Applied Researcher at Founders Pledge
I think that’s a bit too pessimistic! Founders Pledge has made some progress on this (link goes to pdf) and I think we can do pretty well by taking a kind of journalistic approach. For example, we can speak to charities, experts, and government officials and see if the charity’s claims about who they spoke to and when are true, if the timelines match up, and if it seems like the government would have made changes anway. Check out pp. 8-10 of the linked doc.
I do recognize that this is much more difficult than looking at the results of an RCT. We’ll never be as sure that the effect is causal and it takes a lot of time from both us and the organisation we’re looking at. These costs are the main reason we’re not continuing our growth work at this time.
Thanks for this thoughtful comment! Thinking about x-risk reduction as giving us more time to grow the economy and alleviate poverty is really interesting.
While I agree the long-term effects are highly uncertain, I think it’s important to distinguish catch-up growth from frontier growth. Most growth accelerations in low-income countries bring them from “super poor” to “still pretty poor”. People in these countries live more comfortably, but they’re usually not getting rich enough to develop geopolitical ambitions that increase x-risk. (China and maybe India being notable exceptions.)
I’m actually not sure it’s true that “most of us have accepted longtermism.” As we say in this post, the Global Health and Development Fund is still the biggest EA Fund. Last year’s EA survey found that Global Poverty was still the most popular cause, and only 41% of respondents would choose the Long Term Future if they had to focus on one cause.
In any case, we might want to continue to have some EAs working on things other than longtermism in order to diversify in the face of moral uncertainty. And, as you say, having something useful and interesting to say about more mainstream causes is important for PR and movement growth. I thought the discussion of this point in the comments of this post was good.
I think it’s probably the case that good heuristics for making career decisions are different than good heuristics for making donation decisions. We shouldn’t necessarily expect a framework (ITN or otherwise) to be ideal for both.
If someone today decides to work on a certain cause, they strengthen the pipeline of good funding opportunities in that cause. But there’s a time lag. Pivoting to work on biosecurity might be a great career decision right now. However funding a person to do that work might not be a great donation until a few years down the road, when they’ve gained the skills and credentials needed to make an impact.
As another data point, this OECD report says that from 2013-15, half of all philanthropic funding for international development came from the Gates Foundation ($12 billion out of $24 billion total).
Hey Bryan, agree that this is a really interesting cause area in high-income countries. I’ve written a report on UK planning reform for Founders Pledge. We’ve recommended London YIMBY, who are working to strengthen Johnson’s proposed reforms and design politically-palatable proposals that will actually get through Parliament.
As you know, proper land use reform could have very large welfare benefits so I’m excited to see more work bringing attention to the issue! Now the trick is finding policy proposals that overcome the huge political barriers to reform. I’m glad you think Biden’s proposals are decent.
NTI is a great choice! I also ran a birthday fundraiser this year. I think there are positive benefits to running public donation campaigns. I’m also a fan of “normalizing” giving by running small fundraisers like this.
Hey Sam, thanks for this. I always appreciate the critical, reflective perspective you bring to these discussions. It’s really valuable. I think you’re right that we should consider the failure modes to which we’re vulnerable and consider adopting useful tools from other communities.
I think perhaps it’s a bit premature to dismiss the value of probabilistic predictions and forecasting. One thing missing from this post is discussion of Tetlock’s Expert Political Judgement work. Through the ’90s and ’00s, Tetlockian forecasters went head-to-head against analysts from the US military and intelligence communities and kicked their butts. I think you’re right that, despite this, forecasting hasn’t taken over strategic decisionmaking in these communities. But as far as I know Tetlock has continued to work with and receive funding from intelligence projects, so it seems that the intelligence people see some value in these methods.
I think I’d agree with other commenters too that I’m not sure longtermist grants are that reliant on expected value calculations. The links you provide, e.g. to David Roodman’s recent paper for Open Phil, don’t seem to support this. Roodman’s paper, for example, seems to be more of a test of whether or not the idea of explosive economic acceleration this century is plausible from a historical perspective rather than an attempt to estimate the value of the future. In fact, since Roodman’s paper finds that growth tends to infinity by 2047 it’s not actually helpful in estimating the value of the future.
Instead, it seems to me that most longtermist grantmaking these days relies more on crucial considerations-type analysis that considers the strength of a project’s causal connection to the longterm future (e.g. reducing ex risk).
P.S. If you ever feel that you’re struggling to get your point across I’d be happy to provide light edits on these posts before they go public—just message me here or email me at work (stephen [at] founderspledge [dot] com)
It could be and I know there’s at least one non-profit working in this space (Taimaka Project). One Acre Fund also provides loans to farmers. However I don’t think this intervention seems likely to be much better than cash transfers, and could be worse (because less targeted and involves a lot more overhead).
Oh, also Tyler Cowen and Esther Duflo sort of discuss this question in their Conversation (ctrl + f “invest” or “return” to find the discussion). Duflo says:
So there are some people with very high rates of return, as you were saying, 50 percent or 60 percent. But there are not very many. I think that is why the . . . First of all, there are not very many, and they are not necessarily the one that have access to money. That’s one of the big reasons why the cost is lower, is that there is a mismatch between the investment opportunity and who has the money. And that’s what my colleagues call misallocation.
This is a really important question, and I agree a bit of a puzzle. Burke, Bergquist, and Miguel sort of address it in “Sell Low and Buy High”. Burke et al. test the effect of providing credit to farmers in Kenya. They find that with access to credit, farmers are able to save more of their harvest and sell it at a different time when local prices are higher, raising their income and allowing them to pay back the loan. The return on investment is 29%.
But, as you say, 29% is a big return—why aren’t local lenders already providing this opportunity? From the very end of the paper (p. 838-9):
What our results do not address is why wealthy local actors—for example, large-scale private traders—have not stepped in to bid away these arbitrage opportunities. Traders do exist in the area and can commonly be found in local markets. In a panel survey of local traders, we record data on the timing of their marketing activities and storage behavior but find little evidence of long-run storage. When asked to explain this limited storage, many traders report being able to make even higher total profits by engaging in spatial arbitrage across markets (relative to temporal arbitrage). Nevertheless, this does not explain why the scale or number of traders engaging in both spatial and intertemporal arbitrage has not expanded; imperfect competition among traders may play a role
So, yeah, they don’t really know. Lenders have other good opportunities, and maybe discount future returns enough that they would rather engage in spatial rather than temporal arbitrage. As Larks wrote, too, risk aversion and fixed costs could make these very small loans to people in extreme poverty unattractive.
I’m really happy to see the Animal Welfare Fund is still getting lots of donations. I also think the range of organisations receiving grants is pretty awesome!
I’d be curious to hear someone from the Fund talk a bit about the rationale for providing smaller grants to a large number of organisations, rather than larger grants to a smaller number of the most promising projects. Apologies if this has been addressed before.
The FCO-DFID merger seems pretty anti-EA to me. The stated motivation was to allow the government to leverage the UK’s aid budget to advance British interests. In contrast, presumably, an independent DFID was more free to pursue poverty allevation and development as an end goal. It’s odd to me that this angle isn’t really discussed in the piece.
I also think it would probably be really bad for Cummings to become associated with EA given that he’s such a controversial and disagreeable person. And while I’ve seen him linked with us multiple times, I can’t actually find any material where he’s discussed, supported, or even mentioned EA.
Yeah, I don’t blame Linch for passing on this question since I think the answer is basically “We don’t know and it seems really hard to find out.”
That said, it seems that forecasting research has legitimately helped us get better at sussing out nonsense and improving predictions about geopolitical events. Maybe it can improve our epistemic status on ex risks too. Given that there don’t seem to be too many other promising candidates in this space, more work to gauge the feasibility of longterm forecasting and test different techniques for improving it seems like it would be valuable.
Thanks for this! Something that came to my mind as I was reading this was that it might be time for an update of CEA’s list of good policy ideas that won’t happen (yet).
You wrote that “It seems like, given an already-existing basket of policies we’d be interested in advocating for, we can make lobbying more cost-effective just by allocating more resources to (e.g.) issues that are less salient to the public.” This made me think it might be useful be to make a list of EA-relevant policy ideas and start organizing them into a Charity Entrepreneurship-style spreadsheet. Something I’ll keep musing on!
I’m also curious about what motivated you to take on this project, and what you’re planning to work on next?
Wow, this is really fantastic work! Thank you for the effort you put into this. Overall I think this paints a more optimistic picture of lobbying than I would have expected, which I find encouraging.
To follow up on a couple specific points:
(1) Just in terms of my own project planning, do you have an estimate of how long you spent on this? If you had another 40 hours, what uncertainties would you seek to reduce?
(2) Your discussion of Bumgartner et al. (2009) is super interesting. You write “Policy change happens over a long time frame.” I wonder if you could expand on this briefly. Do you mean that it takes a lot of lobbying over years before a policy change happens, or do you mean that meaningful policy change happens through incremental policy changes over time?
(3) Your finding that lobbying which protects the status quo is much more likely to be effective seems particularly actionable. I mean, once put into words it seems obvious, but it’s a point I hadn’t thought about before. I notice, though, that your list of ideas seems to consist of positive changes rather than status quo protection. I wonder if it would be worth brainstorming a list of good status quo issues that might be under threat. Protecting these would be less exciting than big changes, but for exactly the reasons you outline here more likely to work!
(4) I’m interested in thinking a bit more about uncertainty about policy implementation. This is something that we’re currently grappling with in our models of policy change where I work (Founders Pledge). On the one hand, the Tullock Paradox suggests that we should expect lobbying to be extremely difficult (otherwise everyone would do a lot more of it). On the other hand, we’ve noticed that very good policy advocates seem to quite regularly affect meaningful policy changes (for example, it seems like the Clean Air Task Force regularly succeeds in their work).
In your model you write that “the change in probability of policy implementation lies with 95% confidence between 0 and 5%, and is distributed normally.” I’m not sure about this, but I imagine the distribution of “chance of affecting policy success” over all the possible policies we could work on is much flatter than this. Or perhaps it’s bimodal: there are some issues on which it is near impossible to make progress and some issues where we could definitely get policies implemented if we spent a certain amount of money in the right way.
Perhaps we want to start with a low prior chance of policy success, and then update way up or down based on which policy we’re working on. Do you think we’d be able to identify highly-likely policies in practice?
(5) I found this post super helpful, but overall I think I’m still quite puzzled by the Tullock Paradox. If anything I’m more confused now, given that this post made me update in favour of policy advocacy. I think perhaps something that’s missing here is a discussion of incentives within the civil service or bureaucracy. A policy proposal like taking ICBMs off hair-trigger alert just seems so obvious, so good, and so easy that I think there must be some illegible institutional factors within the decision-making structure stopping it from happening. I don’t blame you for excluding this issue considering the size of this post and the amount of research you’ve already done, but it seems worth flagging!
Thanks again for a great post! I’m really excited about more work in this vein.
Some fun, useful questions with shorter time horizons could be stuff like:
Will GiveWell add a new Top Charity to its list in 2020 (i.e. a Top Charity they haven’t previously recommended)?
How much money will the EA Funds grant in 2020? (total or broken down by Fund)
How many new charities will Charity Entrepreneurship launch in 2020?
How many members will Giving What We Can have at the end of 2020?
How many articles in [The Economist/The New York Times/...?] will include the phrase “effective altruism” in 2020?
Stuff on global development and global poverty could also be useful. I don’t know if we have data to resolve them, but questions like:
What will the global poverty rate be in 2021, as reported by the World Bank?
How many malaria deaths will there be in 2021?
How many countries will grow their GDP by more than 5% in 2021?
I’m slightly confused by the part where you say you’re struggling to understand effectiveness on an “emotional” level. Are your doubts about the state of our knowledge about charity effectiveness, or are you struggling to feel an emotional connection to the work of the charities we’ve identified as highly effective?
Lots of EAs seem pretty excited about forecasting, and especially how it might be applied to help assess the value of existential risk projects. Do you think forecasting is underrated or overrated in the EA community?
Most of the forecasting work covered in Expert Political Judgement and Superforecasting related to questions with time horizons of 1-6 months. It doesn’t seem like we know much about the feasibility or usefulness of forecasting on longer timescales. Do you think longer-range forecasting, e.g. on timescales relevant to existential risk, is feasible? Do you think it’s useful now, or do you think we need to do more research on how to make these forecasts first?
Good forecasts seem kind of like a public good to me: valuable to the world, but costly to produce and the forecaster doesn’t benefit much personally. What motivates you to spend time forecasting?