Reformers concerned about the rise of partisan polarization often advocate reforming institutions, reducing the influence of political actors believed to have a polarizing effect on politics, or simply adopting a cynical “throw the bums out” mentality. In this chapter I propose that, rather than seek to improve our institutions, we seek to inform and empower voters by combining recent advances in political science and technology. Just as Amazon has made smarter consumers and Netflix has made it easier to discover movies and television shows we like, data and technology can similarly transform the political marketplace. The marvels of the big data revolution that helped campaigns learn about voters and to predict their behavior have been widely lauded following the 2012 elections. However, I believe that the true potential of the big data revolution for politics will be realized by harnessing its power to help voters learn about candidates in an engaging and efficient way.

Much of the unease concerning the rise in partisan polarization relates to the perceived incongruence between the ideological extremity of elected politicians and the relative centrism of the electorate they are sent to represent. Although the mass public has become more polarized in recent decades, it has done so much more slowly than politicians (Fiorina, Abrams, and Pope 2005; Theriault 2008; Abramowitz 2010). This disconnect has fueled concerns about the health of our democracy and that broken electoral and representative institutions have prevented voters from electing the types of representatives they want or deserve. However, others push back, arguing that a flawed electorate, rather than flawed institutions, is to blame.

Scholars have struggled to reconcile the disconnect between the ideological dispositions of voters and those of the politicians elected to represent them. This debate has identified two general lines of explanation, one relating to candidate entry and the other to voter competence.