Do you think there’s more useful research to be done on this topic? Are there any specific questions you think researchers haven’t yet answered sufficiently? What are the gaps in the EA literature on this?
Thanks for this. That’s a good question. I think it partially depends on whether you agree with the above analysis. If you think it’s correct that, when we drill down into it, evaluating problems (aka ‘causes’) by S, N, and T is just equivalent to evaluating the cost-effectiveness of particular solutions (aka ‘interventions’) to those problems, then that settles the mystery of what the difference really is between ‘cause prioritisation’ and ‘intervention evaluation’ - in short, they are the same thing and we were confused if we thought otherwise. However, if someone thought there was a difference, it would be useful to hear what it is.
The further question, if cause prioritisation is just the business of assessing particular solutions to problems, is: what the best ways to go about picking which particular solutions to assess first? Do we just pick them at random? Is there some systemic approach we can use instead? If so, what is it? Previously, we thought we have a two-step method: 1) do cause prioritisation, 2) do intervention evaluation. If they are the same, then we don’t seem to have much of a method to use, which feels pretty dissatisfying.
FWIW, I feel inclined towards what I call the ‘no shortcuts’ approach to cause prioritisation: if you want to know how to do the most good, there isn’t a ‘quick and dirty’ way to tell what those problems are, as it were, from 30,000 ft. You’ve just got to get stuck in and (intuitively) estimate particular different things you could do. I’m not confident that we can really assess things ‘at-the-problem-level’ without looking at solutions, or that we can appeal to e.g. scale or neglectedness by themselves and expect that to very much work. A problem can be large and neglecteded because its intractable, so can only make progress on cost-effectiveness by getting ‘into the weeds’ and looking at particular things you can do and evaluating them.
Do you think there’s more useful research to be done on this topic? Are there any specific questions you think researchers haven’t yet answered sufficiently? What are the gaps in the EA literature on this?
Hello Risto,
Thanks for this. That’s a good question. I think it partially depends on whether you agree with the above analysis. If you think it’s correct that, when we drill down into it, evaluating problems (aka ‘causes’) by S, N, and T is just equivalent to evaluating the cost-effectiveness of particular solutions (aka ‘interventions’) to those problems, then that settles the mystery of what the difference really is between ‘cause prioritisation’ and ‘intervention evaluation’ - in short, they are the same thing and we were confused if we thought otherwise. However, if someone thought there was a difference, it would be useful to hear what it is.
The further question, if cause prioritisation is just the business of assessing particular solutions to problems, is: what the best ways to go about picking which particular solutions to assess first? Do we just pick them at random? Is there some systemic approach we can use instead? If so, what is it? Previously, we thought we have a two-step method: 1) do cause prioritisation, 2) do intervention evaluation. If they are the same, then we don’t seem to have much of a method to use, which feels pretty dissatisfying.
FWIW, I feel inclined towards what I call the ‘no shortcuts’ approach to cause prioritisation: if you want to know how to do the most good, there isn’t a ‘quick and dirty’ way to tell what those problems are, as it were, from 30,000 ft. You’ve just got to get stuck in and (intuitively) estimate particular different things you could do. I’m not confident that we can really assess things ‘at-the-problem-level’ without looking at solutions, or that we can appeal to e.g. scale or neglectedness by themselves and expect that to very much work. A problem can be large and neglecteded because its intractable, so can only make progress on cost-effectiveness by getting ‘into the weeds’ and looking at particular things you can do and evaluating them.