Larry Wasserman calls the use of noninformative priors a “lost cause.” I agree for the reasons he stated, and the fact that there are always better alternatives anyway. At the very least, there are the heavy-tailed “weakly informative priors” that put nearly all weight on something reasonable, such as small to moderate values of a variance, and little weight on stupid prior values, such as mean values on the order of 10100.
However, they’ll be around for years to come. Noninformative priors are nice security blankets, and we get to think that we are approaching a problem with an open mind. I guess open minds can have stupid properties as well.
I hope, though, that we will start thinking more deeply about the consequences of our assumptions especially about noninformative priors rather than feeling nice about them.