Being a freshman at university, I seem to have been bestowed the great privilege of infinite possibilities. There is this strange feeling of trying to plan a career in a world that might not exist in five years. Not in a doomer sense but that the world of 2031 might be so radically different from today that most attempts of planning are incoherent. I contemplate machine god super intelligence arriving before I graduate, intelligence explosions compressing 10,000 years of progress into one, the possibility of being among the last humans to die before death itself is solved; then I do my laundry and pick electives. I am surprised I am not entirely losing my mind.

Robin Hanson writes, in 2009, This is The Dream Time:

Perhaps most important, our descendants may remember how history hung by a precarious thread on a few crucial coordination choices that our highly integrated rapidly changing world did or might have allowed us to achieve, and the strange delusions that influenced such choices. These choices might have been about global warming, rampaging robots, nuclear weapons, bioterror, etc. Our delusions may have led us to do something quite wonderful, or quite [...]

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https://carolannejiang.substack.com/p/planning-80000-hours-at-the-plausible

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TLDR: We built Beeminder for effective charities. Access it here.

Commitment Contracts don't work with effective charities

Commitment Contracts are simple: You commit to pay money if you don't do something. Then, when you don't do the thing, you pay the company offering these contracts. This hurts, and that's why it works.

Commitment Contracts are surprisingly effective for behaviour change: A large-scale study from stikK showed that contracts with money staked are 60 percentage points more likely to succeed.

That's why there are plenty of organisations offering commitment contracts already: Beeminder, stickK, and forefeit. However, they either take the staked money or donate it to a portfolio of average NGOs.

We built an app that fixes that

We developed an app that applies this concept but donates the staked money to effective charities. It takes two minutes to set up and works in your browser and on your phone.

Worried that it'll be less effective that way? You're right. It'll "hurt less" than donating the money to the NRA. But that's easy to fix. Just stake more money, and it'll hurt just the same.

Not sure that's the best way to change behaviour? You're right again. Check out our [...]

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Outline:

(00:30) Commitment Contracts dont work with effective charities

(01:14) We built an app that fixes that

(01:56) Give it a try

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This is a contribution to AGI & Animals Debate Week (March 23–29, 2026). Co-written with Claude and ChatGPT.

Summary: It seems reasonable to think that there's a >20% chance[1] that TAI will bring us a ‘technological roadmap’[2] to clean meat within the next 15 years. A simple model: such a roadmap won’t solve the problem, but it will make ending factory farming much easier, i.e. the cost-effectiveness of factory farming interventions will increase – perhaps by a factor of 2-10x. The movement should therefore be investing instead of deploying, focusing on capacity-building, research, and literal investment of money. It may also be cost-effective to act now on some ways of removing barriers to the eventual adoption of clean meat (e.g. ensuring clean meat can be halal-certified at scale).

I will argue:

1. AI-driven R&D will likely deliver a ‘technological roadmap’ [1] to clean meat within the next 15 years or so.
2. However, this won’t end factory farming by itself – and some barriers can be worked on now.
3. More broadly, we should be anticipating a stark increase in cost-effectiveness, so we should move into an ‘investment mode’.

At the end, I’ll provide some specific ideas about useful work (e.g. working with [...]

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Outline:

(01:41) 1. AI-driven R&D will likely deliver a technological roadmap to clean meat

(03:38) 2. However, this wont end factory farming by itself - and some barriers can be worked on now

(05:49) 3. The movement should move into an investment mode

(07:42) 4. Some specific ideas

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The text of the bill can be found here. It begins by citing the warnings of AI company CEOs and deep learning pioneers Geoffrey Hinton and Yoshua Bengio, as well as the 2023 FLI open letter calling for a 6-month pause. The bill would prohibits the construction or upgrading of AI datacenters until Congress pass an AI safety law aimed at preventing AI companies "from releasing harmful products into the world that threaten the health and well-being of working families, our privacy and civil rights, and the future of humanity". It would also impose export controls for advanced chips to any country "to any country or entity that does not have laws and regulations in place to protect humanity from AI safety concerns and existential risks, protect workers, and protect the environment". Sen. Sanders and Rep. Ocasio-Cortez announced the bill in a live press conference:

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The Community Building Grants (CBG) program, run by the Groups team at CEA since 2018, is undergoing substantial changes.

Through the CBG program, we fund a set of professional city and national EA groups[1] and support their leaders through retreats, regular check-ins and calls, a Slack space, and resources for running groups.

CBG groups have achieved exciting things, such as helping EAs navigate (policy) hubs, supporting hundreds of community members in taking next steps, and incubating new organisations.

In this post, we want to share what's changing and the reasoning behind it. In 2026, two things are changing:

• CBG grant evaluation is moving from the Groups team to EA Funds (which became part of CEA in the summer of 2025), where it will be managed alongside, but remain distinct from, the EA Infrastructure Fund. 
• CBG non-monetary support has been transitioned, integrated with other offers, or phased out.

Why we are making these changes

In 2025, we reviewed how the CBG program fits into CEA's broader strategy. As CEA aims to reach and raise EA's ceiling, we are shifting internal focus more towards scalable products that can support this ambition. After a long strategic process, we concluded that [...]

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Outline:

(01:15) Why we are making these changes

(03:01) Whats changing

(05:11) What has not changed

(06:23) Trade-offs

(07:42) Finally

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This post was inspired by debate week, but I also published it to my Substack. There, most of my readers are not as familiar with EA discourse, so I added a long introduction which I haven’t copied here (but which you might find entertaining). There's also a voiceover of the full version available on Substack or in any podcast feed if you search “Sandcastles”.

1. The heart of the matter

There's a debate taking place on the EA forum this week. The motion is:

If AGI goes well for humans, it’ll probably (>70% likelihood) go well for animals.

Taken literally, this could leave a 30% chance of AI going catastrophically bad for animals even if it went well for humans– think factory farms orbiting space colonies.

Many people working frantically on AI alignment agree with the statement “If AGI takes off hard and fast, it will probably (>70% likelihood) go well for humans.” 30% is still a terrifyingly high chance of disaster, more than enough to throw out everything else and focus on averting it.

Multiplying these two .7s gets us to .49, i.e. a less than 50% chance of AI going well for animals. But I don’t think [...]

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Outline:

(00:35) 1. The heart of the matter

(03:25) 2. The make AI go well movement

(05:53) 3. AW and GHD are part of MAIGW

(07:29) 4. A new hope

(08:57) 5. How to be a TAI-focused AW movement

(11:39) 6. Raising an animal-friendly god 🚨 \*CRUX ALERT\*

(20:03) 7. How to be an animal-friendly Make AI Go Well movement

(24:34) 8. Family reunion

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Cross-posted from my website.

Epistemic status: Speculating with no central thesis. This post is less of an argument and more of a meditation.

A decade ago, before there was a visible path to AGI and before AI alignment was a significant research field, I figured the solution to the alignment problem would look something like Coherent Extrapolated Volition. I figured we'd find a way to get the AI to internalize human values. I had problems with this approach (why only human values?), but I still felt reasonably confident that the coherent extrapolation of human values would include concern for the welfare of all sentient beings. The CEV-aligned AI would recognize that factory farming is wrong, and that wild animal suffering is a big problem.

Today, the dominant research paradigms in AI alignment have nothing to do with CEV, and I don't know what to think.

Regarding the promisingness of today's popular research paradigms, my beliefs are aligned (heh) with those of most MIRI researchers: namely, I don't think they have promise. For example, see On how various plans miss the hard bits of the alignment challenge by Nate Soares. I'm not an alignment researcher, but [...]

The original text contained 8 footnotes which were omitted from this narration.

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Summary

In many worlds, but not all

- If AGI is widely available, alt protein advocates could direct it themselves and prioritization is not an issue.

- If AGI capability is concentrated in governments and companies, cultivated meat competes with other issues like cancer, climate, and national security.

- An autonomous AGI reasoning from first principles might prioritize it, but animal welfare is underrepresented in alignment frameworks—there is not yet a strong basis for assuming it would.

Very Likely

- Current AI tools are already highly capable of solving biological problems. AGI would likely be able to solve remaining scientific questions in cultivated meat.

- The science of scaling would also likely be handled well by AGI

- The data scarcity problem in alt proteins may be less of an issue with powerful, generalisable AGI.

Likely

- AGI could optimize facility design, supply chains, and input costs, improving economics and attracting private capital.

- Physically building out an industry that barely exists takes time regardless of how good the designs are, but this may not meaningfully slow deployment.

Lean no

- AGI can [...]

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Outline:

(00:13) Summary

(01:06) Intro

(02:18) For AGI to solve cultivated meat, all of the following must hold

(02:24) Cultivated meat (or animal welfare) is prioritized

(05:18) The remaining science is solved

(07:15) Manufacturing scales affordably

(09:29) Regulators speed up, maybe by adopting AI

(13:07) Political opposition reverses

(15:21) Consumers accept cultivated meat

(18:43) All of the above happen in coordination, on a timeline that matters for animals

(20:54) Caveats:

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Epistemic status: medium, unsure if this is biased to what I have experienced, but think it is useful regardless.

I think that organisations and individuals should try be more transparent about their capacity, e.g. at conferences when people ask for volunteering / collaboration opportunities, a lot of orgs/individuals say yes, and then nothing ever really happens.

For example, some members from EA Bath attended EAGx Amsterdam last year. One of my members was pretty excited about EA and using his skills to help in climate change / GHD. He met with a lot of people who offered him opportunities and collaboration, so he followed up with them all after the conference, but it resulted in them all ghosting him, which lead to him being less sure that EAG/ EAGx's were a good use of his time. I've had similar experiences too, with asking people if they have opportunities and them saying yes, and then I receive no reply when I email them.

I think that these people / organisations are genuinely excited for more people like me (students / entry-level) to get involved, but are also probably time constrained. Because of this I think it's super important that [...]

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TL;DR

I spent eight months as a community builder for an EA group. This is a reflection on what that work actually looks from the inside, why I’ve found it's structurally undersupported, and what I think could be different for funders, organisations, and for community builders themselves.

What community builders actually do

From the outside, community building can look deceptively simple. Organising events, running fellowships, hosting discussions. And yes, those things are part of it. But most of the actual work happens in the spaces between. The one-on-one conversation with someone trying to figure out how they want to contribute. The introduction you make between two people who probably should've met a year ago. The moment someone finally feels comfortable asking the question they've been sitting with for months because the room feels safe enough.

These things don't show up cleanly in metrics. But they tend to be the moments that actually shape people's trajectories.

If you think about how someone typically moves toward an impact-focused career or project, it rarely happens in one step. There's an initial spark, be it through an event, an article, or even a conversation. Then, there's deeper engagement. After that, usually what comes [...]

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Outline:

(00:13) TL;DR

(00:33) What community builders actually do

(02:03) The call that made me write this

(03:17) The strange place community building holds

(04:41) What doesnt show up in a grant application

(07:12) Whats actually broken, and what could be different

(11:08) Communities arent background noise

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