2017 Reading List

I've been reading a lot during my commutes this year, and I thought I'd summarize some of my thoughts about the books I've read and how much I enjoyed them.

Subliminal: How Your Unconscious Mind Rules Your Behavior by Leonard Mlodinow - 4/5
This was a fun read. Lots of examples of how unconscious decisions are actually more prevalent than most people realize. This was particularly interesting as I've been thinking more about unconscious bias lately. This book got me thinking about data-driven approaches to quantify bias (both conscious and unconscious), but it is obviously tricky to define the correct loss function to train this model.

But What If We're Wrong? by Chuck Klosterman - 2/5
Not sure if I got the point of this book (to be fair, the book did warn me that this might happen at the beginning). I thought the book was about politics (the back of the book mentions the president), but what I remember of it was mostly about pop culture and philosophy. Still, it's good to be reminded periodically to try to think how others feel in a two-sided political situation.

Dune by Frank Herbert - 1/5
Couldn't really get into this book. I thought the world was not particularly interesting and apart from a few events early on, I found the story a bit slow.

Data for the People by Andreas Weigend - 5/5
Full disclosure, Andreas is a friend of mine so it's hard for me to be objective about this book. I think Andreas discusses interesting ideas on the trade that users have with a company, that is giving up some of their privacy in exchange for better services from the company. I worry though, that the ideas are hard to implement without an external body to enforce it. There are many fun stories about data to tie all of these ideas together.

Hillbilly Elegy by J.D. Vance - 3/5
As the author of this book is a successful lawyer who grew up relatively poor in the rust belt, the author is the ideal person to translate the ideals of the working class to city dwellers. This book is mostly about the life of the author but touches on religion, family values, and the hillbilly lifestyle that contributed to his worldview. I felt like this definitely helps contextualize some of the voting patterns that I see in the U.S.

Weapons of Math Destruction by Cathy O'Neil - 4/5
Definitely some good lessons on how defining metrics is key and how, without retraining, models can get gamed and not serve their intended purpose. I feel like there were a lot of ideas and guidelines for preventing dangerous models, but without an enforcement mechanism, I'm unsure if any of the ideas can come to fruition. I'm always advocating for data-driven solutions to problems, but this book has made me consider that models have to be cautious, especially when biases can be involved.