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I wrote this aimed at audiences who aren't already familiar with the idea of effective giving or pledging. Also posted at juliawise.net and Substack.

Takeaways:

  • The world has a lot of appalling problems. Many can’t be addressed very well with money, but some can.
  • On a rich-country income, you almost surely have some income you could dedicate to making the world better in whatever way seems best to you.
  • This is best done not impulsively and sporadically, but deliberately as part of your ongoing budget.
  • Donating a fraction of your income is a pretty great opportunity to make the world more like what you want it to be: with less suffering, more progress, more fairness, or whatever seems best to you.
  • You don’t have to agree with my choice of where to donate! Think it through yourself!
  • My ask to you for the coming year: think seriously about how much you want to give, and where you want to give it. One tool that I recommend is making a pledge (either for a period of time, or ongoing).

The world still has a lot of little match girls

[content: fictional and statistical child death, this section only]

Yesterday I took my daughter to see her friend in a Christmas performance based in part on Hans Christian Andersen’s story The Little Match Girl. I figured a family Christmas play would probably alter the part where the main character freezes to death, but no. I sobbed messily while the plot moved on.

The 1844 story is about a child dying from poverty in the streets of a major European city. That was common then; all rich countries were much poorer then. 

But in today’s world, millions of children (expected to rise this year after aid cuts) still die every year from preventable causes like malaria, diarrhea, and pneumonia. Those dying from extreme poverty aren’t in Copenhagen now, and they’re not in Boston where we paid $75 to watch the play. They’re out of sight, out of mind to us here.

……..

I take very seriously that I have the power to prevent other families from losing their children. This is a huge deal. For about $3,000, you can expect to save a parent from watching their child die from malaria. (Why this much, when treatment only costs a few dollars? Because most treatments won’t prevent a death, just like most vaccines. But it’s worth it to protect all the most vulnerable people, and to prevent a lot of nonfatal sickness.)

I don’t have words for how messed up it is that there are still so many preventable deaths. A world that had its act together would have fixed this by now.

The world clearly does not have its act together.

You don’t have to think global health is the best area

Donations let you make a dent in big problems, whether or not you also contribute in other ways. You can do that in lots of areas, if global health isn’t what seems most important to you:

  • Maybe there are systemic changes you think are better to support.
  • Maybe you think economic growth is more important, since it’s behind so many other improvements.
  • Maybe you’d rather support developing new solutions instead of rolling out existing ones.
  • Maybe there’s another population you think will benefit more from help.
  • Maybe you want to try to prevent future problems (this is where Jeff and I are doing most of our giving this year).

If you take a hard look, you’ll also see many things you’d like to donate to that are not the most important ones. I think of those as candidates for a “have a good life in my community” budget (which is a totally valid thing to budget for!) but not a “change the world” budget.

You can afford to change things

If you’re reading this, you’re probably much richer than the typical person in the world. By living a bit more below your income, you can empower a cause you care about. As you think about your budget for the coming year, make a plan to set aside a meaningful amount to make the world more like what you want to see. (“Meaningful” will vary a lot by budget, but 10% is one longstanding method.)

Please give it a try. 

Some places to get started

If you’re interested in recommendations from the effective altruism space:

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An underexplored alternative to donation is hiring people from low-income contexts to do paid work on meaningful problems.

Here's a rough estimate of "happy" hourly rates for remote intellectual manual labor (data labeling, checking, summarization, interpretability grunt work), in USD:

Estimated Happy Rates ($/h)

Country p25 p50 p75
Brazil 2.35 3.35 4.69
Argentina 2.11 3.02 4.23
Colombia 3.93 5.61 7.85
Peru 2.38 3.40 4.75
Chile 4.75 6.79 9.50
Bolivia 1.70 2.45 3.40
Paraguay 2.05 2.95 4.10
Ecuador 2.70 3.85 5.40
Mexico 2.90 4.10 5.80
Nigeria 0.70 0.99 1.39
Ghana 0.63 0.90 1.26
Kenya 1.24 1.77 2.48
Uganda 0.55 0.80 1.15
Tanzania 0.60 0.88 1.25
South Africa 2.07 2.96 4.14
Egypt 1.46 2.09 2.92
Morocco 1.85 2.65 3.70
Tunisia 1.95 2.80 3.90
India 0.95 1.40 2.10
Bangladesh 0.55 0.80 1.20
Pakistan 0.65 0.95 1.40
Sri Lanka 0.85 1.25 1.85
Vietnam 1.35 1.95 2.80
Philippines 1.60 2.30 3.30
Indonesia 1.10 1.60 2.40
Thailand 2.10 3.00 4.30
Malaysia 2.60 3.70 5.30
Nepal 0.60 0.88 1.30
Cambodia 0.75 1.10 1.60
Mongolia 1.10 1.60 2.30
Fiji 2.40 3.40 4.90
Samoa 2.10 3.00 4.30
Tonga 2.20 3.10 4.50

There exists a very large supply of people who are both willing and happy to do careful cognitive work at rates that are trivial by rich-country standards, if the work is structured and paid.

Some reasons this possibility can be quite good and interesting:

  • It allows money to be converted into actual work on impactful tasks, even if that work is initially "intellectual manual labor" (labeling, checking, summarizing, auditing, interpretability grunt work, etc.).
  • It treats people as participants rather than recipients. Receiving payment for work tends to be more humanizing than receiving aid, because it encodes agency, skill, reciprocity, and contribution.
  • It onboards people into the global intellectual labor market: deadlines, quality standards, tooling, communication norms. Those skills compound and transfer.
  • It can operate without heavy intermediary organizations, which reduces overhead and incentive distortion and keeps the causal chain legible: money → work → output → learning.

A lot of important research and analysis is not bottlenecked on genius so much as on coordination, paradigms, and tooling. Once those exist, large amounts of careful human attention can be usefully applied in parallel.

My usual joke is "GPT-2 has 12 attention heads per layer and 48 layers. If we had 50 interns and gave them each a different attention head every day, we'd have an intern-day of analysis of each attention head in 11 days."

This is bottlenecked on various things:

  • having a good operationalization of what it means to interpret an attention head, and having some way to do quality analysis of explanations produced by the interns. This could also be phrased as "having more of a paradigm for interpretability work".
  • having organizational structures that would make this work
  • building various interpretability tools to make it so that it's relatively easy to do this work

Buck's comment on "How might a herd of interns help with AI or biosecurity research tasks/questions?", EA Forum

I think there are real downsides of mixing unrelated goals (in this case: improving livelihoods/skills for educated people in LMICs, and getting work done). 

  • remote work requires people who already have computer access, reliable internet, professional skills, and proficient English (or whatever language you need). So these are people who are already relatively well-off in their setting.
  • management capacity is often a bottleneck, so rather than onboarding people to things like deadlines and quality standards, for the sake of getting the work done efficiently you might rather pay a higher rate to get someone who doesn't need as much hand-holding. (Maybe this isn't relevant if the work you want done isn't itself aiming at a positive impact, and you're ok with your widget business running less efficiently in order to offer a jobs program.)

    If you have needs that can be met just as well by remote workers in LMICs, seems great! But I wouldn't start with the premise that this is your best option for improving the world.

I agree this cannot replace donation-based interventions! It is still feels potentially underrated and underconsidered.

I do agree that management and structure are the hardest parts. I do imagine many EA orgs have solved harder problems in the past.

I think automatic dubbing services have become good enough to make English fluency not be a hard requirement anymore for many potential jobs.

Here is a super hacky fermi-gpt estimate of a headcount of potentially hireable global workers:

"""

hacky fermi estimate — internet users → elite tail

definitions (clean + explicit):

  • population: total population (≈2024–2025)
  • internet users: people using the internet (any device)
  • final pool (÷8000): internet users filtered by three independent 95th-percentile criteria
    • high cognitive ability (≈95th percentile)
    • hardworking (≈95th percentile)
    • ethical / trustworthy (≈95th percentile)
      combined ⇒ (1 / (20×20×20) ≈ 1 / 8000)

interpretation: this is a very conservative lower bound on people who could plausibly do high-quality remote cognitive work using tools like chatgpt (incl. translation). this is not a hiring claim; it’s an order-of-magnitude sanity check.


hacky fermi table

country population internet users final pool (÷8000)
brazil 203,000,000 170,520,000 21,315
argentina 46,000,000 41,400,000 5,175
colombia 52,000,000 40,040,000 5,005
peru 34,000,000 24,480,000 3,060
chile 19,500,000 17,940,000 2,243
bolivia 12,400,000 7,440,000 930
paraguay 7,500,000 5,850,000 731
ecuador 18,300,000 13,725,000 1,716
mexico 129,000,000 96,750,000 12,094
nigeria 227,000,000 88,530,000 11,066
ghana 34,000,000 18,020,000 2,253
kenya 55,000,000 23,650,000 2,956
uganda 49,000,000 14,210,000 1,776
tanzania 67,000,000 20,100,000 2,513
south africa 62,000,000 44,640,000 5,580
egypt 112,000,000 80,640,000 10,080
morocco 37,000,000 31,080,000 3,885
tunisia 12,300,000 8,733,000 1,092
india 1,430,000,000 800,800,000 100,100
bangladesh 173,000,000 70,930,000 8,866
pakistan 241,000,000 86,760,000 10,845
sri lanka 22,000,000 11,880,000 1,485
vietnam 101,000,000 75,750,000 9,469
philippines 114,000,000 83,220,000 10,403
indonesia 277,000,000 182,820,000 22,853
thailand 71,000,000 60,350,000 7,544
malaysia 34,000,000 32,980,000 4,123
nepal 30,500,000 13,420,000 1,678
cambodia 17,000,000 9,520,000 1,190
mongolia 3,500,000 2,905,000 363
fiji 930,000 697,500 87
samoa 225,000 157,500 20
tonga 107,000 74,900 9

key takeaway:
even after filtering to internet users only and then applying an extremely harsh 95%×95%×95% filter, many countries still have thousands to tens of thousands of plausible high-quality contributors. at global scale, talent supply is not the bottleneck; coordination, tooling, and trust are.

"""

(I know this estimation relies on some independence assumptions. Regardless, it is meant to be illustrative, not authoritative.)

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