From Paul Graham's recent post

I think you should say "College is where faking starts to stop working."

This statement is up for interpretation. But I at least think I understand the gist.

I've always been fascinated with academia at least partially for this reason, and I've noticed a progressing desire as I age to be in environments where “faking it” is less and less tolerable. Microsoft is certainly more of a meritocracy, most academic organizations even more so. (Although, from what I hear, tenure tends to spoil this effect in many cases.) I spend countless hours of recreational time in order to improve my own thinking, mostly by studying formal theories and interesting works, but also through exercises such as writing compilers and learning new programming languages and ideas. It frustrates me to no end when somebody can get by, not on the merit or accuracy of their ideas, but rather due to politics or the networking effect of a bunch of fakers who can't recognize the difference.

But I am also very cognizant of what I do not know or understand. This, I think, is equally as important to knowing a lot. Well, at least in a person interesting in contributing at least one idea of importance to a field. Interestingly, Simon makes this same point in his “how to write a good research paper” talk referenced here. He advises that the process of understanding what you do not know helps you to better focus your research activities to fill in the gaps. I couldn't agree more. (In my limited experience.) The sooner you identify these areas, the sooner you can make progress.

I also find it interesting that, through the act of filling knowledge gaps, the foundational knowledge built up in your head seems to shift, sometimes causing other areas to become obsolete. This tends to create new gaps which need to be re-filled in the context of the new shifted foundation, but also creates new and interesting connections and clarifications on previously faulty mental models (which you might have thought were accurate, and which still likely aren't). But it's a beautiful, iterative process. No room for faking. And it certainly never ends.