Although communicating the precise expected resilience conveys more information, in most situations I prefer to give people ranges. I find it a good compromise between precision and communicating uncertainty, while remaining concise and understandable for lay people and not losing all those weirdness credits that I prefer to spend on more important topics.
This also helps me epistemically: sometimes I cannot represent my belief state in a precise number because multiple numbers feel equally justified or no number feels justified. However, there are often bounds beyond which I think it’s unlikely (i.e. <20% or <10% or my rough estimates) that I’d estimate that even with an order of magnitude additional effort.
In addition, I think preserving resilience information is difficult in probabilistic models, but easier with ranges. Of course, resilience can be translated into ranges. However, a mediocre model builder might make the mistake of discarding the resilience if precise estimates are the norm.
Although communicating the precise expected resilience conveys more information, in most situations I prefer to give people ranges. I find it a good compromise between precision and communicating uncertainty, while remaining concise and understandable for lay people and not losing all those weirdness credits that I prefer to spend on more important topics.
This also helps me epistemically: sometimes I cannot represent my belief state in a precise number because multiple numbers feel equally justified or no number feels justified. However, there are often bounds beyond which I think it’s unlikely (i.e. <20% or <10% or my rough estimates) that I’d estimate that even with an order of magnitude additional effort.
In addition, I think preserving resilience information is difficult in probabilistic models, but easier with ranges. Of course, resilience can be translated into ranges. However, a mediocre model builder might make the mistake of discarding the resilience if precise estimates are the norm.