--- product_id: 26698707 title: "Algorithms to Live By: The Computer Science of Human Decisions" brand: "brian christian, tom griffiths" price: "€ 36.16" currency: EUR in_stock: true reviews_count: 13 url: https://www.desertcart.be/products/26698707-algorithms-to-live-by-the-computer-science-of-human-decisions store_origin: BE region: Belgium --- # Algorithms to Live By: The Computer Science of Human Decisions **Brand:** brian christian, tom griffiths **Price:** € 36.16 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Algorithms to Live By: The Computer Science of Human Decisions by brian christian, tom griffiths - **How much does it cost?** € 36.16 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.be](https://www.desertcart.be/products/26698707-algorithms-to-live-by-the-computer-science-of-human-decisions) ## Best For - brian christian, tom griffiths enthusiasts ## Why This Product - Trusted brian christian, tom griffiths brand quality - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description Wall Street Journal Bestseller New York Times Editor's Choice New Yorker Favorite Book of the Year “A remarkable book... A solid, research-based book that’s applicable to real life." - Forbes An exploration of how computer algorithms can be applied to our everyday lives to solve common decision-making problems and illuminate the workings of the human mind. 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 they’ve found have much to teach us. In a dazzlingly interdisciplinary work, Brian Christian and Tom Griffiths show how algorithms developed for computers also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one’s inbox to peering into the future, Algorithms to Live By transforms the wisdom of computer science into strategies for human living. ## Technical Specifications | Specification | Value | |---------------|-------| | Dimensions | 6.55 x 1.15 x 9.55 inches | | Edition | 1st | | Isbn 10 | 1627790365 | | Isbn 13 | 978-1627790369 | | Item Weight | 2.31 pounds | | Language | English | | Print Length | 368 pages | | Publication Date | April 19, 2016 | | Publisher | Henry Holt and Co. | ## Images ![Algorithms to Live By: The Computer Science of Human Decisions - Image 1](https://m.media-amazon.com/images/I/81EI+ELW9EL.jpg) ## Available Options This product comes in different **Format** options. ## Customer Reviews ### ⭐⭐⭐⭐⭐ Great book on real world problems solved by computer science *by on Reviewed in the United States November 25, 2016* Despite being an East-coaster, I'm a member of the Long Now Foundation, which--when I'm asked to describe it--I usually say is like TED, but with a long term view and way better substance. The Long Now gives regular talks, and then puts those talks up in video and audio form for others, who couldn't be in attendance. I subscribe to the podcast in iTunes, and listen to it--along with other podcasts--on my way to and from work.A few months ago, Brian Christian was the guest speaker, and gave a talk centered around the subject matter of his latest book: Algorithms to Live By. The talk was fascinating, and contained a nice mixture of computer science, statistics, and humor to win the crowd over, and Christian managed to do so without coming across as too "pop science."I purchased the book that same week, and between juggling work responsibilities and twins, managed to carve out about an hour each night to read through it. There were chapters that held my interest, and chapters that didn't, but overall the book was a fantastic mix of how various computer science problems are also real work problems, and algorithms that solve one can be applied to the other as well.The first thing that catches you in the book is the discussion of optimal stopping, and how given a decision that needs to be made, you should begin making your choice after 37% of the options have been mulled over, assuming any of the next decisions/options are better than the ones that came before. This is illustrated with the secretary problem, and you can see why the authors led with this example not just in the book, but also in the Long Now talk. It seems both crazy and fascinating to have a difficult decision boiled down to such a hard percentage. The authors then go over different variations of the problem, and show how slight alteration can bring the best outcome.The authors (Christian and Tom Griffiths) then follow this up with a rapid succession of entertaining problems such as exploit/explore to determine whether you should go with something that you know, or try something new, as well as chapters on sorting, caching, and scheduling, giving messy desk people hope by showing that a stack of files on a desk where something searched for is retrieved and then placed on top of the pile will eventually result in the most optimized sorting methodology for the job, and reminding older, forgetful people that accumulation of knowledge can result in greater time to sift and retrieve that information, renaming so-called brain farts to caching misses.The chapter on Bayes' rule is where things start to get a little bogged down, but only in the beginning. Eventually, the chapter turns into an explanation on forecasting, showing which various predictive methodologies should be used for which various distributions--even equating the Erlang distribution to politics.The back half of the book isn't as tight or as entertaining as the parts that came before it, but overfitting was a great read to be perusing while Nate Silver was being hammered for his polling methodology in the most recent election, and the chapter on networking gave a great, easy-to-read introduction to how information networks differ from telephony. The authors then conclude the book with game theory, discussing the tragedy of the commons, and how, as a society, we could pursue better options in order to ensure mass participation in important initiatives.As somebody who studies and works in computer science and mathematics, I can say that casual readers will likely get lost in some sections, but powering through or re-reading will get you on to the more entertaining sections. This is a great book that works as a science popularizer without injecting fluffy prose/concepts or dumbing the material down. ### ⭐⭐⭐⭐ A brief intro into what algorithms are and are not *by on Reviewed in the United States May 31, 2021* When one thinks of algorithms, it is often in association with computers or machines. Not humans. It is also common to think algorithms are there to provide a simple, neat solution to complex problems only a machine could solve. Or that algorithms can, once fed enough information, predict one’s every action and solve every problem. The main premise of Algorithms to Live By is to disabuse one of such notions. Algorithms to Live By explores how regular people use algorithms without even realizing it in their day-to-day lives. By doing so, the authors hope to destigmatize the word and get people to see the concept differently. Though the book can be dry at times, the authors manage to write a book that is accessible to most people. And there are moments of insight that do make the book a fascinating read.As aforementioned, the book explores how people use algorithms in their day-to-day to accomplish tasks. They focus on several elements: explore/exploit, or when it is best to continue to look for something better or make a choice from what one already knows; sorting and tradeoffs; and scheduling being among the subjects of focus. What makes these sections interesting is that they often talk about tradeoffs that one would seem counterintuitive. An example of this is in the scheduling section. The authors mention how the placement of a task on a schedule may be influenced by how much one knows about the task: by its duration or difficulty. This may increase the difficulty of scheduling if one were to know every detail of every task that must be done for the day. They also mention that while some may be tempted to schedule tasks based on how easy they are, this may also come with downsides. Especially if one decides to prioritize harder tasks before easier ones, only to realize that its completion requires completing an easier task. They give an example of a NASA Mars rover being frozen due to this fact. The rover was programmed to prioritize high priority tasks first in its queue over low priority tasks. However, one of the low-priority tasks kept being pulled from the bottom of the queue to the top. This caused the rover to freeze. Thus, even well-thought-out systems can lead to problems.The above example with NASA shows another aspect of the book I like; the use of real world examples. The authors tell stories involving real world mathematicians and scientists struggling with these issues in their personal lives. This helps make the subjects feel personal and applicable to one's own life. In fact, I would argue that the only issue with the book is that these anecdotes seem to be an afterthought. This is due to the fact that the anecdotes become more prominent as the book progresses towards the end. Thus, the first few chapters can be somewhat dry in its presentation which may turn off a lay reader. Furthermore, the use of hypothetical scenarios in the earlier chapters feel like a pale imitation of the personal anecdotes of later chapters.All in all, this book was fairly enjoyable. While having some rough patches, the authors did try and succeed in making an accessible book. ### ⭐⭐⭐⭐⭐ Mathematicians' contributions to everyday problems *by on Reviewed in the United States June 19, 2017* For me, the book takes intellectual effort to absorb. As I was preparing to write this review, I was further impressed with the range of information presented by the authors. I am personally undertaking an investigation of machine learning, artificial intelligence, data mining, etc; The book fit into this investigation. If you have interests in this area (or areas), I think you'll find the book useful. It probably shouldn't have, but the parallels between common human problems and computer programming surprised me. As the book has had a large number of reviewers already, I will highlight some, but far from all, of the topics of each chapter so you may see if they make you curious. While the book speaks of algorithms to live by, the mathematics in the book is highly limited.Optimal stopping - how many people out of 100 possible candidates should one interview for a given position (including that of spouse)? 37%, Why? Read the book.The Explore/Exploit dichotomy - Should one ask the question "What's new" or "What's best"? Your answer may depend on your time horizon. As your time horizon shortens, "what's best" may be the better question. The book explains why. The book also looks at the multi-armed bandit as an example of the explore/exploit dichotomy. What's a multi-armed bandit? Think of the one-armed bandit in Vegas and multiply its arms. Mathematicians do so. Their conclusions may be useful. The trials of music critics also fit into the explore/exploit dichotomy. The authors explain why music critics find exploration a chore.Sorting - libraries are the metaphor for computer sorting. Human memory also requires sorting. Maybe the decline in memory as humans age may be due to the amount of information through which it must sort and not due to declining faculties. A five-year old has a lot less information to go through than a seventy-five year old. The authors consider sorting techniques with email, Yelp, and other common uses. There is much useful information.Caching - when is forgetting necessary? According to the authors, the first computer cache was developed for a supercomputer in 1962 ub Manchester, England. I wonder how "super" that computer was? Caching allows some information to be stored for repetitive use and uncached information to be kept in the background.Scheduling - many scheduling problems have "intractable" solutions. The authors suggest different solutions based on algorithms such as precedence constraints, earliest due date (one I personally use frequently, which I couple with a personal likely to get me in the most trouble the quickest test) and shortest processing time. The scheduling problem has received substantial effort from mathematicians.Bayes's Rule - how to use statistical inference to make useful predictions. Couple a well-defined problem with a range of prior outcomes and one can make accurate guesses. A .300 hitter comes to the plate against the same pitcher who has already struck the batter out twice and it may be a fair guess that the hitter is due for a hit.Overfitting - don't overthink and over complicate a problem. The authors advise against practicing the idolatry of data. A more complex theorem may well lead to less accuracy rather than more. On the level of incentive compensation, the authors quote Steve Jobs for being careful that you include only those elements in your incentive package that matter; you will get what you measure.Relaxatrion - the perfect is the enemy of the good. To get any useful answer from your mathematical model, it may be necessary to relax some of your constraints (insisting that your model never allow the traveling salesman to re-enter the same city twice may preclude any answer at all in a time period of less than the remaining life of the universe).Randomness - mathematicians sometimes realize that the best answer comes from sampling and not from strict calculations. This may explain why I get so many survey requests. Algorithms for prime numbers use this technique. And, apparently, thousands of years ago the Greeks were already looking for prime numbers.Networking - here the authors examine the "Byzantine generals" problem, which plays a part in explaining how computers communicate with each other.Game Theory - Alan Turing investigated the "halting problem" in the 1930s. What if you give your computer a problem and it just keeps going? Rock, paper, scissors is a game with which most are familiar. It, too, is part of game theory. When a game seems to have no satisfactory answer, maybe it's time to change the game. What happens when you have an "information cascade"?If any ot this interests you, I believe that you will enjoy the book. I recommend it highly. ## Frequently Bought Together - Algorithms to Live By: The Computer Science of Human Decisions - Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones - Thinking, Fast and Slow --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.be/products/26698707-algorithms-to-live-by-the-computer-science-of-human-decisions](https://www.desertcart.be/products/26698707-algorithms-to-live-by-the-computer-science-of-human-decisions) --- *Product available on Desertcart Belgium* *Store origin: BE* *Last updated: 2026-06-17*