We need more nuance regarding funding gaps

TLDR: Funding gaps should be talked about in more specific ways, e.g., considering specific cause areas, organizational scale, and funder diversity. When broken down this way, there are likely far more gaps than many EAs imagine. Our model should look more like the table below than a simple “whether EA has strong funding or not” aggregate.

Funding gaps are a well-discussed topic in the EA movement and between funders of all sizes. The concept overall is highly relevant and useful when making decisions. However, I think the bulk of communication about funding gaps is quite unspecific and unrefined, and even carefully communicated content can lead to confusion in overall discourse. A claim like “EA has a funding gap” or “EA does not have a funding gap” is too unspecific a heuristic and can lead to a lot of confusion about the state of funding, as some strong charities receive no funding despite a consensus that the given area is considered “funding flooded.” Working with a number of early-stage charities going through the Charity Entrepreneurship Incubation Program has really given me a more nuanced sense of where specific gaps are and how important this information can be.

Cause area variation

Funding gaps quite clearly change across cause area, and it could be true overall that AI has very few funding gaps while mental health has many. But I think the level of nuance could even go a lot deeper than that. Corporate campaigns in animal welfare might be well-funded while, at the same time, funding in vegan outreach is quite limited. Funding differences according to location can also be radical, with a project in London getting far more funding than the same project based out of Abuja. Most funders and EAs recognize this, although it’s sometimes forgotten in the broader discourse. A less-considered factor is that organizations might have other differentiating factors outside of cause area that affect their funding options. This possibility is what I want to delve into more in-depth for this post.

Organizational size variation

A factor that is not often talked about is that the size (and correlating factors like age) of an organization can be just as influential to funding availability as cause or intervention area. For example, there are areas with large governmental funders who only consider organizations of a certain size and age or have requirements that would be near impossible for a smaller organization to fulfill. Governments are not the only entities with these restrictions – large funders are often looking for large opportunities. Some funders are uniquely keen on very large megaprojects but, of course, relatively few of them launch from scratch, with most experiencing a slow build-up of resources and capacity.

Example: global poverty
To take global poverty as an example, GiveWell is typically looking for organizations that can absorb considerable amounts of funding in the near future (e.g., 10 million per year or more). This strategy is well thought out. GiveWell wants to move a huge amount of funding and only has time to evaluate a certain number of organizations to the level of depth they require in order to recommend them. It would take 10x as much evaluation time to consider 10 organizations that can each only absorb 1 million per year. Although this strategy makes sense in GiveWell’s case, it can have a strange effect on the ecosystem. It may result in small projects not getting funding because of the idea that GiveWell would already have funded strong projects in the area (without a donor necessarily knowing whether a charity was ruled out for cost-effectiveness or simply size). It also means there are considerable impacts that may be left on the table from new organizations who have not gotten to that scale or small-scale projects that could be highly cost-effective but do not have the capacity to grow to that size. This means that even in an area that has funding overhangs, there could be and often are still highly promising projects that are funding-limited. For example, my current sense of the poverty funding space based on organizational size is radically different than the impression one might get if they only consider the large-scale funding column.

Differentiated size can, in some ways, be very exciting. Being the funder in an area that has a weak seed stage but a strong large-scale funding stage could allow a given donation to be catalytic and get an organization to the size it needs to be to access other pools of support. It could also mean there are highly impactful opportunities (e.g., at higher levels of cost-effectiveness or with a different risk profile) that could result in more impact per $, even considering only the more direct impacts compared to the well-known impacts of larger-scale organizations.

I think global poverty is a good example of an area that has highly differentiated funding availability depending on organization size, both inside (connecting to GiveWell) and outside (connecting to large-scale foundations and governmental actors) of the EA movement.

Example: animal welfare

Let’s look at a different area that, although much smaller, is balanced much better across organization size: the animal welfare movement.

Even though the total sum of money going into animal welfare is considerably smaller (particularly at the high end), due to its balance, a new well-performing animal welfare organization does not have as clear a valley of death for getting to a certain size. There are, however, funding pathways fairly clearly divided. Even though there are certain size requirements that Open Philanthropy, for example, might have in order to fund animals, places like the Animal Welfare Fund allow smaller projects to ramp up to a size where they could be considered by larger funding bodies down the road. A result of this is that when considering projects founded by CE, although our largest projects end up being poverty initiatives, far more of them struggle in the early stages (including the ones that eventually get to scale) relative to our animal-focused organizations.

Laying out more information

So, this view, broken up by cause area and organization size, adds a lot of nuance to the discussion of what the funding gap is for different organizations. However, I still think it’s pretty inexact and there is more information to consider. Another big factor that connects to funding availability is the diversity of funders in a given space. Particularly, funders with different views and intuitions. One funder with 10 million per year of available funding would almost definitely make different calls than 10 funders with 1 million each, even if all agree broadly with the principles of EA and want to maximize impact. Doing good is messy, and intelligent and reasonable people can disagree on what the most impactful thing to do is. Sometimes an organization will be extremely clear on which areas they cover and which they do not (GiveWell does a good job of this, for example), but every funder has a certain worldview as well as logistical and ethical assumptions (whether stated or not) that affect their donations. So, let’s add some information onto our chart here connecting to the number of funders with unique, but still fairly EA, views in a given area. An estimated number of unique funders is now added in brackets to each cell below.

Unsurprisingly, areas with more limited funding will have fewer differentiated funders. More surprisingly, an area can have a very large volume of total funding but relatively few unique effectiveness-minded views. Although animal organizations might have had an easier time scaling up, once they are large, if they have a different view than one of the relatively few funders it could change their situation dramatically. Poverty, on the other hand, has a pretty healthy ecosystem, even when limiting it to just those with semi-EA mindsets. Diverse funding sources also make an ecosystem less likely to be affected by a historical fluke (e.g., if Open Philanthropy is the only/​main actor in a space and recommends two areas but only finds a program officer for one of them, this could majorly affect the funding in the space as a whole).

Broader but not deeper

This information, breaking up gaps by cause, organization size, and funder diversity, is about as deep as I personally went into this issue. I think there are other factors that could really change the probability of funding, such as disconnected capacity (for example, if Open Philanthropy was not able to find a good program officer for air quality, there would have been far less funding in the space) or geographic factors.

For a few areas, I did do a full map that I might post at a later time covering how much room for more funding there is and what specific sources give funding vs. what charities report having RFMF. I did, however, broaden it and get some other folks to check the numbers. A little over half a dozen people commented on these numbers and suggested changes to my estimates. Many of them were funders who had a sense of the ecosystem they were in, while the rest were charity CEOs working in the relevant spaces. However, I expect these numbers are far from perfect. I think that in reality there could be more or fewer sources of funding, depending both on the information known (there are some big funders known to only a handful of people in the EA movement) and the definitions used (what counts as impact-focused?). Still, I do think this is a decent estimation of what a new charity would know when getting started with some moderately strong connections in the EA movement (a group I know very well).

I think that taking the same landscape and breaking it up in other novel ways (e.g., not by cause but by evaluation process) could also lead to finding some impactful funding gaps.

I think there is a bit of a habit in the EA movement of not posting something unless you have an extremely high level of confidence in each number, but I think it’s better to be imprecisely correct vs. precisely incorrect. I also see moving to a model closer to this level of nuance, even with imperfect data (which, sadly, will always be the case for information like this), as a very positive step forward. Happy to see information in comments or DMs that could suggest updates on this model and, of course, I expect this model to change over time as new funders come on or current funders change their priorities.

Note: I also might write a follow-up post on how the EA movement could facilitate possible solutions to move forward on key “red” gaps in this model.