I’m an independent researcher working on various projects in cause prioritization and global conflict research.
Previously I’ve been a Research Fellow at the Forethought Foundation, where I worked on What We Owe The Future with Will MacAskill; an Applied Researcher at Founders Pledge; and a Program Analyst for UNDP.
As an example of how powerful these demographic shifts will be, this recent paper claims that ~all of Japan’s poor economic performance relative to other developed nations since the ’90s can be explained by its demographic shift (specifically the decline in the population share of working age adults). Think about how much consternation there has been about Japan’s slow growth. We’re all headed that way.
Interestingly, AFAIK Japan has not drastically liberalized its immigration much in response to its slow growth. The proportion of foreign-born residents has grown a bit, but not much. Maybe this is changing, but we’ll see if anything actually happens, and Japan has been struggling to grow for decades.
I think both of these trends can occur simultaneously
I’m not sure it’s very helpful to think of this as “jobs moving from one country to another”. It makes it seem zero-sum, whereas it is actually a positive-sum efficiency gain
Migrants to higher-income countries benefit from public goods like better services and public safety in addition to higher incomes
As Lant has pointed out, the higher income someone gains from moving from a low- to high-income country is enormous. IIRC it can be something like a 10x increase in consumption even if they’re working the same job. So even if we imagine some fixed pool of jobs, I’m not sure it is “far better” for jobs to move from high- to low-income countries. Given the choice of working the same job in a high-income or a low-income country, I think many people would choose to move to the high-income country.
Great post, Tom, thanks for writing!
One thought is that a GCR framing isn’t the only alternative to longtermism. We could also talk about caring for future generations.
This has fewer of the problems you point out (e.g. differentiates between recoverable global catastrophes and existential catastrophes). To me, it has warm, positive associations. And it’s pluralistic, connected to indigenous worldviews and environmentalist rhetoric.
I loved Chris Miller’s Chip War.
If you’re looking for something less directly related to things like AI, I like Siddhartha Mukerjee’s books (The Emperor of all Maladies, The Gene), Charles C. Mann’s The Wizard and the Prophet, and Andrew Roberts’ Napoleon the Great
What a sweet post 💙
Thank you also to you for setting up Vida Plena! By putting so much work into setting up a new organization you’ve helped a lot of people.
Ranil Dissanayake actually just published an article in Asterisk about the history of the poverty line concept. The dollar-a-day (now $1.25 a day or something) line was kind of arbitrary and kind of not:
rather than make their own judgment on what constituted sufficient living, they could instead rely on the judgment of poor countries themselves. They would simply take an average of the poorest countries in the world and declare this to be the global minimum of human sufficiency
noting further in a footnote that
Of course, things are never quite so pure: The bank was closely involved in the development of national poverty lines around the world, so there was some element of circularity to the development of the global line.
The whole article is very interesting, worth a read for people in this space.
Great comment, I appreciate this perspective and have definitely updated towards thinking the 10x gap is more explainable than I thought.
I do note that some of the examples you gave still leave me wondering if the families would rather just have the cash. Sure, perhaps it would be spent on high-priority and perhaps social signal-y things like weddings. But if they can’t currently afford to send all their kids to school or other medical treatment, I wonder if they’d sensibly rather have the cash to spend on those things than a bednet.
(Also, my understanding from surveys of cash recipients is that most do spend their money on essentials or investments.)
Sorry, yep, I meant to add an “annually” there!
I’m somewhat sympathetic to something like GiveDirectly’s take. If bednets are something like 10x more valuable than the cash used to purchase them, I find it a bit weird that people don’t usually buy them when given a cash transfer.
I’ve previously written a short comment about mechanisms that could explain this and do think there are important factors that can explain part of the gap (e.g. coordination problems). But I’m still a bit skeptical that the “real” value is 10x different.
I suppose we could straightforwardly just transfer enough cash to everyone below a certain poverty line until their annual income is above it. The Longview team has estimated this would cost about $258 billion [edit: annually] (pp. 8-10 here).
a lot of my confidence in the above comes from farmed animal welfare strictly dominating GiveWell in terms of any plausibly relevant criteria save for maybe PR
Well some people might have ethical views or moral weights that are extremely favourable to people-focused interventions.
Or people could really value certainty of impact, and the evidence base could lead them to be much more confident that marginal donations to GiveWell charities have a counterfactual impact than marginal donations to animal welfare advocacy orgs.
FWIW I’m more likely to donate to animal welfare orgs too, but I’m sufficiently uncertain that I wouldn’t say I believe they dominate the GW orgs on relevant criteria. That would be pretty surprising, they’re very different in their goals and approach!
Asssume “Philanthropy to the Right-of-Boom” is a roaring success (say, a 95th-percentile good outcome for that report). In a few years, how does the world look different? (Pick any number of years you’d like!)
I first got interested in civilizational collapse and global catastrophic risks by working on a Maya archaeological excavation in Guatemala.
I didn’t know this, and it’s awesome.
What did your work on the Mayans teach you about civilizational collapse?
I’m curious who you’ve seen recommending starting with Mearsheimer? That seems like an unbalanced starting point to me.
I’d personally recommend a textbook, like an older edition of World Politics.
Thanks for writing this. I think a lot of it is pointing at something important. I broadly agree that (1) much of the current AI governance and safety chat too swiftly assumes an us-v-them framing, and that (2) talking about countries as actors obscures a huge amount of complexity and internal debate.
On (2), I think this tendency leads to analysis that assumes more coordination among governments, companies, and individuals in other countries than is warranted. When people talk about “the US” taking some action, readers of this Forum are much more likely to be aware of the nuance this ignores (e.g. that some policy may have emerged from much debate and compromise among different government agencies, political parties, or ideological factions). We’re less likely to consider such nuances when people talk about “China” doing something.
That said, I think your claim that governments don’t influence AI development [via semiconductor progress] is too strong. For example, this sentence:
It seems plain that nations are not currently meaningful players in AI development and deployment, absent conspiracy-level secrecy.
seems likely wrong to me. The phrasing (“it seems plain”) also suggests to me that you should be somewhat less confident in your views on these issues overall.
Some examples of government being meaningful players:
The US government potentially kneecapping Chinese AI development by putting in place harsh export controls on semiconductor products and software
There are large public subsidies for chip companies (potentially up to $150 billion for Chinese semiconductor companies)
More generally, governments will have a lot of influence over domestic companies by deciding what kinds of regulations they’ll be subject to
There are also historical examples of government action shaping outcomes in the semiconductor (and therefore AI space).
For example, early demand for semiconductors was driven by the US government’s military and space program. And TSMC got started when the Taiwanese administration invited Morris Chang to start a semiconductor company in Taiwan (and provided half his start up funding) (source: I read this in Chip War, and that take is summarized on the Wikipedia page).
You write also that “Google and Microsoft really care about each other’s chip access in a way that they only do to a weaker degree about Alibaba’s.” That may be true, I don’t really know. But I’m pretty confident that the US government does care a lot about whether Google or Alibaba have access to more chips. Hence the export controls, subsidies, and regulations discussed above.
I disagree fwiw. The benefits of transparency seem real but ultimately relatively small to me, whereas there could be strong personal reasons for some people to decline to publicise their participation.
More country-specific content could be really interesting. I’d be interested in broad interviews covering:
China—economic projections, expert views and disagreement on stability of CCP, tech progress, info on public opinion about US/West, demographic challenges, entrepreneurship, etc. (not sure he’d be the best person to cover all this, but maybe Kaiser Kuo?)
India—whether high growth rates can be sustained, Sino-Indian relations, complexity of India’s diplomatic relationships with Russia and US, challenges and stability of world’s largest democracy, intra-country variation in culture and economic structure, Indian human capital and tech talent + plausibility of India becoming an AI power in next few decades
Same for other emerging powers—maybe Nigeria and Indonesia
A whole episode on semiconductors and supply chains, including role of countries like South Korea, Japan, and Singapore
Thank you for sharing!
Interesting, thanks for checking that!
What I had in mind were the data from this Pritchett paper. He sets out a range of estimates depending on what exactly you measure. For example he shows that the US wage for construction work is 10x the median of the poorest 30 countries (p. 5). The income gains for a low skill worker moving to the US vary depending on where they’re coming from, but range from 2.4x (Thailand) to 16x (Nigeria) (p. 4).
That’s pretty different than the paper you cite. I’m not sure what accounts for that right now. Hopefully we see more work in this area!