Why is controlling for too many variables considered harmful? I am trying to understand the point of the second panel in the following xkcd comic:

Specifically, how can one be misled by controlling too many confounding variables in one's models?
Any pointers to what this criticism is called in the literature—so I can look into it further—will be appreciated.

The term you are looking for is overfitting.  Wikipedia has a good explanation.
