By: Eric Siegel, Founder, Predictive Analytics World

Originally published in Analytics Magazine

Book: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O'Neil (Crown, September 2016)

Book review bottom line: Definitely go read this book, despite the fact that it does convey a certain oversimplifying, "black-and-white" position.

Related reading: I devoted all of Chapter two of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (2013; 2016) to ethical issues that arise in predictive analytics’ deployment. Parts of that chapter, along with my article “The Risk of Prejudice in Computerized Prediction” in Profiles in Diversity Journal, cover some of the same topics of concern in Weapons of Math Destruction.

My Review of This Book:

Cathy O'Neil's New York Times Bestseller Weapons of Math Destruction belongs squarely in the "must read" category. In this first-of-its-kind book, the author, an industry insider and experienced expert, thoroughly covers the sociological downside of data science.

In the world of big data, there's a lot of music to be faced. With all its upside, data science's deployment risks being prejudicial, predatory, exploitative, buggy, blindly trusted, and secretive. And it has the potential to magnify the consumer’s personal economic struggle rather than remedy it.

These risks permeate across the field. The book's broad coverage includes examples from all the main business application areas to which predictive models commonly apply: marketing, online ads, credit scoring, insurance, workforce analytics, law enforcement, and political campaigns.

By providing such a uniquely comprehensive treatment of data's downside, this book addresses two dire needs: increasing awareness and opening the door to prolific discussion.

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Click here to access Eric Siegel’s full book review in Analytics Magazine (above are only the first four of the review’s 21 paragraphs).