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.)
Somewhat related: https://x.com/i/status/2021218105154756893