Algorithmic lens in the social sciences Looking at questions through the algorithmic lens (i.e. from an algorithmic or complexity point of view) has become useful in disciplines outside of the 'standard domain' of computer science. In particular CS has made an impact on biology through computational biology, on physics through quantum information processing, and AI and complexity theory seem to regularly interact with neuroscience. The natural sciences seem relatively comfortable with TCS.

Thus, my question is in regard to the impact of TCS on the social sciences.


  What novel and important insights into the social sciences has TCS provided?


I am vaguely aware of the impact of algorithmic thinking on economics (through game theory). In fact algorithmic game theory is now a part of the 'standard domain' of TCS, so lets exclude AGT answers unless they specifically altered existing theories in the social sciences. 

Another example I recall is from linguistics in the learnability vs. innateness of grammar (i.e. poverty of the stimulus) debate. Gold's theorem about the unlearnability of context free grammars provided a strong argument for innate-ness and helped convince some skeptics (I am not sure if this is still valid, since SCFG seem to be learnable). I am more interested in examples of this type, where TCS thinking helped change or shape existing theories in the social sciences.

References to books/surveys are appreciated.
This example is from social choice theory, and elections in particular. We know that Arrow's theorem (and the Gibbard-Satterthwaite theorem in general) rule out the possibility of elections that are fair, non-manipulatable and without other bizarre consequences. But a seminal paper by Bartholdi, Tovey and Trick showed that finding the desired 'hack' to break a voting scheme was NP-hard, and there's been a large body of work by many researchers on the complexity of problems in the realm of election design. There's a nice survey by Faliszewski, Hemaspaandra, and Hemaspaandra on this topic.