The best books about algorithms for people who don’t know anything about algorithms

John MacCormick Author Of Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today's Computers
By John MacCormick

The Books I Picked & Why

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

By Cathy O’Neil

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

Why this book?

This is the original and the best deconstruction of algorithmic bias, written by an insider who has seen firsthand how the sausage is made. As a pure math professor turned hedge fund quant, Cathy O’Neil has the tools to rip open algorithmic cans of worms, from financial crises to college admissions. Paradoxically, she does this with equal measures of gusto and clarity, making this the most fun depressing book on my bookshelf.


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The Thrilling Adventures of Lovelace and Babbage: The (Mostly) True Story of the First Computer

By Sydney Padua

The Thrilling Adventures of Lovelace and Babbage: The (Mostly) True Story of the First Computer

Why this book?

A graphic novel about Ada Lovelace, Charles Babbage, and their quixotic Victorian escapades designing computers and algorithms nearly a century before their time? As fascinating as that may already sound, it’s only the beginning. This is the only graphic novel I’ve read that has footnotes to the footnotes—immensely amusing footnotes. While reading this book, I feel constantly in the presence of insane genius. (But please read this book on physical paper. It is a work of art.)


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Algorithms to Live by: The Computer Science of Human Decisions

By Brian Christian, Tom Griffiths

Algorithms to Live by: The Computer Science of Human Decisions

Why this book?

I like to think of this book as the Thinking Fast and Slow for computer science and algorithms. Danny Kahneman’s Thinking Fast and Slow taught us how to apply ideas from psychology to our own lives. Christian and Griffiths do the same thing for algorithms—it’s what they call “human algorithm design”. I was amazed at how much I learned from this book, even after I had been teaching college computer science for years and writing books about algorithms myself.


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The Golden Ticket: P, NP, and the Search for the Impossible

By Lance Fortnow

The Golden Ticket: P, NP, and the Search for the Impossible

Why this book?

The most important unanswered question in computer science has a huge public relations problem. Back in the 1970s, this question became known as “P=NP?”—and who could write an exciting book about that? Luckily for us, Lance Fortnow can. As one of the world’s foremost experts on P-vs-NP, he takes us on a wild and truly accessible ride through the most important question about computing. I’ve seen many attempts at making “P=NP?” accessible/understandable/intriguing for non-experts. But Fortnow nails it like nobody else, reformulating P-vs-NP as a search for one of the golden tickets in Charlie and the Chocolate Factory. (Which is another one of my favorite books, even though it’s not going to make it onto this list about algorithms.)


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Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World

By Leslie Valiant

Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World

Why this book?

In a world full of buzzwords about the latest AI algorithms, Leslie Valiant is one of the few authors who can shrug off the hype and deliver something truly profound. Valiant is a Turing Award winner whose work has changed the face of computational learning theory. His ideas show how algorithms can arise naturally, as part of evolution. (He calls them ecorithms.) These ideas are stunningly original. I admire Valiant’s no-nonsense prose style immensely—it’s such a pleasure to read something where the ideas and explanations are simultaneously so clear and so deep that they provide their own star power.


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