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Algorithms to Live By: The Computer Science of Human Decisions

4.13  ·  Rating details ·  22,476 ratings  ·  2,132 reviews
What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of the new and familiar is the most fulfilling? These may seem like uniquely human quandaries, but they are not. Computers, like us, confront limited space and time, so computer scientists have been grappling with similar problems for decades. And the solutions the ...more
Paperback, 368 pages
Published April 6th 2017 by William Collins (first published April 19th 2016)
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Stephen Hendrickson classic catch-22. you need to listen to the book to develop the skills needed to determine whether or not to listen to the book. (so far, i really enj…moreclassic catch-22. you need to listen to the book to develop the skills needed to determine whether or not to listen to the book. (so far, i really enjoy it but i'm not 37% of the way through.)(less)
Weltengeist If I was you, I would look for books that come under the heading of "Computational Thinking". Of course, it depends a bit on what you liked about the …moreIf I was you, I would look for books that come under the heading of "Computational Thinking". Of course, it depends a bit on what you liked about the book, but examples might include:
- Martin Erwig: Once Upon an Algorithm (if you're more into examples on how to apply algorithms in everyday life)
- Paul Curzon, Peter W. McOwan: The Power Of Computational Thinking (works mostly with examples, puzzles and games)
- Karl Beecher: Computational Thinking (somewhat more technical)

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B Schrodinger
This is one of those books that you pick up in the hope that it lives up to its title but is likely not to because it was written by someone from marketing. Every now and then it pays off, and this is one of those times.

This book spoke volumes to me. I have studied math, and I love math especially applying it to scientific problems. But I have never looked into algorithms, nor have I been taught algorithms. What a shame! I took to the ideas instantly and it all made complete sense - not only the
Brian Clegg
Apr 21, 2016 rated it it was amazing  ·  review of another edition
I was captivated by much of this book. It's the perfect antidote to the argument you often hear from young maths students - 'What's the point? I'll never use this in real life!' This often comes up with algebra (which often is useful), but reflects the way that we rarely cover the most applicable bits of maths to everyday life at high school. Although this book is subtitled 'the computer science of human decisions', it's really about the maths of human decision making (which is often supported b ...more
I enjoy thinking about algorithms as they are applied to technical problems. So, when I saw this book, I thought, "This is a book written just for me." And, that assessment was absolutely correct. It is a fascinating book, all about how sophisticated algorithms are applicable to everyday problems.

The book starts out describing the "optimal stopping problem." It is also sometimes called the "secretary hiring problem", and I have seen it applied to dating to find a romantic partner, and this book
Amir Tesla
Sep 04, 2016 rated it really liked it  ·  review of another edition
Recommends it for: Nerds, geeks, productivity lovers
Okay, I loved this book. So what is it about?

The big picture
We encounter many problems in our daily life, for instance, should I park my car here or proceed with the hope of finding a free spot a bit further? Should I try new restaurants or just stick to good old ones I know? How can I find my life's purpose? What is the fastest way I can sort out my books, hmmm, should I even try sorting out my shelves? How can I best schedule my tasks for maximum productivity and many more routine problems lik
Jul 24, 2016 rated it liked it  ·  review of another edition
Shelves: blue
Even though I'm a computer programmer, I have to say when I saw the title I was a bit put off. Algorithms are what I use for telling a computer what to do, but I'm not sure I feel comfortable with using them to tell myself what to do. Real life is less tidy and binary than the data in a computer.

But, perhaps out of train-wreck curiousity, I picked it up and took a look. The first thing I noticed is that Alison Gopnik gave it a dust jacket endorsement. Ok, you have my full attention now.

Once I st
Riku Sayuj
A simple algorithm to conceive of literary plots could be to slot them as belonging to one of these categories: Man vs. Nature, Man vs. Self, Man vs. Man & Man vs. Society.

Brian & Tom enlists findings from computer science to guide us through these. Algorithms here are the shortcuts or even the intuitions that guide us through problems that are intractable at first glance. We, apparently, use them everyday. Brian & Tom are here to document this and to show how exactly we can make them more effi
Arunothia Marappan
In this book the authors explain famous algorithms in real world context.

My notes from this book -

(1) Optimal Stopping
(2) Old people don't lose memory - they have so much of it that it slows their system.
(3) Procrastination can be seen as an efficient scheduling problem with wrong priority.
(4) Predictive Models - Gaussian, Power Law, Erlang
(5) Over-fitting - "It really is true that a company will build whatever the CEO decides to measure".
(6) Penalize complexity - Occam's Razor Principle
(7) "A
Feb 25, 2016 rated it it was amazing  ·  review of another edition
I really enjoyed this book. It's a nice popular review of research, in a style similar to Malcolm Gladwell. It was fascinating to see the wide-reaching applications of classic algorithms from computer science and also humbling to see how many problems are essentially impossible to truly optimize. However, as luck would have it, there are often simple approximations that give a pretty good solution with very little effort. The authors do a good job giving interesting backstory on the algorithms a ...more
May 26, 2016 rated it really liked it  ·  review of another edition
Shelves: favorites
An engaging conceptual tour of computational/networking concepts, how they apply in the computer world, and how we can use them to reframe, streamline, and manage a diverse array of real-life problems, both silly and serious. As a reader who knows little about computer science - but loves learning new frameworks, drawing analogies between disparate fields, and finding metaphors for life everywhere - I thoroughly enjoyed this.

Some of my favorite principles/concepts:
* 37% rule of "optimal stoppi
Feb 16, 2016 rated it really liked it  ·  review of another edition
So many great one-liners in this book.

Stop on Tinder at 37%.

Use thick markers in brainstorming.

All things being equal, it'll last as long as it's lasted.

But lest you think this is another fluffy brain book, it's actually hard computer programming with the occasional laugh-out-loud line. The team behind it are serious academics who have thought deeply about how computers think and how we can use those algorithms to make our lives easier. Which, when you think about it, isn't so crazy, because who
Manuel Antão
Sep 06, 2020 rated it really liked it  ·  review of another edition
Shelves: 2020
If you're into stuff like this, you can read the full review.

P vs NP: "Algorithms to Live By: The Computer Science of Human Decisions" by Brian Christian, Tom Griffiths

Regardless of what Feynman said (it wouldn't matter if even Gödel said it), Computer Science is not engineering. I add some caveats to that, Computer Science is not so easily categorized, so by Computer Science I refer to the formal science aspect. Now, referring to "Nature", two things, some results of Computer Science if they we
Jan 09, 2017 rated it really liked it  ·  review of another edition
Shelves: science
It was quite interesting, intriguing ! Once I had an argument with somebody who believed in using "steepest ascent hill climbing approach" while decision making. I personally don't favor hill climbing algorithm.
I think the following two lines matter:

neighbor <---a highest valued successor of the current.
if value(neighbor)> value(current) then replace current with neighbor.

Now, whether people would execute these two lines or not depends on many things. Sometimes they may, sometimes they may comm
Ross Blocher
May 22, 2020 rated it it was amazing  ·  review of another edition
Even as a lover of cerebral non-fiction, Algorithms to Live By: The Computer Science of Human Decisions sounded mentally taxing enough that I put off listening to it for quite some time (I had acquired the Audible version, read by Brian Christian, in a 2-for-1 deal). I hope that others will not be similarly dissuaded: there's a lot of great, applicable information to be had here. It kept occurring to me that those who could benefit the most from this book's message of better-living-through-data ...more
Dec 05, 2016 rated it did not like it  ·  review of another edition
Oy. This type of thinking is part of what is wrong with the world and gives nerds a bad reputation.

These algorithms are very theoretical. It's impossible to apply them without making all kinds of assumptions that don't seem generally valid in the real world. And the proponents don't test them to see if they work. For example, they've got one on how to find a parking spot. They ask the guy who came up with it how it works for him. He answers "Oh me, I ride a bike." [rimshot]

Also, the narrator ta
Shayan Kh
Dec 13, 2016 rated it it was amazing  ·  review of another edition
یه سری توضیح فارسی بعد از این ریویو ی انگلیسی هست.

Wow. I did not expect this book to be this good.
Algorithms to live by is aptly named. The authors use computer science problems to tackle everyday problems that every one of us encounters on a daily basis. How should I schedule my day? How should I organize my files? When I found a parking spot, should I park or should I search a bit more?
All of these problems have a right answer, and people mostly don't know the answer. This book has been sent
Jul 19, 2016 rated it liked it  ·  review of another edition
Definitely valuable material here, but I can't fully recommend it... although I'm having trouble discerning why. Fact is, I read a lot of books of this ilk, and this one didn't strike the right balance between the hard math and the chatty anecdotal moments, as Freakonomics did. Moreover the real life application of these principles are in many cases strikes me as being about as real-world-useful as textbook economic models, with their perfectly logical actors, etc. Good food for thought, nonethe ...more
Huyen Chip
Jan 11, 2017 rated it it was amazing  ·  review of another edition
I read this book per my professor's recommendation and I wasn't disappointed. Throughout the book, there are many moments that made me go: "Wow, that explains a lot!" I'm familiar with most the algorithms mentioned in the book, but I didn't see their application in real life until now. ...more
Nov 01, 2016 rated it it was amazing  ·  review of another edition
One of the authors of this also produced The Most Human Human, a very good book about artificial intelligence that I probably didn't laud in enough detail in my review (although, to be fair, I read it on a Turkish beach and reviewed it well afterward). This book is an even more ambitious attempt to bring computer science concepts to a lay audience, and I thought it was excellent.

Presenting common algorithms as a way of making decisions in ordinary human affairs seems a lot like the computer-sci
Todd N
Jan 31, 2018 rated it really liked it  ·  review of another edition
This is the first book I’ve read that was recommended to me by a Goodreads friend I haven’t met irl. (Thanks, Darian!)

Very interesting and readable book that goes through algorithms that are common in computer science and tech fields, gives a bit of history about them, and then shows ways that they could be applied to every day scenarios.

Since I’ve worked in tech on products up and down the OSI stack, I was familiar with a lot of them though I certainly hadn’t sat down in a systematic way and th
Mar 17, 2017 rated it really liked it  ·  review of another edition
A really excellent book
Apr 16, 2017 rated it really liked it  ·  review of another edition
Shelves: non-fic
3.5/5. I'm totally hooked and decided to buy the print version because it is actually that helpful. It could almost rival Thinking, Fast and Slow in terms of how much of (relative) new yet relevant things it taught me. However, the writing is not as neat and the authors try a bit too hard to sell to book to general audience, stretching the implications/applicability of some algorithms. They are not the original researchers, i.e. they didn't actually solve these mathematical/computational problem ...more
Mar 27, 2017 rated it really liked it  ·  review of another edition
Shelves: philosophy
It was a delightful book for all nerds, STEMians and utilitarians, who would love to analyse every single action by the probable result of doing it.
This book uses some major algorithms that has been used in computer science and mathematics, and showed their implications for daily decisions.
I enjoyed this book, though I would've loved it, if it had more of a structure, and maybe even exercises, for eager audience.

Kathryn Bashaar
This book was entertaining to me because I minored in Math & Computer Science in college and have made most of my career in information mangement. The premise is that computers are so fast and so smart now that they can solve problems that stymied mathematicians for centuries, and can even shed light on more everyday human problems. Such as, how many people should I interview before making a hiring decision? Or, should I finish my small tasks first or tackle the big ones? The main conclusion tha ...more
Dec 25, 2016 rated it liked it  ·  review of another edition
Shelves: owned
3.5 out of 5.

I feel like this book was a bit misleading, but still offered quite a bit of interesting knowledge. In the first few chapters, there were fantastic parallels to real-life problems that are synchronized with computer and mathematical problems. Beyond these first few chapters, however, I felt like the majority of the book was spent telling us about the computational problems, without doing as good of a job as referencing back to everyday life as was done previously. Because of this, t
Sep 08, 2017 rated it it was ok  ·  review of another edition
I am surprised by all the positive reviews of this book. Basically the authors start each chapter with a snippet of "history," one that is oversimplified and completely removed from its historical context (and basically used as as filler). Then they talk about a computer science concept and relate it to math, which is the true focus of the book--a random walk with the authors through computer science algorithms and ideas. To close the chapter they *try* to relate it to human problems (like decid ...more
Willian Molinari
I'm migrating all my reviews to my blog. If you want to read the full review with my raw notes, check it here:

This is that kind of book that does not answer questions, it just creates a lot more. :)

I tend to not implement algorithms just for the sake of learning a new one and this is not a good thing. When you read these kinds of books you understand why it's so important to know which kinds of algorithms already exists and which problems they solve.

Real hac
Mar 19, 2017 rated it did not like it  ·  review of another edition
This book takes the most basic algorithms in stats and computer science and combines them with the obvious examples of their usage while successfully presenting nothing useful. For those who are interested in maths, there is only some intuitive descriptions of the algorithms without any concrete proof, and most CS or stats students learn them in depth in their first year anyway. The part about "to live by" is where the authors use their power of hindsight to discuss the obvious. The whole book c ...more
Feb 18, 2019 rated it it was amazing  ·  review of another edition
I really liked this book. (I’m not technical or educated in mathematics, and if you are, then the following may not apply to you at all.) This book did a great job explaining technical concepts like sorting or caching, and showing how these are applied in complex algorithms — or in everyday life.

Writing and storytelling wasn’t perhaps quite as gladwellesque as it could have been, but the content was very illuminating.
I'd highly recommend this book to anyone who starts (or continues) to study computer science. It provides an important connection or grounding, between somewhat dry science and real life and shows how our everyday actions and decisions are described or affected by core CS algorithms.

I listened to it as an audiobook and I'd say that's the only book with the word "algorithm" in its title so far, that is perfectly suitable for the audiobook format. It doesn't have formulas or source code. It
Dec 13, 2016 rated it it was amazing  ·  review of another edition
Shelves: self-improvement
Useful and curiosity pleasing at the same time. I will remember to use in my office and personal life the exponential backoff algorithm for sure. I will also use technique of relaxing difficult problems (the method is used as a modeling strategy in mathematical optimization). This one is cute too: some problems are so complex, they are simply intractable (i. e. no algorithms that can solve them elegantly exist and the only solution -- brute-force search). One more sweet notion: computational kin ...more
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Brian Christian is the author of The Most Human Human, which was named a Wall Street Journal bestseller, a New York Times Editors’ Choice, and a New Yorker favorite book of the year. He is the author, with Tom Griffiths, of Algorithms to Live By, a #1 Audible bestseller, Amazon best science book of the year and MIT Technology Review best book of the year.

Christian’s writing has been translated int

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“Seemingly innocuous language like 'Oh, I'm flexible' or 'What do you want to do tonight?' has a dark computational underbelly that should make you think twice. It has the veneer of kindness about it, but it does two deeply alarming things. First, it passes the cognitive buck: 'Here's a problem, you handle it.' Second, by not stating your preferences, it invites the others to simulate or imagine them. And as we have seen, the simulation of the minds of others is one of the biggest computational challenges a mind (or machine) can ever face.” 44 likes
“Don’t always consider all your options. Don’t necessarily go for the outcome that seems best every time. Make a mess on occasion. Travel light. Let things wait. Trust your instincts and don’t think too long. Relax. Toss a coin. Forgive, but don’t forget. To thine own self be true.” 36 likes
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