Personalized Search generates user profiles using a MapReduce over Bigtable. These user profiles are used to personalize live search results.This appears to confirm that Google Personalized Search works by building high-level profiles of user interests from their past behavior.
I would guess it works by determining subject interests (e.g. sports, computers) and biasing all search results toward those categories. That would be similar to the old personalized search in Google Labs (which was based on Kaltix technology) where you had to explicitly specify that profile, but now the profile is generated implicitly using your search history.
My concern with this approach is that it does not focus on what you are doing right now, what you are trying to find, your current mission. Instead, it is a coarse-grained bias of all results toward what you generally seem to enjoy.
This problem is worse if the profiles are not updated in real time. This tidbit from the Bigtable paper suggests that the profiles are generated in an offline build, meaning that the profiles probably cannot adapt immediately to changes in behavior.
See also my earlier posts, "Google Bigtable paper", "A real personalized search from Google", and "More on Google personalized search".