I run the Centre for Exploratory Altruism Research (CEARCH), a cause prioritization research and grantmaking organization.
Joel Tan🔸
Karma: 1,841
Hey Ozzie—the MCF runs biannual grant rounds, and this round also seems to have moved less than the average so far (e.g. see the winter 2023 round which moved about 700k and summer 2024 which moved 2m). In general, I would expect the average annual amount moved to be higher than what was granted this time, but Joey would know more than me.
I know a couple of MCF members, and I understand some are “2nd tier” members—they have access to the applications but I’m not sure if they commit to the annual 100k. @Joey ?
Thanks for the thoughts!
(1) I’m in strong agreement with worries over people leaving/disengaging from EA due to applying for a huge number of jobs and getting disillusioned when not landing any. From my conversations with various EAs, this seems a genuine problem, and there are probably structural reasons for this: (a) the current EA job market (demand > supply); and (b) selection effects in terms of who gives advice (by definition, us EA folks at EA organizations giving advice on EA jobs, have been successful in landing a direct EA job, and may underrate the difficulties of doing so).
(2) On whether the average early career EA should try for E2G—I’m not sure about this. It’s true that they’ve been selected for, but they’re still fundamentally at a big disadvantage in terms of experience, and I’m seriously worried about a lot of selection into low career-capital but nominally EA roles that disadvantage them later on, both in terms of impact and financial security.
In any case, at EAGx Singapore last weekend, I did a talk to a crowd of mainly these early career EAs on having impact with and without an EA career, and I basically pitched trying for an EA job but also seriously considering impact by effective giving in a non-EA job as a Plan B. I think it’s especially relevant for LMIC EAs, who cannot move to the UK/US for high-impact roles (or find it harder to do so).
Hi Alex. It’s a great idea to have this AMA! Hopefully it helps raise more awareness of earning to give as a potential path to impact for more people.
Two questions that I’d be keen to get your views on, and which may be of interest to the community:
(1) How do you balance your earning to give/effective giving commitments with your family commitments? (e.g. in my own experience, one’s partner may disapprove of or be stressed out by you giving >=10%, and of course with a mortgage/kids things get even tougher)
(2) Would you say currently, the median EA should consider trying some E2G (or at least non-EA work while giving significantly) early on in their career?
The main considerations, as far as I see, relate to: (a) the EA labour market (where currently, demand for jobs outstrip supply—so chances of landing a job are low & counterfactual impact relative to next best hire is small); (b) whether money is the bottleneck for EA (it does seem so, at least for GHD/AW—and importantly, you can’t always choose to work at the most effective charities but can choose to donate to them); and (c) miscellaneous issues like financial stability, building career capital, and ability to switch career paths (traditional work in finance/consulting/tech for 1-3 years of E2G seem to be stronger on all three counts, relative to the marginal EA job that a fresh grad is likely to land)
Cheers,
Joel
My own experience, and my sense from talking to other organizations, is that management time is a significant opportunity cost, while the benefit (the work done by the intern) is both highly variable in quality and potentially not that great in expectation—not just because interns may be less experienced, but also because you probably put in fewer resources into the selection process, commensurate to the expected duration, cost and amount of work the intern puts in (all low relative to a full hire).
Some organizations leverage internships better, typically in roles that require time but not a lot of experience/expertise, and that require minimal supervision—but precisely because of that, the internship because less valuable from a talent pipeline perspective (since by definition you already have an existing source of free labour).
I don’t see any strong theoretical reason to do so, but I might be wrong. In a way it doesn’t matter, because you can always rejig your weights to penalize/boost one estimate over another.
I generally agree, and CEARCH uses geomeans for our geographic prioritzation WFMs, but I would also express caution—multiplicative WFM are also more sensitive to errors in individual parameters, so if your data is poor you might prefer the additive model.
Also general comment on geomeans vs normal means—I think of geomeans as useful when you have different estimates of some true value, and the differences reflect methodological differences (vs cases where you are looking to average different estimates that reflect real actual differences, like strength of preference or whatever)
Spectacles do look fairly promising, especially if conventional estimates of the benefits factor in income and not the pure health/sight aspect (depends on how much you think GBD disability weights of vision loss transfer over to myopia)
Yep, the idea is more the former. And While GWWC is mainly OP funded, that’s not entirely the case (https://forum.effectivealtruism.org/posts/a8wijyw45SjwmeLY6/gwwc-is-funding-constrained-and-prefers-broad-base-support), and could expand on the margin with individual donor contributions.
The point isn’t specific to GWWC though—rather, I think it’s potentially promising that cause-neutral effective giving organizations have the potential to effectively launder GHD dollars into AW dollars, by persuading GHD donors to support GHD effective giving (rather than persuading them to support animals, which is presumably harder).
This is somewhat offtopic, but getting GHD donors to give to GWWC and other GHD-focused effective giving orgs that also fundraise for AW, is effectively turning GHD dollars (from people who are emotionally uninvested in AW) into AW dollars for ACE et al.
And through this method, no appeal to animals is needed.
Intersectoral reallocation of resources doesn’t mean an overall increase in demand, and hence even influx of labour and capital into YIMBY-initiated housebuilding won’t cause higher inflation economy-wide—if anything, it pushes it down due to expanded supply bringing down rents, and as you note housing is an important part of PCE.
Generally, you would prefer lower interest rates from the perspective of LMICs, because you risk debt crises when high US interest rates intersect with LMIC dollar denominated debts, plus everything from food subsidies to investing in health/education/infrastructure becomes far more difficult.
Hi James, on the South Asian Air Quality portfolio, would be it be fair to say that OP’s grants so far have been focused on research and diagnosing both the problem and potential solutions, rather than executing on interventions themselves? Is the current bottleneck a lack of cost-effective and feasible ideas—and if so, what looks most promising so far?
This is something Sjir’s team and myself have discussed at length—we’re definitely more pessimistic than GWWC on this point.
CEARCH’s view is that the raw numbers look good, but if you regress dollar donated against year since pledging, while controlling for pledge batch (and hence the risk that earlier pledgers are systematically different/more altruistic), there is a positive but statistically insignificant relationship between average annual donations and years since pledging (n.b. increase in 35 dollars per annum at p=0.8). The experts we spoke to were split, with a weak lean towards it increasing over time—some were convinced by the income effects, while others were sceptical that you can beat attrition.
Ultimately, we chose to model a very marginal increase (<0.01% per annum); we’re really not confident that you can reasonably expect an increase in giving over time for the 2025 and future pledge batches.
For how expected donations generated by a dollar evolves over time (ignoring discounts), available evidence suggests that it’s flat (and so the graph is just a horizontal line terminating around 30 years later). There’s a lot of uncertainty, not least on how long the giving lasts, given that we can only observe a little more than a decade of giving at this point.
Thanks Sjir! I’m grateful for the transparency and data sharing throughout—I don’t see how we could have done the evaluation otherwise!
I don’t have the estimates for how the multiplier changes over time, though you would expect a decline, driven by the future pledging pool being less EA/zealous than earlier batches.
For the value of a *pledge* - based on analysis of the available data, it doesn’t appear that donations increase over time (for any given pledge batch), so after relevant temporal discounts (inflation etc), the value of a pledge is relatively front-loaded:
Hi Nuno,
We report a crude version of uncertainty intervals at the end of the report (pg 28) - taking the lower bound estimates of all the important variables, the multiplier would be 0x, while taking the upper bound estimates, it would be 100x.
In terms of miscellaneous adjustments, we made an attempt to be comprehensive; for example, we adjust for (a) expected prioritization of pledges over donations by GWWC in the future, (b) company pledgers, (c) post-retirement donations, (d) spillover effects on non-pledge donations, (e) indirect impact on the EG ecosystem (EG incubation, EGsummit), (f) impact on the talent pipeline, (g) decline in the counterfactual due to the growth of EA (i.e. more people are likely to hear of effective giving regardless of GWWC), and (h) reduced political donations. The challenge is that a lot of these variables lack the necessary data for quantification, and of course, there may be additional important considerations we’ve not factored in.
That said, I’m not sure if we would get a meaningful negative effect from people being less able to do ambitious things because of fewer savings—partly for effect size reasons (10% isn’t much), and also you would theoretically have people motivated by E2G to do very ambitious for-profit stuff when they otherwise would have done something less impactful but more subjectively fulfilling (e.g. traditional nonprofit roles). It does feel like a just-so story either way, so I’m not certain if the best model would include such an adjustment in the absence of good data.
https://docs.google.com/spreadsheets/d/1MF9bAdISMOMV_aOok9LMyKbxDEpOsvZ9VO8AfwsS6_o/
Probably majority AI, given the organizations being given to and the distribution of funding. This contrasts with the non-GWWC EG organizations in Europe, where I believe there is a much greater focus on climate, mainly to meet donors where they are at.
They’re working on creating an option to make it easy for posters to add the diamond, but in the meantime you can DM the forum team (I did!)
Hi Nicolaj,
Thanks for sharing! That’s really interesting. Couple of thoughts:
(1) For us, CEARCH uses n=1 when modelling the value of income doublings, because we’ve tended to prioritize health interventions where the health benefits tend to swamp the economic benefits anyway (and we’ve tended to priortize health interventions because of the heuristic that the NCDs are a big and growing problem which policy can cheaply combat at scale, vs poverty which by the nature of economic growth is declining over time).
(2) The exception is when modelling the counterfactual value of government spending, which a successful policy advocacy intervention redirects, and has to be factored in, albeit at a discount to EA spending, and while taking into account country wealth (https://docs.google.com/spreadsheets/d/1io-4XboFR4BkrKXgfmZHQrlg8MA4Yo_WLZ7Hp6I9Av4/edit?gid=0#gid=0).
There, the modelling is more precise, and we use n=1.26 as a baseline estimate, per Layard, Mayraz and Nickell’s review of a couple of SWB surveys (https://www.sciencedirect.com/science/article/abs/pii/S0047272708000248). Would be interested in hearing how your team arrived at n=1.87 - I presume this is a transformation of an initial n=1 based on your temporal discounts?
Cheers,
Joel
https://forum.effectivealtruism.org/posts/ymEqipmiM3SLyQvaC/value-of-life-vsl-estimates-vs-community-perspective
This might be of interest—goes through the various substantive issues with VSL as a method