Hi, thanks to a post that I recently wrote about geographic diversity in EA I have discussed this question with people from other local groups that have more experience in local prioritization and it has led to very interesting conversations (I hope we will have something similar for South America soon). So here are my thoughts:
Choosing the most promising causes is a promising and neglected cause by itself, since there can be large differences in value between causes and the area has received little attention outside EA. So far, there have been more efforts to prioritize specific interventions with more immediate goals by comparing their effectiveness but this narrow view can lead us to ignore other areas that could bring more welfare in the long term even if those are harder to assess and difficult to measure. The value of research in this field (as stated on the cause prioritization overview by 80,000 hours) will come from learning how to build the infrastructure for much better prioritization in the future. Exploring ways of prioritizing causes can be valuable even if the methodologies that are put to the test show to be inadequate, since spotting the difficulties that arise during the process and learning how certain tools are inaccurate would facilitate future efforts and shed light on the weaker spots
Existing organizations that develop cause prioritization research usually evaluate priorities from a global perspective; however, I wonder if cause neutrality is necessarily against local prioritization. Perhaps there is a scenario in which we can maintain cause neutrality by having a portfolio of regional causes instead of (or parallel to) a list of global ones. Also, it is not always clear that it would be more cost-effective to coordinate different actors across the globe concerned with the same causes than to coordinate agents with different preference orderings.
Some groups in lower and middle income countries have tried to come up with their own list of priority causes as a way to give advice to local donors about their comparative advantages and some of the identified cause areas are surprisingly different from other global priority causes in EA. The causes are not necessarily immediate nor specific, and some of them –even if narrow in their geographical scope– can have a relatively long-term scope. I wonder if these efforts could inform global prioritization as a whole if done more broadly across the world. Not only their perceptions on what should be prioritized have informational value, but also their assessment of their comparative advantages deserve more investigation.
Finding priorities depends on reliable comparisons with common metrics, but the search for common metrics requires more abstractions and assumptions about long run effects than narrower prioritization. I wonder if we could be narrower in our geographical scope as a way to counter our broad long-term approach; also it could allow us to develop frameworks to aggregate local priority cause research to spot promising areas. Perhaps this could provide a way to break the broader question into pieces and even if we discover that it leads us in a wrong direction, it could help build better methodologies for future explorations.