Recommendation lists….C’mon isn’t the world of Data Science filled with them? 

Bear with me reader, we need to discuss this. 

Being a good data scientist means more than just the maths and programming. We should strive to improve ourselves in what regards to communication skills, decision making skills and knowledge about the effects of our work in the world in which we work on. Non technical books can help fill this gap and play an important role in the development of an awesome data scientist. 

This little list isn’t extensive, there might be more awesome suggestions (send them to us) well worth to add to it, but here is a beginning list of really good non technical books that will help you improve and gain a new perspective on the area. Let’s just start with 4 awesome books. 

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World – Pedro Domingos

Let’s begin with an awesome example written by the awesome Pedro Domingos. Wanna understand the evolution of AI and how the algorithms ended up divided into “sort of” competitive classes? Wanna learn about the history of AI including the crazy and weird ideas? 

Pedro Domingos, with true impassionate portuguese blood, takes us on a journey to discover where the master algorithm, the one able to learn it all, might come from. For us data scientists, it is a lesson on how to take data science to the general public, masterfully written. Want a peak? Check his talk at google here ; 

Factfulness: Ten Reasons We’re Wrong About the World–and Why Things Are Better Than You Think – Hans Rosling 

Who hasn’t seen the late Hans Rosling TED talk yet? Why are you wasting your time? Go see it !  

Hans Rosling was an awesome statistics teacher at the Karolinska Institute in Sweden, where he revolutionized the world of statistics applied to health. In his funny demeanour and blunt way of speaking, his book takes us through the health statistics during the 20th century and to the realization that the reality regarding health and life expectancy is way better than what we think.

In an easy tone Hans teaches us how data has to be properly treated to effectively pass the correct information to the public and how bias often get us stuck. Data visualization lovers, this is the book for you. 

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy – Cathy O’Neill

This one might be scary to read but it’s also very true. Cathy, through the lens of a normal person’s day to day life, analyzes in depth the influence that algorithms have in our lives, most https://console.cloud.google.com/compute/instances?project=twitterapptest-219618of them without us even realizing it. Cathy is slightly cold (sometimes a little bit panicky) but her book is a cold read on a world full of technology. For us it is important to understand the possible outcomes of the work that is done at universities or on the industry. 

1984 – George Orwell 

“huhhhhh….is really Susana adding this one to the list?” Some of you might think. Yep, I am. 

1984 is a cautionary tale above all, and remains relevant to this day. While being a dystopian reality, George Orwell is able to set a plausible future in a world where totalitarianism exists due to the state tracking every single movement of its citizens. We are already living in partial “1984” realities such as the China Social Credit Score. A lot of the totalitarianism defined in 1984 is allowed due to technology and facing this dystopian novel will allow us to consider the outcomes of our work. It’s a hard read, but it’s really an important one. 

What about you? Which suggestions of non technical books do you have that can improve the lives of your fellow data enthusiasts ?