This is a somewhat hard to read (at least for me) Wikipedia article on sensitivity analysis. It’s a common tool; my extension of it to moral uncertainty would basically boil down to “Do what people usually advice, but for moral uncertainty too.” I’ll link this comment (and that part of this post) to my post on that once I’ve written it.
Also, sensitivity analysis is extremely easy in Guesstimate (though I’m not yet sure precisely how to interpret the results). Here’s the Guesstimate model that’ll be the central example in my upcoming post. To do a sensitivity analysis, just go to the variable of interest (in this case, the key outcome is “Should Devon purchase a fish meal (0) or a plant-based meal (1)?”), click the cog/speech bubble, click “Sensitivity”. On all the variables feeding into this variable, you’ll now see a number in green showing how sensitive the output is to this input.
In this case, it appears that the variables the outcome is most sensitive too (and thus that are likely most worth gathering info on) are the empirical question of how many fish hedons the fish meal would cause, followed at some distance by the moral question of choice-worthiness of each fish hedon according to T1 (how much does that theory care about fish?) and the empirical question of how much human hedons the fish meal would cause (how much would Devon enjoy the meal?).
And is there any literature or information on how value of information analysis can account for things like unknown unknowns?
Very good question. I’m not sure, but I’ll try to think about and look into that.
This is a somewhat hard to read (at least for me) Wikipedia article on sensitivity analysis. It’s a common tool; my extension of it to moral uncertainty would basically boil down to “Do what people usually advice, but for moral uncertainty too.” I’ll link this comment (and that part of this post) to my post on that once I’ve written it.
Also, sensitivity analysis is extremely easy in Guesstimate (though I’m not yet sure precisely how to interpret the results). Here’s the Guesstimate model that’ll be the central example in my upcoming post. To do a sensitivity analysis, just go to the variable of interest (in this case, the key outcome is “Should Devon purchase a fish meal (0) or a plant-based meal (1)?”), click the cog/speech bubble, click “Sensitivity”. On all the variables feeding into this variable, you’ll now see a number in green showing how sensitive the output is to this input.
In this case, it appears that the variables the outcome is most sensitive too (and thus that are likely most worth gathering info on) are the empirical question of how many fish hedons the fish meal would cause, followed at some distance by the moral question of choice-worthiness of each fish hedon according to T1 (how much does that theory care about fish?) and the empirical question of how much human hedons the fish meal would cause (how much would Devon enjoy the meal?).
Very good question. I’m not sure, but I’ll try to think about and look into that.
It’s good to have a word for that sort of thing.