The AI wealth boom and the absorption problem


Unless you’ve been hiding under a rock—or sunning yourself on a beach—you’ve probably seen Nan Ransohoff’s piece. She does the napkin math and estimates that AI wealth could generate another $37–100 billion in annual philanthropic giving. Given the track record of stuff like the Giving Pledge, we wouldn’t bet the farm on those numbers, but by any measure there’s going to be a lot of new money looking to fund impact. If you haven’t read her piece, it’s worth doing.
A flood of new money sounds great. Nick Allardice, CEO of GiveDirectly, worries that the flood could swamp the field: there aren’t nearly enough organizations built to turn that much more money into that much more impact. If he’s right, doers – it pays to have plans with what you’ll do with a really big check. Super thoughtful, well-informed and a good read—agree or disagree, it’s a really important piece.

To beat the flood metaphor to death, Mulago cares about where the water goes even more than the surge itself. Ben Hyman of the Africa Jobs Fund has a lot of useful thoughts about what might go to Africa and what might best be done with it. We loved this sentence the most: “The best philanthropy takes advantage of its greater flexibility relative to institutional funding to ensure it has a catalytic effect.”

In a collaboration with Mulago portfolio organization Taleemabad, Kevin went to the mountains in Pakistan to teach the Mulago impact-at-scale curriculum to a crew of awesome Pakistani founders. He wrote this about it on LinkedIn:
“Pakistan is a nuclear power. It also has a GDP per capita that is only two-thirds of Kenya’s, a maternal mortality rate 50% higher than Tanzania, and a literacy rate much lower than Zambia’s. However, its government has a remarkable ability to get things done—and fund them—when it chooses, and there is a rising generation of social entrepreneurs with the ideas and the chops to deliver. This country represents an enormous opportunity for funders.”
If a flood of AI money does emerge, impact evidence will be that much more important. RCTs are called the gold standard of impact evidence. Lennart Finke argues that better data, better methods, and faster computers have made observational evidence far more useful, and certainly more useful than many researchers admit.
We’re neither statisticians nor economists, and it’s riled plenty of them. But funders and doers do need better—cheaper and easier—ways to evaluate impact, and Lennart’s (very readable) case for taking observational evidence more seriously is an important contribution.

The bank robber Willie Sutton was asked "Why do you rob banks?”. His answer: “Because that’s where the money is.” In Africa, cities are where the opportunities are, and that’s where people are going. Within a generation, urban Africans will outnumber rural Africans.
Planning now (which means funding good planning ideas) can make the difference between cities that suck for most people and cities that provide opportunity for all. The Economist quotes one of our newest Fellows Patrick Lamson-Hall, whose big idea is simple: get the right roads in place before cities grow.
We’ve written a lot about the end of Big Aid. This interview with Atul Gawande makes sure we don’t look away from the brutal, callous, and avoidable human cost of how it ended.

Joe Studwell wrote the highly regarded book “How Asia Works” about how countries there became prosperous. The first step was to crank up agricultural productivity focused on exports. In our last Links, we talked about his new book “How Africa Works,” which makes a similar case for Africa.
Hmmm. So at Mulago, we’ve observed that 1) African farms are too small, 2) most farmers don’t want to be farmers, and 3) most don’t have access to markets. This piece in the latest Economist seems to agree, and that doesn’t bode well for Africa’s prospects. (FWIW, some of our newest Fellows do have solutions that address precisely these problems…).

This comes from a great piece by Esben Brandi on why the trillion-dollar figures that anchor the nature-finance conversation don’t measure what you think they measure — and how they make both good policy and good investing that much harder.
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