Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

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Author: Cory Maloney
Date: Spring 2017
From: Journal of Markets & Morality(Vol. 20, Issue 1)
Publisher: Acton Institute
Document Type: Book review
Length: 1,447 words

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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

Cathy O'Neil

New York: Penguin Random House, 2016 (272 pages)

Weapons of Math Destruction exposes the tremendous power that data, the analytics of data, and the use of analytics yield over many aspects of our lives. Building on the shocking title, the author creatively uses the imagery of bombs, weapons, and war to organize the book and emphasize the real dangers of data analytics in our world.

The book begins with a chapter titled, "Bomb Parts," in which O'Neil describes the three measures she uses throughout the book to evaluate whether a data analytical system is a Weapon of Math Destruction (thematically abbreviated WMD) or is instead "benign." First, the more opacity a model has within it, the more dangerous it is. O'Neil considers opacity to be the level of transparency within the algorithm to those using it and affected by it as well as how accurately the statistics used in the analysis actually represent the desired outcome. Second, the larger the scale of the utilization and thus impact of the model, the more dangerous it is, simply because it affects more people. In addition, scale also includes the expanded applications of the model beyond its initial purpose. Third, the more damage a model has caused or has the potential to cause increases the likelihood of its diagnosis as a WMD. Within the analysis of the damage caused, O'Neil considers who exactly is hurt by the model and especially weighs the impact on vulnerable populations such as the poor or minorities. These three measures are best understood when operationalized in the dozens of examples presented in the subsequent chapters, of which we will explore several to get the gist of the dangers.

The sport of baseball is filled with statistics, statisticians, and sophisticated analyses that drive decisions in nearly every aspect of the sport. Baseball teams today rely heavily on these analyses to determine which players to draft, to retain, and to trade; where to position their defenses against various batters; which pitcher to start or bring in depending on the game, inning, upcoming batters, and so forth; and...

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