I was thinking of doing more research and a write up, but someone may have covered it or knows of a good reference (I have seen there is some related discussions here on uncertainty and Bayesian updating).
Priors are not all equal, there is a big (rather obvious) difference between a prior that is based on empirical data and quantitatively robust models, and priors that are based on personal guesses and intuitions. Personally, with my own empirical and skeptical training as background, I find conflating these somewhat unhelpful and giving the appearance of having more confidence than one really should at times (that is, having a 90% confidence derived from empirical analysis seems very different than having a 90% confidence derived from unenumerated priors).
Is there a good discussion anyone is aware of delineating these? It seems often, particularly among those applying bayesian updating to lay settings, priors are not clearly differentiated on an evidentiary basis.
I was thinking of doing more research and a write up, but someone may have covered it or knows of a good reference (I have seen there is some related discussions here on uncertainty and Bayesian updating).
Priors are not all equal, there is a big (rather obvious) difference between a prior that is based on empirical data and quantitatively robust models, and priors that are based on personal guesses and intuitions. Personally, with my own empirical and skeptical training as background, I find conflating these somewhat unhelpful and giving the appearance of having more confidence than one really should at times (that is, having a 90% confidence derived from empirical analysis seems very different than having a 90% confidence derived from unenumerated priors).
Is there a good discussion anyone is aware of delineating these? It seems often, particularly among those applying bayesian updating to lay settings, priors are not clearly differentiated on an evidentiary basis.