pretty quick job of this so that it actually gets out there. [Having written that sentence, I proceeded not to publish the post for 2 years. So if you’re wondering why there are errors in it, it's because this time round I’m actually going [...]
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Outline:
(01:45) Run unstructured interviews
(03:18) Work tests can be feasible and useful even for high-skill roles
(05:24) Informal references are useful
(08:07) Get information from people with conflicts of interest
(09:43) You can put numbers on things (but don't trust them too much)
(10:51) Bonus suggestion for applicants: Ask about the people you'll be working with
(11:59) Getting advice
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Audio note: this article contains 381 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description.
(This post will be much easier to follow if you’ve first read either “Should you go with your best guess?” or “The challenge of unawareness for impartial altruist action guidance”. But it's meant to be self-contained, assuming the reader is familiar with the basic idea of cluelessness.)
According to the view that we’re clueless, the far-future consequences of many of our actions are so ambiguous that we can’t say if they’re good, bad, or neutral in expectation. Concerningly, this view doesn’t even let us say that the most obviously bad actions are, well, bad. I’ll show how we can take cluelessness seriously and still rule out these actions in a principled way.
To see the worry, consider this story. You’re a fairly thoughtful longtermist who one day comes across the idea of cluelessness. You’re skeptical, but you find yourself grudgingly agreeing that predictions about the far future are mostly made-up. Claims like “this intervention will increase expected total welfare across the cosmos” start to seem fake. Still, surely [...]
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Outline:
(09:56) The problems and why previous work doesn't fully solve them
(10:57) Problem 1: Radical cluelessness due to indeterminate beliefs
(14:03) Problem 2: Tradeoff between infectious incomparability and stakes-insensitivity
(18:38) Metanormative bracketing
(19:35) Setup
(26:48) Does metanormative bracketing have an individuation problem?
(30:49) A full metanormative bracketing choice rule
(32:06) Step 1: Ruling out the worst options
(34:25) Step 2: Stakes-sensitively ranking the remaining options
(36:26) Summary of the choice rule
(37:29) Why metanormative bracketing avoids radical cluelessness
(40:11) Implications of metanormative bracketing
(40:29) Cluelessness and cause prioritization
(41:53) On arbitrariness and neartermism vs. longtermism
(48:29) Other potential implications to explore
(52:04) Acknowledgments
(52:30) Appendix: Example where metanormative bracketing is sensitive to individuation of normative views
(55:59) References
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Last year, GiveWell revised its estimate of our cost-effectiveness, rating our work 3–4x higher than before. That shift was driven in part by evidence on how cash transfers affect local economies. In this post, we break down that evidence, explaining how cash boosts local economies.
Summary
One of the world's largest cash studies found that GiveDirectly's program, giving a one-time $1,000 cash transfer to 10,500 poor households in rural Kenya, led to 2.5x that amount in economic growth.
Now, we’re building on these results to launch the world's biggest randomized controlled trial on cash, and asking even bigger questions [...]
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Outline:
(01:25) Cash boosted the local economy because families spent close to home
(02:21) 🤝 Neighbors who didn't get cash also earned more and lived better as businesses grew
(02:55) Every $1 delivered as cash grew the local economy by $2.50
(03:36) 📈 Click to read how the multiplier is calculated
(04:37) Cash caused nearly no inflation because businesses already had room to grow
(06:10) 💡 Researchers credit this low inflation to slack in the local economy
(07:19) Next we're testing if cash can transform entire regional economies
(07:55) 🔎 Growth in Kenya beat predictions; the Malawi study will test how far markets can stretch
(08:29) Malawi will show us just how far cash can go
(10:22) Additional commentary
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Hi everyone, Zershaaneh here!
Earlier this year, 80,000 Hours published an article explaining the risks of power-seeking AI.
This post includes some context, the summary from the article, and the table of contents with links to each section. (I thought this would be easier to navigate than if we just reposted the full article here!)
ContextThis is meant to be a detailed, introductory resource for understanding how advanced AI could disempower humanity and what people can do to stop it.
It replaces our 2022 article on the existential risks from AI, which highlighted misaligned power-seeking as our main concern but didn't focus entirely on it.
The original article made a mostly theoretical case for power-seeking risk — but the new one actually draws together recent empirical evidence which suggests AIs might develop goals we wouldn’t like, undermine humanity to achieve them, and avoid detection along the way.
What [...]---
Outline:
(00:35) Context
(01:11) What else is new?
(01:31) Why are we posting this here?
(02:15) Summary (from the article)
(03:09) Our overall view
(03:13) Recommended -- highest priority
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TL;DR: I took the 🔸10% Pledge in 2016 and haven’t kept to it consistently. I’ve decided not to pay the backlog donations, and instead to recommit fresh from today, with simple systems to keep me on track. Sharing this for transparency and in the hope it may be helpful to others
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Why I’m posting
In 2016, as a university student, I took the Giving What We Can 10% Pledge. I made my pledge publicly, and my social media profiles show the 🔸10% Pledge badge. For integrity's sake, I want to be equally public that I fell short—and [...]
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Outline:
(00:29) Why I'm posting
(00:52) What happened
(01:53) Going forward
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Improving the welfare of farmed fish is probably some of the most cost-effective near-term suffering reduction work the EA community engages in.
To celebrate the EA community's amazing work for trillions of fish around the globe, here's a list of ten surprising fish behaviors and capabilities! Hopefully this list will help you/others appreciate the diversity, intelligence, and sentience of fish. Many of these examples are drawn from the excellent book on fish intelligence, What a Fish Knows by Jonathan Balcombe. Enjoy!
1. White-spotted pufferfish spend many hours constructing and maintaining their circular nests.
2. Fish's lack of hands means they are more limited in their tool use. Here, a blackspot tuskfish on the Great Barrier Reef uses a rock as an anvil to bash open a clam.
3. It is not known why mobula rays leap above the water. Some [...]
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By Ben Wilson and John Bash from Metaculus
Main Takeaways
Top Findings
Other Takeaways
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Outline:
(00:20) Main Takeaways
(03:24) Introduction
(04:30) Methodology
(13:59) How do LLMs Compare?
(17:18) Which Bot Strategy is Best?
(23:04) Are Bots Better than Human Pros?
(25:38) Binary vs Numeric vs Multiple Choice Questions
(27:07) Team Performance Over Quarters
(31:14) Bot Maker Survey
(31:40) Best practices of the best-performing bots
(38:27) Other Survey Results
(41:32) How did scaffolding do?
(45:33) Advice from Bot Makers
(53:48) Links to Code and Data
(54:56) Future AI Benchmarking Tournaments
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https://www.metaculus.com/notebooks/40456/q2-ai-benchmark-results/
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In August we launched a redesign of the EA Funds website. The main goal was to improve overall perception and make the site feel modern, trustworthy, and more consistent with the effectivealtruism.org brand. We also wanted to aim the site more towards donors, increase transparency around grantmaking and evaluation, and improve overall usability.
View the EA Funds websiteWe've been making incremental improvements since launch and will continue to do so.
The update includes:
A closer look at the changes
A key focus for EA Funds [...]
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Outline:
(02:15) A closer look at the changes
(02:32) Critiquing the old site
(03:18) Explaining the changes
(03:59) Early results
(04:22) Future work
(04:40) Share your thoughts
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