The dark side of data analytics

Data analytics and especially Big Data has been a hot topic for a while now and many good things can be done with it. However, if we use them inappropriately, we cause more harm than good. Unfortunately, this is more common than most people think because a lot of people get intimidated when they see numbers and complex formulas, if they see the formulas at all, and believe the number for the sake of the number.

The book “Weapons of Math Destruction” from Cathy O’Neil explores and describes the danger that lies in the inappropriate use of data and analytics. She earned a Ph.D. in mathematics from Harvard and taught at Barnard College before moving to the private sector, where she worked for the hedge fund D. E. Shaw. She then worked as a data scientist at various start-ups, building models that predict people’s purchases and clicks. Cathy is a data scientist and also the author of the blog

From the Book

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated.

But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.

Tracing the arc of a person’s life, O’Neil exposes the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.

Even if you don’t have a background in analytics I highly recommend you check out this book. NPR also did a short interview with the author, which you can find here.

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