How Algorithms Impact Our Daily Lives
4 Data Science books that studied these sociological impacts
Data science has gained much deserved popularity and utility. Yet it’s also probably the least understood by an average person. So for anyone hoping to learn more, here are some of the best data science books.
This reading list ranges from technical machine learning, math textbooks, and sociological studies of how algorithm impact our daily lives.
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz
This is a fun read. Every chapter tells a story illustrating a data science concept — like, from Google Searches, news, about image data, etc.
People frequently lie — to themselves and to others.
In 2008, Americans told surveys that they no longer cared about race. Eight years later, they elected as president Donald J. Trump, a man who retweeted a false claim that black people are responsible for the majority of murders of white Americans, defended his supporters for roughing up a Black Lives Matters protester at one of his rallies, and hesitated in repudiating support from a former leader of the Ku Klux Klan. The same hidden racism that hurt Barack Obama helped Donald Trump.
Netflix learned a similar lesson early on in its life cycle: don’t trust what people tell you; trust what they do.
Naked Statistics: Stripping the Dread from the Data by Charles Wheelan
This book gives a lot of examples of how statistical concepts apply in the real world.
It’s easy to lie with statistics, but it’s hard to tell the truth without them.
…one of the most important things to remember when doing research that involves regression analysis: Try not to kill anyone. You can even put a little Post-it note on your computer monitor: “Do not kill people with your research…
…Fire, knives, automobiles, hair removal cream. Each of these things serves an important purpose. Each one makes our lives better. And each one can cause some serious problems when abused. Now you can add statistics to that list…
— Charles Wheelan
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil
This book is a collection of stories of algorithms’ real-world applications their inefficacies, and suggestions on how to improve them.
Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide. We have to explicitly embed better values into our algorithms, creating Big Data models that follow our ethical lead. Sometimes that will mean putting fairness ahead of profit.
— Cathy O’Neil
Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Noble
In this book, Safiya shares stories on “small data” with a lot of context.
…algorithmic oppression is not just a glitch in the system but, rather, is fundamental to the operating system of the web…
Google Search is in fact an advertising platform, not intended to solely serve as a public information resource in the way that, say, a library might. Google creates advertising algorithms, not information algorithms.
There is no algorithm that can replace human dignity. They created a system that simulates a value, based on their own algorithm…
— Safiya Noble
