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The diversity bonus : how great teams pay off in the knowledge economy
Page S., PRINCETON UNIVERSITY PRESS, Princeton, NJ, 2017. 328 pp. Type: Book (978-0-691176-88-8)
Date Reviewed: Oct 15 2018

Diversity, perhaps appropriately, means different things to different people. To some it is a quasi-religious norm and a central motivation in political discussions and policy debates. To others, such as cognitive scientists and experts in machine learning, it refers to combining multiple algorithms to solve a problem. As a political scientist with a strong bent to mathematical modeling and complex systems, Scott Page has long been interested in formal characterizations of diversity [1,2]. This volume brings together theoretical results on the benefits of diverse teams, empirical evidence for those benefits in actual case studies, and discussion of the relations between different kinds of diversity.

The series in which this volume appears, “Our Compelling Interests,” is focused on diversity as a moral norm for a heterogeneous society. “Diversity” in this context refers most naturally to “identity diversity,” characterized by Page (p. 133) as “differences in race, gender, age, ethnicity, religion, physical qualities, and social orientation,” and is often promoted ideologically. In his opening chapter, Page makes clear that his focus is on “cognitive diversity,” differences in the mental toolboxes that people bring to interpreting data, reasoning about it, and solving problems. These toolboxes include a variety of information, knowledge, heuristics, representations, and mental models (or frameworks). His theoretical and empirical results show that cognitive diversity offers benefits (a “diversity bonus”) over cognitively homogeneous teams for non-additive tasks. An additive task would be one in which productivity depends simply on the number of people doing the work. Doubling the number of house painters should enable a painting company to paint twice as many houses in a given period of time, no matter how diverse or homogeneous the painters are. Similarly, in the days before digital computers, rooms full of humans performed ballistics computations, and twice as many people could compute twice as many trajectories, regardless of their diversity. The benefits of cognitive diversity are in cognitive (rather than manual) tasks that are non-routine. In other tasks, one does not expect a bonus from diversity.

Cognitive diversity is not identical with identity diversity. But throughout the book, Page seeks to show ways in which identity diversity may enhance cognitive diversity and thus bolsters ideological arguments for promoting identity diversity with the argument for a (cognitive) diversity bonus. The last chapter’s commentary by Katherine Phillips goes further, arguing on psychological grounds that identity diversity leads to improved team performance even if it does not contribute to cognitive diversity.

After an introduction by Earl Lewis and Nancy Cantor, series editors, and a prologue summarizing Page’s experiences in dealing with diversity in organizations, the first chapter sketches how cognitive diversity works. Chapter 2 presents a model for the cognitive repertoires in terms of which cognitive diversity is defined, while chapter 3 explains the theoretical logic that yields bonuses. Chapter 4 grapples with the question of how cognitive and identity diversity interact. Chapter 5 presents empirical evidence for the benefits of diversity, and chapter 6 relates this evidence to the broader business case for diverse organizations. Chapter 7 discusses mechanisms to promote diversity in organizations.

Page’s theoretical arguments are of interest to computer scientists and cognitive scientists interested in the benefits of heterogeneous reasoners (for example, in ensemble learning), and he discusses examples such as the Netflix Prize to show the gains offered by such architectures. His recurring engagement of the relation between cognitive and identity diversity will be of interest to a much wider range of readers, who will find the book engaging and highly readable.

One question is touched on only tangentially, and merits much deeper discussion. Page makes clear that some tasks do not benefit from diversity. Conversely, some forms of diversity cannot help with any task. Page repeatedly emphasizes the need for a common mission and vision across a team. But the identity of some groups includes rejection of a heterogeneous culture. Far from being surprising, this characteristic is a predictable endpoint of the documented homophily among members of an identity group (p. 144), amplified by the dynamics demonstrated in Schelling’s segregation model [3]. Including members of such groups in diverse teams is a recipe for disaster. Does achieving the business benefits that Page promotes, and the social benefits that the book’s series envisions, require discriminating against such identity groups, in direct contradiction of the broader diversity mandate? This “diversity paradox” seems to be related to other fundamental paradoxes in mathematics, such as Russell’s paradox in set theory or the behavior of self-referential statements at the root of Gödel’s incompleteness theorem. A formal characterization of this phenomenon would, like Page’s bonus-based arguments, help move discussions of diversity from ideological debate to rational principles that allow discussion, exploration, and progress.

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Reviewer:  H. Van Dyke Parunak Review #: CR146280 (1812-0628)
1) Page, S. E. The difference. Princeton University Press, Princeton, NJ, 2007.
2) Page, S. E. Diversity and complexity. Princeton University Press, Princeton, NJ, 2011.
3) Schelling, T. C. Dynamic models of segregation. The Journal of Mathematical Sociology 1, (1971), 143–186.
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