Non-technical books for technical people
No, this is not a productivity post!
It’s a short list of books that can widen your perspective as a tech worker. They won’t directly teach you how to communicate better with your manager, or how to design a scalable distributed system. But, read over some tea on a weekend, they could make you see your work differently.
Atlas of AI by Kate Crawford
As tech workers, we spend our days peering at computer screens. We stare at code and analyze neat squares of data. We have ergonomic chairs and air-conditioned offices! But, as Kate outlines in this book, the AI industry is not only algorithms and programs whirring on machines.
“AI is neither artificial not intelligent. Rather, artificial intelligence is both embodied and material, made from natural resources, fuel, human labour, infrastructure, logistics, histories and classifications”
Kate forces us to look up from our screens and consider the AI industry as an extractive one, one that extracts, literally, minerals from the earth to build computing machines, human knowledge as data to train models, and messy human preferences to build classification models that represent a stripped-down version of how humans experience music, books and social connection.
We are taken on a tour of the lithium mining pits in Nevada being stripped to provide rare metals to build computers, the “long-corridors of energy-devouring data centers, skull archives, image databases and the fluorescent-lit hangars of delivery warehouses”. For someone who’s interaction with a data center is pressing “Start” on a cloud instance to run a machine learning model, the book is an eye-opener.
Given the breadth of this book, the “atlas” in the book’s title becomes a image that organises the books information. Each book chapter is meant to connect to the others to form a map of the AI industry. These accounts cover the “extractive mining that leaves an imprint of the planet, the mass capture of data, and the profoundly unequal and exploitative labor practices that sustain it”. It’s a wide-ranging set of settings, and it forces the reader to consider more closely the “physical infrastructure, social values and power dynamics” that influence the AI industry.
When this book was published in 2021, some practices in the tech industry, such as using classification algorithms for social justice or using employing low-wage workers for data labelling tasks, were still not as widely discussed or as regulated as they are today. We’ve made progress between 2021 and now. But although we are now more aware of these realities, the industry is still young, and this books offers a great way to think about the challenges ahead.
The Real Work by Adam Gopnik
A tech worker is always paddling against an incoming tidal wave of information. Every week there is a new Large Language Model released. Every week a new technique to improve Retrieval-Augmented Generation is published. Keeping up with the news to stay relevant is half our jobs. Then, the other half of the job is getting better at what we already know. Coding, a main way we express our ideas to a computer, is a craft that needs to be honed deliberately. We are always faced with the question of how to improve and maintain mastery.
And mastery is precisely what Adam Gopnik writes about in The Real Work, though not in the way that you might think. How to cultivate mastery is already extensively covered in books like Timothy Gallwey’s “The Inner Game” series. What Gopnik does, in contrast, is take us through examples of every day mastery that are commonly overlooked, and to draw out the poetry in the mundane.
My favourites are his accounts of his mother and his wife baking bread, of his attempts to learn to dance with his daughter, and his experiences learning to drive.
None of these activities are very remarkable. Most people can do these things every day without much thought. Certainly someone who kneads a good sourdough is not at the level of someone winning an Olympic medal or writing a seminal research paper. But this is entirely Gopnik’s point — there is “accomplishment” (getting a good grade on a music exam), and there is “mastery”, which is feeling like what was devilishly hard to do before, like make a sound on a flute, suddenly feels easy. The first relies on external measures of achievement, and the second involves a more internally-focused way of transcending one’s former limitations.
Gopnik does not offer any instructions or self-help tips in this book. But he does approach mastery as something poetic, fulfilling and uniquely human. Mastery is not only a “sign of skill”. When appreciating mastery, we also “search for the signs of a unique human presence: it’s why we love vibrato in a voice, legato in piano performance, why we catalog the tics and mannerisms of a baseball player at the bat”. Mastery is not only a means to recognition, achievement, and status. it’s also something worth pursuing for its own sake.
I’m going to keep these descriptions in mind the next time another article about “the 5 ways to progress to staff engineer” pops up.
For a summary, The Atlantic published a great article here.
The Lifecycle of Software Objects by Ted Chiang
This is a short story more than a book, but it’s quite profound. In this book, the two main characters are employees at a computer that builds digital pets. The protagonist, Anna, develops a close relationship with one of the pets, Jax, and is faced with a dilemma when the company creating the pets, Blue Gamma, is shut down. The digital pets no longer have a home on the internet, and Anna and other digital pet owners have to make some tough decisions on whether and how to sustain these “beings”.
There are so many ethical threads to this story and no answers, which is precisely why it’s such a good read.
A summary of the short story can be found here
