I think this post is really pretty good. What I’d like to see, either included here or in future work, is a plain-language description of your assumptions and conclusions. I tried to make one, which went something like this:
GiveWell’s global health work saves lives, but the people they save go on to destroy insect habitat. The worth of a single insect is negligible relative to that of a human, but so many of them die when forests get cut down that global health efforts in certain locations could conceivably be bad overall. This side effect would be especially bad in countries where the most deforestation per capita is going on, and where habitat for insects is particularly lush.
Based on a shallow dive and plugging some numbers into a simple model, the results suggest we should reallocate human health resources out of a few countries and into other countries where less habitat destruction is happening, or reallocate some of those resources to preserving habitat. We really need to research this more carefully before taking these conclusions too seriously—but these early results suggest it would be worth the effort.
It would also be nice to move the acronyms (i.e. t_a) to the figure captions where they’re presented, and work on better formatting the tables. You’ve done the research and thinking, so take a little more time to polish up the presentation so we can read it more easily :)
Thanks for the kind words! I like your summary. Just one note, since we are arguably so far from knowing whether insects have good or bad lives, I do not think we can take the conclusion below.
Based on a shallow dive and plugging some numbers into a simple model, the results suggest we should reallocate human health resources out of a few countries and into other countries where less habitat destruction is happening
I believe the best attitude is one of cluelessness, where we just know that insects may dominate (or not) the analysis, either making GiveWell’s top charities much more harmful or beneficial. Moreover, we should beware surprising and suspicious convergence. If insects indeed went on to dominate the analysis (quite unclear), I would expect targetted wild animal interventions to be more effective than global health and development ones.
It would also be nice to move the acronyms (i.e. t_a) to the figure captions where they’re presented, and work on better formatting the tables.
I have now restated the meaning of N_ta and N_h just before the tables, and improved the formatting of the headers of the table a little.
You’ve done the research and thinking, so take a little more time to polish up the presentation so we can read it more easily :)
I think this post is really pretty good. What I’d like to see, either included here or in future work, is a plain-language description of your assumptions and conclusions. I tried to make one, which went something like this:
It would also be nice to move the acronyms (i.e. t_a) to the figure captions where they’re presented, and work on better formatting the tables. You’ve done the research and thinking, so take a little more time to polish up the presentation so we can read it more easily :)
Thanks for the kind words! I like your summary. Just one note, since we are arguably so far from knowing whether insects have good or bad lives, I do not think we can take the conclusion below.
I believe the best attitude is one of cluelessness, where we just know that insects may dominate (or not) the analysis, either making GiveWell’s top charities much more harmful or beneficial. Moreover, we should beware surprising and suspicious convergence. If insects indeed went on to dominate the analysis (quite unclear), I would expect targetted wild animal interventions to be more effective than global health and development ones.
I have now restated the meaning of N_ta and N_h just before the tables, and improved the formatting of the headers of the table a little.
Ah, you are right!