This was a very interesting but sometimes confusing read. I thought the topic was relevant to our current world but in order to understand some of it I was lost because the numbers just confused me.

I’m on the fence with this one. The subject matter is of interest to me, but the proto-dystopian view of data analytics is... difficult to parse. I don’t believe that what the author posits is untrue, but it does feel weighty on the side of unintended evils in technology.

Because of poor formatting, it took me a little over two months to get halfway through this book, and at this point, I think I need to cut my losses. Don't get me wrong--the concept here is fantastic, highly relevant, and the writing is a nice blend of technical, historical, and anecdotal. Sometimes it's a little overly technical, making me feel like I'm back in my Quantitative Methods or Algorithms courses in college, but it's understandable why Smith writes that way. This is a problem whose roots are, in part, based in the limitations of our math and machines, and we need to understand those elements to fully grasp the problems inherent in the system.

The problem is that this uncorrected proof is <i>so</i> uncorrected, it is incredibly difficult to read. Between misplaced and missing capital letters, random spaces missing, and casual typos, it is incredibly difficult to parse the text without extensive effort. This isn't just a standard case of one or two typos here or there; this is a case where nearly every sentence has an error. For a nonfiction book where this clearly isn't just a stylistic choice, especially one that is about building credibility and competency in our machines, it just doesn't work.

Having previewed the Kindle version of the book on its Goodreads profile, the final edit looks like it will be much better, and I'll do my best to get a copy of it when it publishes. Hopefully I can then fully appreciate what Smith has to say and provide a better analysis of the content, rather than just my gripes about poor formatting rendering it almost impossible to enjoy.

<i>I am not posting this review to my blog, as I do not think it is a full, fair assessment of the book. If I am able to read the book once it is better-edited, I will be sure to revise this feedback and post that review on my blog, as well as Goodreads.</i>

Rage Inside the Machine is a delectable blend of (what I like to call) armchair maths, history, autobiography, current events (and what led to them), cautionary tale, and call to action. As a computer professional, for lack of better parlance, this really spoke to me. The book is well-written, easy to follow, and balances hard science with soft entertainment, expertly. I highly recommend this to anyone whose life is affected by algorithms, that is to say, everyone. I plan to get a hard copy to reread at least a few times, as well as pursue some of the bibliography.

I simply could not get past the grammar errors and typing errors. This book leans so heavily on math and precision, but when the writing is done with little to know care, I have a hard time believing the math. Credibility matters and I feel that this uncorrected proof needed to be corrected before it was sent out. I kept trying to ignore it, but I simply could not. Once this is put out in August, I think I will pick it up and give it a try.

This book takes a little reading. Let me explain that sentence. This book is written by a computer engineer so he is very attracted to numbers and formulas. There are a lot of these in this book. However when you get past all of it the message is a very good one on human interaction and bias.