2016: Books of the Year

I didn’t do as much reading as I would have liked in 2015 – It was a roller coaster of a year for many reasons, and at the end of last year, I felt muddled and a little out of sorts. I don’t consider myself a big believer in New Year’s Resolutions, but at the start of 2016 I did make one pledge to myself. I decided to start taking reading seriously again, and to make time to read wholeheartedly every day. I also set a book count goal. We’re nearing the end of the year, and, while I didn’t meet my book count goal, I think I did an alright job.
The renewed focus was good for me: at the end of 2016 I feel more curious and more well-rounded. I’m thinking more clearly, and I’m feeling more reflective. In that spirit of reflectiveness, I present Ryan’s Super Official Top Three Books of 2016. These aren’t necessarily the best (what does that mean, anyway?) books I read this year, but they are the three books that had the most profound impact on me this year. I often find myself thinking about them or referencing their core ideas. They all get an official recommendation from me.

Book 1: The Limits to Growth: The 30-Year Update by Donella H. Meadows, Dennis L. Meadows, Jørgen Randers
The Limits to Growth was originally published in 1972 by a team of scientists and environmentalists from MIT. The authors have published updates every 5-10 years since. The basis of the book is a computer model that the authors designed (“World3”) which was used to run some simulations of the future of our planet. The authors come to some harrowing conclusions about civilization’s consumption of resources and stewardship (or lack thereof) of the planet. This book stands out to me this year for three reasons:

  1. This is one of the most cogent descriptions of systems-thinking I’ve ever encountered. The authors provide a clear and concise overview of the fundamental tools in systems, and then they use those tools to assemble the World3 model.
  2. It’s data-rich – the authors are transparent and detailed when it comes to the data they use in this book.
  3. While the authors are clearly raising alarms, they also lay out options and maintain a sense of hopefulness. They are also honest about their predictions – the point isn’t to predict the future with certainty, it is to understand the landscape of possible futures, and use that to find points of leverage to make meaningful change.

If anything, this is a terrific reminder that many of the problems facing us are complex, and our tendency to gravitate toward the “simple” solutions can be to our detriment. Understand the system, and find the leverage points.

If you would like a fairly technical read on sustainability or just a top-notch case-study in systems-thinking, then I’d highly recommend this book.

Book 2: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil
Ah, the only new release on the list. This book came into my life at an opportune time. In the last year or two I’ve been thinking a lot about the role of technology (and a tech worker like me) in a just society. In Weapons of Math Destruction, Cathy O’Neil lays out a framework for evaluating the use and misuse of Big Data and mathematical modeling, and presents case studies on how seemingly “objective” uses of data can worsen inequality.
O’Neil’s definition of a Weapon of Math Destruction (WMD) has three components: a WMD is opaque to the people impacted by it, it operates at a large scale, and it does harm. It’s not an explicit part of the definition, but she also spends a great deal of time discussing the danger of pernicious feedback loops. As someone who works with a giant pile of data every day, this is a useful framework for thinking about the ethics of my work. (In fact, I thought it was so appropriate I re-started the company book club to discuss this book)

Some highlights:

  • Every model is an approximation of reality. Models are built on a giant pile of assumptions (and those assumptions often prove false). Our tendency is to take a model as The One Objective Truth because its output is numerical. O’Neil demonstrates that in many cases, models only serve to encode our biases. For example, Medical School admissions software that “learned” to discriminate by race.
  • Beware the feedback loop. When the thing we’re trying to measure is influenced by the model, it can lead to self-fulfilling prophecies. For example, the misuse of predictive policing software can lead to the appearance of increased crime; or using credit scores in job screening can lead job-seekers further into debt.
  • The nature of big data means wealthy people are increasingly “handled” by another human being, whereas the poor are “handled” by a computer.

This is not a math book. The author has a PhD in mathematics so I’m certain she could’ve written it that way, but you don’t need any advanced math training to understand this book. It’s also not a hardcore technology book – you don’t need to be a computer scientist to enjoy this book. It’s an easy read that you could get through in a few days.

I’ll provide two criticisms: I wish the sources were better-cited, and some examples seemed to be cherry-picked. However, I wouldn’t let that detract from the usefulness of this book. It’s a much-needed pop-sci look at a very important topic. I recommend this book for anyone who works in or around technology, or who is interested in the intersection of social justice and technology.

Book 3: Justice as Fairness: A Restatement by John Rawls
I can’t imagine why anyone ever would, but if you were to ask me what “school” of political philosophy I subscribe to, I would tell you that reality is very messy and dogmatic adherence to any particular philosopher’s work would make me a fundamentalist. If you insisted, I would probably say I am broadly Rawlsian.

Justice as Fairness: A Restatement is a more concise version of the argument he laid out in an earlier book (A Theory of Justice), that also includes responses to some criticism. Rawls’s theory of justice is based on the following:

  1. We’re all born into political society without much (or any) say in the matter, so a just society should provide ample opportunity to every person, regardless of the circumstances of their birth.
  2. Rawls is a social contract theorist, meaning that a just society is one that’s constructed by broad agreement of people. Since every citizen didn’t actually get together and sign a contract before creating Society, he does a thought experiment around what sort of social contract people would agree to from what he calls “The Original Position”. Basically, if a group of rational people representative of the world’s diversity were asked to design the structure of society before being born and without knowing anything about their upcoming lives (race, gender, class, intelligence, etc.), what would those rational people agree to? Rawls contends that they would choose to design a society based on egalitarian principles. This is a really useful thought experiment – I’d encourage you to do it now and then with your political positions.
  3. There are some basic liberties that every person should be entitled to. A few of those: freedom of speech, freedom of conscience, freedom of personal property, and a few others.
  4. Rawls does not protest all inequality, but states that any inequalities in the system must satisfy two criteria. First, there must be equal opportunity (as in the first point). Second, they must satisfy what he calls “The Difference Principle”: we should only permit inequality in the basic structure of our society if it is to the benefit those who are least-advantaged.

Rawls then uses his framework to evaluate a few systems of government. He ends the book on a hopeful note: this is not pipe-dream utopian thinking, he says, but a tractable direction. This book is great because it provides a lot to chew on – even if you ultimately disagree with Rawls’s theory, it provides a useful framework for thinking about how to design a just society. Perhaps most importantly to me, while Rawls is an academic, his work is broadly applicable to many of the policy questions we think about every day. This is not an easy read – Rawls is a philosophy professor and writes like you’d expect a philosophy professor to write. You may need a quiet room, a notepad, and a highlighter to get through it. But if you want to dig into political and moral philosophy, he’s essential.

Honorable Mention: Waiting for Godot by Samuel Beckett. This was my second reading of this book. Summarized in a quote:
Estragon: I can’t go on like this.
Vladimir: That’s what you think.


What books stuck out for you this year?


If you’re interested in any of the other books I read this year, you can check out my Goodreads profile.

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