The fractal nature of scientific revolutions, again

Shravan writes,

In his book, Fooled by Randomness, Taleb essentially rejects the notion that past results [knowledge] can increase information incrementally. For example, he says [approvingly] that Popper "refused to blindly accept the notion that knowledge can always increase with incremental information--which is the foundation of statistical inference" (p. 127). Isn't this the same thing as saying that informative priors are not really informative? Informative priors represent our previous knowledge--Taleb rejects that as a basis for predicting the future. I see his point regarding trading practices, but I wonder if his position would extend to any statistically driven inference in, say, experimental psychology. I would think not.

My reply: I think the point is that the model itself continually needs to be reassessed, and in good work it ends up getting revised at irregular intervals; see here.