Prioritising causes using scale, neglectedness, and solvability

In the examples above, we could easily screen out those causes for one reason or another. Of course, we would also want our cause prioritisation methodology to tell us, of the problems which remain, which are the highest priority. Let’s distinguish two stages of cause prioritisation. Stage A is where we screen out some of the problems, which we do by assessing all their solutions—this is the stage we have already discussed. At stage B, we determine the marginal cost-effectiveness of the problems which remain. In this section, I explain how the three factors (scale, neglectedness, solvability) combine to determine marginal cost-effectiveness of different causes and allow us to make progress at stage B.

MacAskill, in an explanatory footnote, offers more formal definitions of the terms used informally in the first quote and sets out how the three factors combine to determine the cost-effectiveness of a cause:

Formally, we can define these as follows: Scale is good done per by percentage point of the problem solved; solvability is percentage points of a problem solved per percentage point increase in resources devoted to the problem; neglectedness is percentage point increase in resources devoted to the problem per extra hour or dollar invested in addressing the problem.

When these three terms are multiplied together, we get the units we care about: good done per extra hour or dollar invested in addressing the problem.⁶

6 I believe Cotton-Barratt (2016) was the one who first identified how the factors could be combined to assess cost-effectiveness. EA career’s advice service 80000 Hours and Wilbin (2017) also uses this quantitative version of the framework.

179 We can write this as an equation:

Scale x Solvability x Neglectedness = Good done/dollar

(Good done/% solved) x (% solved/% increase in resources) x (% increase in resources/extra dollar) = Good done/dollar

Hence, scale, neglectedness and solvability are defined as factors which, when multiplied together, calculate the cost-effectiveness of whichever cause is being analysed.

It’s worth briefly noting the existence of an earlier/alternative version of the three-factor framework that is qualitative in nature.⁷ On the qualitative version, the same three factors were thought relevant to understanding a cause’s cost-effectiveness—

causes that were larger, more solvable and more neglected were presumed to be higher priority. However, there was no mechanism to trade-off the factors against each other or to combine them to determine cost-effectiveness, something this quantitative version allows. I use the newer quantitative version as it—unlike the older, qualitative one—allows us to determine the cost-effectiveness of causes and thus compare them to each other on that basis.

This brings us to the question of why there are three factors (rather than, say, four) and why these particular factors are used. This becomes clear once consider that causes generally have diminishing marginal returns: individuals will pick the ‘low

7 This is version is used by MacAskill (2015) in chapter 10 and Wiblin (2016). It seems to have been originally proposed by Open Philanthropy Project and Karnofsky (2014). In conversation, Hilary Greaves suggests that this version is arguably implicitly quantitative in nature, or at least used in that way: individuals applying the framework would assume something like the following: if cause A was X% larger in scale but Y% less neglected than cause B, the two causes would be equally cost-effective at a given ratio of X:Y. It might be true that framework has been in used this way, but given that no explanation has been offered as to why the factors could be traded-off like this, or what the appropriate ratios are, it’s hard to see what justification there could be for using this framework to set priorities as opposed to just making educated guesses about the cost-effectiveness of particular interventions.

180

hanging-fruit’ first, which means that initial resources put towards the problem will do more good per unit of resource than those added subsequently. This is represented in figure 5.1.

We can now point out the role each of the three factors plays. To determine the cost-effectiveness of additional resources, we need to know three things. First, the scale of the problem—how far up the Y-axis, which represents value, the line goes (how much fruit there is to pick in a given field).

Second, how much of the problem is solved for different amounts of resources, which is what solvability refers to (how easy it is to pick the fruit in this field and how this gets progressively harder). Combined with scale, this gives the shape of the cost-effectiveness line, which I’ll call the solvability line. We cannot determine the solvability line with a single assessment, which is what we might have thought, but a series of assessments: given diminishing marginal returns, the fraction of the cause that is solved for a given amount of resources reduces as more resources are added. If there were instead constant marginal returns, that is, the cost-effectiveness was linear, then one assessment of the solvability line would suffice.

Figure 5.1.

Scale

Less neglectedness Solvability line

Value

Resources

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Third, we need to know how many resources are being directed at the problem, which is what neglectedness captures. Imagine two identical problems, A and B, with the same solvability line. Suppose no one will try to solve A but many people will try to solve B. Assuming people will pick the low-hanging fruit first, then the cost-effectiveness of additional resources to B will be lower than A. The way we’d represent that on the graph is pushing along the X-axis the point at which we start counting marginal resources. This fact is illustrated in figure 5.2. overleaf.

Thus, we need to know the scale, solvability and neglectedness in order to correctly locate both ‘where on the curve we are’, so to speak—that is, where we should start counting the effectiveness of our marginal resources from—and where we would get to for the additional units of resources we contribute. If we know the three factors, we can determine the cause’s priority (its cost-effectiveness). Note, however, that if there were constant marginal returns, i.e. cost-effectiveness was linear, we would only need two pieces of information to determine cost-effectiveness: first, the scale of the problem; second, a single assessment of solvability, i.e. the absolute number of resources required to solve X% of the problem.

Let’s state the answers to the third and fourth questions posed earlier (what role do the three factors play? Why there are three factors (rather than, say, four) and why these particular factors are used?). To the third, the response is that the three factors are multiplied together to determine the cost-effectiveness of a cause; to the fourth, our goal is to determine cost-effectiveness, and these three are individually necessary and jointly sufficient for that task, hence the factors allow us to meet that goal.

182 Figure 5.2.