The Computer Science of Human Decisions - Algorithms to Live By

The topics selected inside the book are fantastic. The author explains ideas lucidly with interesting facts and simple mathematical reasonings. It's good for people who wants to get an overview for these topics.

Fascinating book, well explained for the non-expert. I picked up this book hoping it would teach me a bit more about how computers work and as well as this I saw the similarities with how people think and how we might tackle tricky problems. This book gave useful insights into the people-based systems in which I work. It is one of the few books I read a second time and take copious notes.

Excellent book with a wealth of additional references. This did wet my appetite, it covers many actual topics and explains them very well. For instance the section on caching and TCP were very helpful.
At times the book is not an easy read but that is to be expected when reading on technical topics. Nevertheless, the authors have done an outstanding job at making technical concepts accessible to a broad audience.
I enjoyed reading this book and it has sparked interest in new topics such as optimal stopping algorithms which should be of interest to many readers.
However, if you are into reality TV this book may not be for you because it will require you to become involved, to read critically and actively. The book will refer back to concepts of previous chapters, so if you have difficulties absorbing the well presented concepts you may get frustrated. This is for sure not a 'Duck Dynasty' read.

Awesome! I thoroughly enjoyed this book. As an engineer with some programming experience I am drawn to algorithms and mathematics, and not only did this book put various algorithms in historical context, but it demonstrated how they can be applied to life while adding a philosophical twist. The authors are skilled at explaining difficult subjects using easy to understand language that builds from simple to complex at just the right pace, all the while using real world examples. Not only did I enjoy the read, but I learned new things that often prompted tangent explorations to learn more. The book left me with a hunger to delve deeper into many of the subjects discussed, and made me challenge, and sometimes affirm, many of my own philosophical beliefs. Well done!

Great information on how to improve your life. I have read the book several times, while making an effort to think about the many ideas proposed by the authors. I love the Explore/Exploit idea.

Note: I wasted a lot of time back in the day reading books by self help gurus. Most of those books lacked scientific backing or employed real studies. Now I seek out books written by STEM and Computer Science majors who back up their sources with footnotes and facts. If you see a book author who tries to excite people by jumping up and down on a stage while clapping his hands, run away as fast as you can. Wishful thinking does not work. Do your homework before purchasing books.

It's hard to say precisely how valuable I found this book. In part because I am still trying to take it all in and will need to re-read it to gauge its full impact. On first reading, the best I can say is this: it satisfies my amateur's enthusiasm for math and science as well as my interest in life hacks and self improvement. (Don't worry about the math part. Almost no mathematical knowledge is required beyond understanding percentages and graphs.) I've given other books 5 stars based on sheer enjoyment. This one deserves its five stars equally for pure practical value. Highly recommended.

I totally enjoyed Algorithms to Live By: The Computer Science of Human Decisions from the first to the last page. My only regret is that there is a last page. I prefer that Brian Christian and Tom Griffiths had ended this book with a promise that this adventure would be continued. The authors introduce and describe in detail several algorithms utilized in computer sciences that are particularly useful in everyday human decision-making. In addition, as with Brian Christian's first and best-selling book, The Most Human Human, this book addresses interesting philosophical and psychological issues inherent in the human experience. Neither a mathematician nor a computer scientist, I found the book easy to read and to understand. When higher math concepts are introduced, the authors spend sufficient time explaining them. The greatest challenge the book poses for me is to stand back from some of my assumptions about decision-making, so that I could absorb new and more effective ways to approach decisions in my everyday life. That’s a challenge I have embraced and prospered from already. Can't wait for the authors to bring us their next book.

This is one of the best accessible pop-science books I have read in a long time! The partnership between the two authors (Brian Christian and Tom Griffiths) is amazing. Too often books on interesting scientific topics are written either written by scientists alone who are not good at explaining their fields to a general audience or authors who, being less versed in the field, make inaccurate/overgeneralized claims or even just miss interesting connections that an expert would be able to include. Algorithms to Live By gets the best of both worlds, Tom Griffiths is an undisputed leader in his field and Brian Christian is a master of translating scientific jargon to human-language. This book walks you through decision theory in a way that is both engaging and enriching. I can strongly recommend that you buy this book (I will probably be purchasing several more copies to give as gifts)

Computer science has the whole living thing figured out, nay? Well, this book lists dozen algorithms making us wiser because life is all about trade-offs. Our intuition fails us miserably understanding connected events; just try to decide if you should keep exploring or start exploiting a resource. The discussion here flows widely also including: sort, cache, schedule, over-fitting, relaxation, randomness, networking and game theory.

A fabulous book overviewing many of the algorithms we use in computer science, with examples about why they're useful to us in our daily lives. Can't recommend highly enough, whether you've taken courses on Computability Theory--or not! I listened to this and bought a copy in hardback--a VERY rare combination for me. Outstanding job Brian and Tom!

Seriously quality read, key insight being that computers aren't about giving you the optimal result - they're about giving you the optimal chance at the optimal result. Great takeaways that I'm excited to use in both work and personal relationships.

I liked learning new things about mathematics, statistics, economics, and the like. I was disappointed the lack of applicability though - only 3-4 things I will actually be able to apply to my life. I would only recommend this book to people who love math and/or programming.

Computation, based in mathematics, is useful in answering many a quantitative question. The moral Christian paints in this book, however, is that many a quantitative question does not the average person face. Rather most important questions seem to pose themselves as impossible to assuredly answer with perfection through rote problem solving. In many cases, the computed answer has only a chance of being perfect, and in that conclusion I feel as though there is a great deal of solace. And frustration. But mostly solace.

Chapter one on Optimal Stopping was amazing. The chapter on cashing systems were also quite good. I don’t recall much else of use, though that may be due to listening to most of the book on audible. I found that listening was a bit too passive in order to retain the information being presented. I may re-read parts of this book at a future daye

Great book. I wrote a long summary of my highlights but I can't link to it the store disallows urls. Too bad, but just but the book you will be happy if you like clever practical ways to make better decisions.

Too verbose. Authors could have used less words to say more and use direct examples instead of round about stories... I would have liked more illustrations... overall a good book of great algorithms but poorly explained in a dull way.

I'm a software developer and it's still pretty difficult to disgust when the technical part is being explains. but overall it is a great book. I always knew you can use basic algorithm to solve certain recurring problems.

I especially love the chapter about explore/exploit. This come in specially useful for relationships and whether if it's worth it to find new friends/lovers or stay with the current ones.

Very interesting read with a lot of insight into the world of Computer Science. At times rather technical for a non-maths guy but I found it very satisfying to think through the concepts. Written in a very readable and engaging way. Would recommend.

If you're not already fluent in the terminology and math discussed in this book, it's pretty easy to get lost. I'm no professional mathematician but I'm more fluent than the average reader and I found the explanations too vague and sparse to really get much out of this book. It certainly doesn't provide anything helpful or particularly interesting for my daily living.

The print production (inside text and page set up) was even and solid. The content is exactly as described. My one comment is...the top edge of outer cover showed a a little smudge (like it was on a metal shelf for too long)...but then I am a tid bit picky. ☺️ Otherwise, I am pleased with the book... as a gift.

This book is so deep that I bought both the audible and hard copy. A fascination on every page and footnote. Probably boring for current computer scientists or math majors, but everyone else interested in optomizing their life should give it a try. Not for those who are easily distracted though.

I'd recommend this book to every scientist. The human side of science is often overlooked and less discussed. The examples chosen are vivid and memorable. Maybe this should be transformed into an university course so the content can evolve as the field evolves over time.

This is a good book if you want to get some help in making the best decisions in everyday life. Not all of the book is about that of course but those parts were the best and most useful parts for me and, for me? they are the main take aways.

What an amazing book. I am anon-CS major data scientists with a masters in stats/machine learning. Although I have been a C/C++ programmer for 8 years, I have always lamented not having a formal education in CS data structures and algorithms, time/space complexity topics. This book is by far the most effective in teaching me CS algorithms. With real life examples, this books teaches the "philosophy" behind scheduling, sorting, searching and many other algorithms. Thank you authors. This is the exact book I needed to learn algorithms. Amazing, amazing!
I always leave reviews only if I am bowled over by the product. This book has surpassed my expectations

This is the kind of book that gives mathematicians and computer scientists a bad name. The authors are the archetypal naive theorists who are so caught up in the elegancy of the math, they just forget that in many real-life situations, the realism of the model and the reliability of the inputs are far more important that any deft algorithm they may come up with.

The first chapter is about optimal stopping – finding the optimal point to stop a risky activity, such as searching, speculation, etc. This is a fascinating topic and could have been a worthwhile reading. Unfortunately, despite a wide variety of problems and a rich body of literature, the discussion of the problem itself is limited and superficial. Instead, the authors spend much of their time talking about how these ‘rules’ can be applied to real life situations, like hiring the ideal employee, finding the right partner, or deciding when to stop agitating your political rival.

The problem is, for these rules to apply, we must make certain assumptions, like we are always looking for the best alternative, we can always properly rank the candidates, we can know all the relevant probabilities. While no doubt there will be situations where such assumptions can be reasonably made, in most complex social situations, we just don’t have the luxury to do so. The messiness of such situations, just makes any talk of optimal stopping strategy meaningless..

For example, when looking for a romantic partner, with no easy way to accurately assess the desirability of your candidate and to know your own ranking in the dating market, any improvement in these knowledges, will vastly out-weight any impact you may get from applying any of these stopping strategy. In fact, in most social interactions, biological and social algorithms honed and battle-tested by hundreds and thousands’ years of natural selection, like intuition and convention wisdom, are much more reliable than any mathematic algorithm came up by the most ingenious computer scientist.

The authors just missed opportunities to adequately explain the topics they try to cover, failed to explore more areas where modern algorithms may have real impacts. Instead, they just too often dabbled in areas clearly out of their depth.

Admittedly, I didn’t read any further than the first chapter. Since here’s one algorithm I live by: if I don’t like the first chapter of a book, I will not waste time reading any further. Yes, the purchase price is the sink cost I have to live with, and writing this review is an attempt to redeem some of its value.

It was a disappointment to read. The use of real world examples helps when you have real world case studies or a solid hypothesis that you actually take part in. He cites the percentage of 37% but never shows the real math of understanding where that percentage came from. The examples used had nothing to do with his own previous work experience, and using the phrase "In computer science" became comical when applied to whatever he was trying to talk about at the time. For example, citing real estate prices is great if you are an expert or if he said 'I had a client and I learned from helping the client that this is what happens when X+Y= Z'. But it seemed like a lot of conjecture without the personal empirical evidence to back up his statements.

The book reads like someone who had done some research on computer science, and then rehashed the information. I wasn't particularly impressed by the examples given by the authors in their stories and anecdotes. I could imagine examples fitting much better to whatever subject at hand.

I didn't like it. But you might if this is one of the first books you've read on the topic.

Along with Computing for Ordinary Mortals, this is by far the best popular computing book I have ever read. Perhaps that is not saying much, I don’t know of many good popular computing books. But it is amazing. The perfect combination of algorithmic description and its application. There is an amazing breadth of topics. In each one, a lifelike problem is presented, then algorithmic solutions, and then further applications and algorithmic refinements. Some of the critics commented that the problems are not realistic. OK. But it does not take much imagination (although expertise helps) to see how they CAN be applied to problems that are. Even for a professional in the field (computing) but not working directly in any of the subareas (except one, caching), I learned something on every page. Almost all of the domains I had heard of, many I had studied in classes, but in almost none was I aware of many of the implications. The topics are Optimal Stopping, Explore/Exploit, Sorting, Caching, Scheduling, Bayes’s Rule, Overfitting, Relaxation, Randomness, Networking, and Game Theory. The most practical is probably Scheduling: while many of the scenarios are too idealized for practical use, there is still plenty of good stuff. For example, let your small tasks accumulate and then solve them all at once. Also practical are Optimal Stopping and Explore/Exploit. These most people already have good intuition about, but the algorithms (and results) show why that intuition is good, and when it is suboptimal, why. Overfitting was perhaps the most useful for me – why less is often more. It certainly shows nicely why some aspects of research are hard. Randomness is probably the most useful for most people: as a professional I have a reasonable feel for the power of randomness, but most people do not. This book should be required reading for all students interviewing for serious computing positions.

I have some familiarity with computer science and thought this book would be an easy bland review of some of the basics. In other words, I wasn't expecting much. I was very pleasantly surprised! The basics are covered well but recent findings in the field of computer science are also included. I actually learned a few things I didn't know. And explaining the concepts in terms of everyday experience (not just abstractions) makes the book very accessible to those with no background in CS.

A key insight of computer science is that it's possible to quantify the "complexity" of a problem and that many problems are too complex to evaluate fully—i.e. searching for an "optimal" solution is a fool's errand. Optimizing your calendar, determining how to research and when to commit to your next big purchase, and figuring out if and how you should organize your bookshelves are all great examples of provably "hard" problems; problems that insights from computer science can help with.

As someone who studied computer science, I wish I had this book when I was first introduced to the concepts: it beautifully bridges the theoretical and the applied, and demonstrates how all the core CS concepts (sorting and searching, constraint optimization, caching, etc.) apply to everyday life. This book should be a mandatory companion for all CS students.

The explanation of the mathematical problems underlying many of our daily tasks has been worth the read, but I wanted the author to leave us with more rules we can implement in our daily lives for overcoming these issues. Instead we get vague guidelines which aren’t directly applicable. I suppose that since we better understand the problems we can manage on our own, but I wanted more than a pop-sci explanation.

Practical takeaways:
-- err on the side of messiness
-- make sure things are closest to the place where they’re typically used
-- complete the easiest task first
-- slow down to get things done
-- optimism is the best prevention for regret

Over and over, this book follows the pattern
(1) accurately and clearly describe a computer science algorithm
(2) accurately and clearly describe a difficulty in the real world
(3) make a completely erroneous, misleading, and potentially damaging analogy between the two

For example, it describes an algorithm for managing communication on a limited bandwidth channel, then describes difficulties about knowing when to promote employees, then tries to draw a connection that makes no sense. The packet management algorithm is clever because it leverages several appropriate assumptions about data transmission which do not apply to humans, businesses, or labor. The analogy is forced, and if anyone actually follows the advice given it will be to their detriment.

In another case, the book introduces the notion of overfitting, then gives a real world example that is actually a case of underfitting. Both are issues in the real world and in the CS world, but it would seem the author doesn't understand the concepts as well as he explains them.

Definitely a classic and hopefully the beginning of a new, exciting genre.

The last time someone introduced a completely new field was perhaps Kahneman and Tversky with Behavioral Science. For the general public, they pioneered a new subject matter which over the years evolved to result in fantastic work from many others including Akerlof, Taleb, Gladwell (although the last two are not into behavioural economics as formally defined but against the previous textbook based approaches like behavioural pundits).

In a way, Mr Christian and Mr Griffith take us in the opposite direction. In behavioural and related sciences, the main focus is to show how real life behaviours and developments do not conform to the mathematical assumptions and theories used in textbooks. They offer few concrete suggestions on how to overcome these anomalies but do a great job throwing light on the non-rational nature of our thinking and activities in general life. This duo takes us to the realms of heuristical sciences and how we can use them in real life.

Heuristical sciences are difficult. They are not only intricate without much deductionist proofs but often counterintuitive. They are supposed to require enormous computing power to execute over and above being impossible to comprehend. Algorithms, created by young programmers drive our modern world, but most of us leave the understanding of them to the geeks shaping everything around. The book makes a bold attempt to prove this does not have to be.

There is new, never before heard (for this reader) information on every page. All this is not only in easily understandable format but enormously interesting and useful. The authors are gifted in making extremely complex things understandable in the simplest terms. I do not remember learning so much from one book in ages. A remarkable feat in our information-infested world. For me, this book will have to be read multiple times over the years for better understanding and amusement.

If there is one quibble, the authors pack way too much and extremely densely. They could have gone somewhat slower without worrying about the length of the book (it is frustratingly short!) and came up with more examples of their everyday application. I will refrain from listing at least ten major themes discussed in the book as they are well covered by other reviewers. In summary, a must and multiple read for everyone.

This is one of the most thought provoking and interesting books I've ever read. I have a MS Degree in Business with emphasis in Quantitative Methods (Data Science) so I've studied some of these principles before, but this is written in layman's terms with real life examples. Each chapter is independent of the others, so it's easy to read in shorter stints. I especially liked the chapter on scheduling. It discussed the various approaches that can be taken when scheduling. It's changed how I think about my task list - there is some value in doing short tasks first to shorten the list of things to do and knock out some quick-wins. It also mentions the book Eat That Frog, which recommends doing the most important task first, even if it is ugly. I've shared some of these ideas with others because I found them so impactful.

Easy to read with lots of examples the typical reader can relate to. The theme of the book is using simple rules and guidelines to wade through and organize the clutter and complexity of modern life. Much of it is intuitively obvious, but intuition seems to fall by the wayside when we’re dealing with complex, high risk decisions or simply have lost sight of what we’re ultimately trying to accomplish. Some of the algorithms we may already apply (though we never call them that) and it is nice to get reinforcement from the book. Others fall into the “why didn’t I think of that?” category. One of my favorites is the 37% rule.

I suspect that people of different generations will give different weights to the various algorithms suggested. That’s one reason to share it among family members and then discuss what you got out of it.

I took some notes on the book and will keep them handy as a refresher. It would be nice if each chapter had a bullet point summary of the algorithms so that I didn’t have to prepare my own, but then again, taking notes is a good way to enhance learning.

All in all a very worthwhile read.

I'm a fan of this book. I have a Computer Science background and actually teach an algorithm course at the University level and I would recommend this book to my students or anyone with interest in mathematics. If you have experience in the field there are some parts of the book that feel a little slow or repetitive, but overall a very enjoyable read. The authors do a good job using real world examples to explain how well-known algorithms can be applied to life and offer a brief history. While I may not agree on applying an optimal stopping algorithm to marriage, it's these types of applications that make the book and enjoyable and easy read. I would highly recommend the book even to those with a non-technical background.

This book provides deceptively simple insights into the day-to-day chores that we do. I don't think I'll every sort my bookshelf, as scanning it is lot more easier. The book provides some examples on how to implement some of these algorithms in our daily routine.

I knew some of the concepts that the book mentions, but algorithms like Optimal Stopping Theory and Bayes' Theorem were definitely eye-catching and thought-provoking. The chapter on Networking discloses complex TCP concepts in relatively easy language.

I believe this book is mostly for Science and Mathematics enthusiasts. A casual reader might get lost in the deep computer- and statistics-theories provided throughout the book. Being one such person, I thoroughly enjoyed reading this book.

A rather enjoyable journey across algorithms and math applied to everyday human situations. This geeky book is very readable (or listenable) and gives surprising insights into mathematically proven optimal strategies for very human dilemmas like finding your dream home or life partner, the best way to sort your bookshelf, trying new restaurants, and family schedule optimisation challenges. Written for a non-technical audience, you'll still find yourself chuckle when the authors apply your favourite algorithm on a very different context.

I have a computer science degree and I learned a LOT from this book. It is by far the most information-dense pop science book I've ever read. Plenty of pop sci books would take half a chapter from this one and pad it out to 250 pages. Furthermore, it does this without reading like a textbook.

Imagine an easier to read Art of Computer Programming and you'll get pretty close.

I am not even halfway through this book and I am already fascinated and enjoy the connections made between the algorithms of the human brain and human behaviors. When reading this book, I realized just how many situations in real life when the brain follows specific algorithms to solve problems. The authors seem to have fully researched the subjects and claims they make, and back it up with evidence from other sources, or sometimes even collecting their own data. After presenting their ideas, the authors explain why the evidence they use supports the theories presented and also challenge themselves to fully explain their points. The research and explanations of the algorithms are well written and detailed without being drawn out or boring. Though seemingly perceived as simply mechanical and technical, the algorithms compared to human behavior open the reader's eyes to their own lives and how they make decisions. I recommend this book to anyone who is interested in human behaviors and how the brain works.

This book describes a range of ideas and algorithms that relate to problems solved in computer science but also having intuitions that relate to daily life. The algorithms discussed include those for sorting, caching, scheduling, predicting, connecting, optimising, solving difficult problems via randomisation, and algorithmic game theory. There are not many books which can explain such a range of algorithms in the fascinating way that the authors have done, giving adequate details so as not to be superficial, and in such a way that relates computing to daily life problems. The last chapter on computational kindness, part of which means designing things and systems in such a way so as to reduce the computational (cognitive) load on people is an interesting idea. I think anyone who is a Computer Scientist should read this book and "revel" in how intellectually rich and relevant their field of study is (i.e., algorithms).

Such a cool book that I would have loved to keep on reading. I can admit I didn't understand everything but still it was absolutely brilliant. Algorithms are everywhere and we use them even if we don't recognize them, so after many epiphanies I was almost shocked.

Libro veramente interessante che avrei voluto non finisse ancora. Posso anche ammettere tranquillamente di non aver capito proprio tutto, ma quello che ho capito mi é bastato per decidere che fosse veramente brillante. Gli algoritmi sono ovunque e li usiamo continuamente senza sapere che sono loro, una volta portati alla luce c'é da rimanete a bocca aperta.

Nerdy book, first and foremost. Those who live at the edge of comp. science will like this. Its a semi-lucid narrative that talks about big concepts in statistics, algorithms and maths. I liked the examples (which were quite understandable) and the bits of history behind the big ideas. Like the traveling salesman problem.

Overall, I loved the book since it jogged my memory on bits of info I knew long ago. And it introduced me to several new CS perspectives that I didnt know about. I'd recommend it to all tech-inclined folks.

No wonder this title is getting reprints. Enjoyable, fluid, with examples well outside of computer studies. Cuts through multiple domains where algorithms are being used, it may very well serve as anyone’s first book on the subject. What I found the most endearing is how the authors look for natural phenomena which show algorithms at work; perhaps it results in a bit overstretched parallels from time to time, but it is still a material worthy of your reflection.

Interesting viewpoint on mapping human psychology onto computer algorithms. Where else would they come from? The writing is entertaining and an easy read for the most part. I'm a software engineer, so some of it was clearly made easier to understand for non-computer folks. The premise opens up an interesting exploration.

After daily-commute-listening to the audiobook narrated by one of the authors, I decided to get the hardcover to fill in gaps left by driving-related concentration lapses. Glad I did! The audiobook is superb to listen to, but it's nice to sit down and absorb the concepts at my own, admittedly slow, pace. So if you're considering the audiobook, great! Get it. If you're considering the printed work, also great! There are charts and graphs!

As an engineer and someone aspiring to know how to write code, this was a wonderful source of introductory information as well as a rational guide for identifying, approaching, and working problems of all shapes and sizes. Along with Chris Hadfield's "An Astronaut's Guide to Life," (another audiobook I found this year that's artfully narrated by its author) this book ranks as a top tier life guide that I wish had been available to me when I was 20. The top review does good justice to it, so no need for me to say more. Just wanted to share my 5 stars for the authors' benefit.

I think the connection between the subtle ways we make decisions and how they can be mapped to computer science, statistics and mathematics is absolutely fascinating. I'm not sure I am going to walk away with any enlightening new tricks for my daily routines however it's still very interesting. I listen to this book on Audible - only comment I would make there is that the book requires your full attention (great for your commute, or on a plane) otherwise the details and points he's trying to make can get lost.

This is an excellent (audio)book. Algorithms that we use in Math, computer science and engineering are explained (without the math) and most importantly how are they used in other real life problems or context. The chapters on Cache memory and on Scheduling are particularly very useful and have large application area. The audio-book is presented well, the narration is excellent (by one of the authors) and the pace is great. The reader would require a little background on algorithms though and how to compare complexity.

I read this book after reading The Signal and The Noise by Nate Silver, and the two definitely complement each other very well. I do have to say though, I definitely enjoyed Algorithms To Live By more. Highly recommend reading this!

Brilliant, eminently likable, and thoroughly entertaining from beginning to end. It validates heuristics when they're valid and explodes them when they aren't. What could be more fun or more useful than that?

This review is based on the Audible edition.

This was an interesting book about the applications of common algorithms. This book is marketed to show how these algorithms can benefit people in their daily lives, but only a few of the chapters relate to topics outside of computer science. While the applicable topics like optimal stopping can be applied to real life, things like bloom filters don't make sense in this book. If viewed as a general overview of many algorithms from different areas of computer science, then this book will not disappoint. Even though I was misled, I still enjoyed the read and the new concepts I learned.

I would recommend this book to the layperson interested in getting into computer science and for the computer scientist looking to understand the real world. This is a great companion piece to Thinking Fast and Slow.

This is a fascinating book that explains how algorithms can help us make better everyday human decisions. Although difficult to read because of the material involved, the authors kept me interested by sharing an eclectic mix of real life applications. I will definitely have to read through the book again to extract even more from this dense and thoughtfully written book. Highly recommended.

This gave concrete examples of how using algorithms can help you to be more efficient, make better decisions, and see the world slightly differently. Its engaging style and evolution of response gives you enough background to understand the underlying concepts without getting caught up in mathematics or programming language. A definite fun read.

This is a fun take on human decision making, which draws directly on algorithms used in the field of computer science to consider topics like an apartment search, marriage, voting, etc. I made the mistake of reading this as an audiobook. That's a fault for this book in particular, as there are a lot of discussion of mathematical relationships that could really be aided by the use of visual graphics. I don't know if such graphics are available in the book, but they should be! -Ryan Mease

As a trained data scientist and one who loves to draw general analogies for living a full and happy life from more technical areas of research, this book hit the spot for me. The explanations of the algorithms I was already familiar with were right, and the analogies and generalizations were fantastic. This is a book I wish I had written first, and am pleased that these two did it, and well. If you aren't inclined toward reading technical material, the book may be a bit dry for you, though not difficult to grasp. It's just...computer science, applied to life's circumstances. There are some real nuggets of wisdom, and I will use this as a reference when giving advice to my own children.
As an aside, I listened to this as an audiobook, though I will be going back and purchasing a hard copy for annotation and reference later.

I personally liked the book because I have an obsession with algorithms and what you can do with them, probably that makes me subjective at this re view but I think the book is also well researched and offers good example.

The only issue I have with the book is that it is too short I think there even more algorithms to talk about but of course the ones presenters really make the point.

Useful life data, historical annecdotes and examples about decision making based on computers and their “thinking,” with some delightful stories, some funny ideas, some hard to follow marhematical concepts, some definitions debunking myths, the many moments of aha provided great conversations for our team and will assist us in making decisions.

Good for people who make decisions with mathematical reasoning backgrounds, not so applicable in real life. I cannot image people memorize lots of examples. Go for other behavioral ECON books instead.