Chad Kohalyk's Reviews > Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

Weapons of Math Destruction by Cathy O'Neil
Rate this book
Clear rating

by
3079724
's review

liked it
bookshelves: audio, general-nonfiction

Solid overview of the various mathematical models that govern our education, labour, wealth, and commerce. O'Neil packs in many examples and unpacks how simplistic, unfair and damaging to already disadvantaged people these models can be. As someone who worked on the front lines of developing models for predictive internet shopping, I was familiar with many of the tactics mentioned in this book, and their ethical shortcomings (which finally led to me leaving the business). What she says is entirely true, and it makes a small amount of people a lot of money. More people should be outraged. This book could help.

There are two shortcomings, though, both possibly due to its short length. First, there is no discussion at all of government abuses of all the data collection detailed within its pages. Maybe in the age of Snowden this is just assumed, but I think it is an important outcome of the big data revolution that should at least be addressed, even in passing. Secondly, I was hoping for more imaginative solutions. The "hippocratic oath" for data scientists she refers to is a nice idea... from twenty years and two big economic recessions ago. Advocating for stronger regulation is certainly prudent. However, I was hoping for something new.

Weapons of Math Destruction is a well documented tour of the standard examples of the misuse of math and big data, and concludes with the standard solutions. A good book to recommend to friends who need a primer on these issues that we have been facing for the last decade or so.
13 likes · flag

Sign into Goodreads to see if any of your friends have read Weapons of Math Destruction.
Sign In »

Reading Progress

September 24, 2016 – Started Reading
September 24, 2016 – Shelved
September 24, 2016 –
18.0%
September 28, 2016 –
34.0%
September 30, 2016 –
55.0%
October 1, 2016 –
87.0%
October 2, 2016 – Finished Reading

Comments Showing 1-1 of 1 (1 new)

dateDown arrow    newest »

back to top