This is a book all about the negative side of big data. The book gives numerous examples of people making decisions based on how it effects a ranking on an algorithm rather than the human beings it effects. The author has a Ph.D. in mathematics from Harvard University and has worked as a quant, short for quantitative analyst, on wall street and well as a researcher in the math department of MIT. As you can imagine, she has worked on algorithms from both the academic and financial side of the world and knows what she is talking about.
The best example that the author gives in the book was about the US News College Ranking. This is an annual ranking of the best colleges in the nation according to an algorithm determined by the magazine US News. Before the publication of the initial list in 1983, US News was known as a second-tier magazine like Time or Newsweek. This list gives a lot of power to an otherwise insignificant magazine.
This list is important enough that colleges often make decisions based on how it will affect their ranking on this list. One of the things this list takes into consideration for the rankings is the rejection rate of accepted students. As a result, lower-tier colleges, otherwise known as safety schools to top students, have started filtering out the very best students because they very rarely attend a so-called safety school. This results in an improved ranking because less students are rejecting their acceptance to the school, but it also results in some potential students getting rejected as well due to overzealous rejections by the college. This was just one example of the effect this ranking has on the colleges decisions.
Another example used in the book is the practice of using personality tests to filter out people for jobs based on their mental health, which is borderline illegal because you cannot deny someone a job based on their health. This was illustrated by the story of a college student that could not get a job anywhere because all entry level jobs in retail or customer service include a personality test.
It was surprising to me that there was not a ton of discussion of the big technological companies such as Facebook, Google or Amazon. I was expecting a lot of discussion about these companies in this book because the topic is highly relevant to the general business practices of those companies.
I enjoyed listening to this book because it shows very clearly the negative effects of having so much of our lives helped by algorithms. I would suggest this book to anyone that enjoys mathematics. I do want to make clear that there is no discussion of algorithms in the book that require any deep understanding of mathematics to understand. I placed this book on level 3.