A book from 2007, about the positive and negative sides of diversity in human groups. The main focus is on the diversity of perspectives and heuristics, NOT identity diversity like race or gender.
The central point of the book is "The Diversity Trumps Ability Theorem" that applies to problem solving by groups. Roughly, it says that given the problem is difficult and the problem solvers are not stupid and no solution except the global optimum is a local optimum simultaneously for every individual in the group and both the initial problem solver population and the selected group are large enough, a randomly selected collection of problem solvers should outperform a collection of the best individual problem solvers. In the model that Page gives, the diversity always trumps ability, given those four conditions hold, but the book also describes how various human factors may make the theorem not work in some cases.
There's also "The Diversity Prediction Theorem": Given a crowd of predictive models, the Collective Error = Average Individual Error – Prediction Diversity. Here a group of randomly selected predictors does not necessarily predict more accurately than a group of the best predictors.
The discussions in the book are well supported with mathematical / computer models (though details are left to referenced papers, keeping the text easy to read), and while it is in general pro-diversity, it is NOT slogan'ishly pro-identity-diversity, but instead specifies what kind of diversity is good in which situations, and what are the accompanying costs that may sometimes cancel out the benefits.
For me, the book was quite an interesting read.
More info at Amazon: http://www.amazon.com/dp/0691128383 and at Princeton University Press: http://press.princeton.edu/titles/8353.html
