Tom Griffiths

Brian Christian

A fascinating exploration of how computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favourites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian (who holds degrees in computer science, philosophy, and poetry, and works at the intersection of all three) and Tom Griffiths (a UC Berkeley professor of cognitive science and psychology) show how the simple, precise algorithms used by computers can 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 understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living."

The Computer Science of Human Decisions

Algorithms to Live By

A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can 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 understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Up until the last chapter, I was planning to rate Algorithms to Live By at three out of five stars. The book is filled with poignant descriptions of algorithmic devices that we (mostly unknowingly) use in everyday life, and the explanations are simple enough to be understood by any layperson. Unfortunately the first half of the book put a bad taste in my mouth with its "by male redditors, for male redditors" tone, but the last 50ish pages on game theory, mechanism design (i.e. "reverse game theory" ), information cascades, Vickrey auctions, and the revelation principle really blew me away. The well-developed conclusion claims that even though we all want to escape the brutal rat race wherein folks take advantage of others at every turn, there is still hope. We can still change many aspects of the game to transform the dominant strategy into one that is based on honesty. I'm super glad I didn't throw this in the DNF pile. 

Ashlyn

Anthony

Exciting book full of great insights. This is one I'd love to come back to from time to time as I continue to explore algorithms and apply them to my life!

Thomas DeCelle

Rohini Anandamurugan

This is the book I was looking for throughout my engineering :) 

Primarily, the book uses a bunch of algorithms to explain everyday problems, ranging from organizing your cabinet to dating to finding an apartment. The book delivers what it promises. It provides a very fascinating perspective to look at life in general and I thoroughly enjoyed it.

The author does seem to go off on tangents every now and then, but considering the nature of the material it covers, I'd still classify it as well written. So it's a pretty good read.

Swastik

This was a (surprisingly) good book. Lots of good ideas, regardless of whether you're familiar with algorithms or not, and it was very well written.

Hrishikesh Bhaskaran

Ryan Angel

Very convincing ideas but unrealistic expectations in a lot of places. Not gonna lie, my mind drifted a lot but I found a lot to be very insightful and interesting. 2.7 stars.

Kyle S

Great book for anyone looking for rational ways to make decisions. My only reason for not giving it 5 stars is because this book has too many good points I think, making it hard to process one before moving on to the other.

Jeni Enjaian

I must have added this book around the same time that I added "The Organized Mind," likely after listening to a podcast on the topic. To go from "The Organized Mind" to this book made several of the topics blur. When I read something in this book that seemed familiar, I could not discern whether that was because I read the same fact or anecdote in "The Organized Mind" or if the authors of this book had repeated themselves.
Perhaps if I had not read this book as a follow up with a brain already full of these facts I would have appreciated the book more. Perhaps not though because this book delved more into the math behind some of these things which even though I don't mind math, tends to turn me off.

Rebeca Keren Nuñez

Muy interesante. Son cosas en las que uno no se pone a pensar, por mas que están presentes todo el tiempo. Ademas el lenguaje que utiliza, creo que va a estar al alcance de todos los que podrían interesarse.

Lance Willett

The last chapter on computational kindness is worth the entire book.

Principle: be aware of optimizations and the level of difficulty to determine the right decision making process. You can’t control the outcome, but you can be “computationally kind” to those who you deal with: yourself, family, friends, colleagues; the world.

Computers and humans use similar tricks to tackle both routine and more difficult tasks: stop early, relax constraints, forgive, and know that sometimes enough is good enough.


 People are almost always confronting what computer science regards as the hard cases. Up against such hard cases, algorithms make assumptions, show bias toward simpler solutions, trade off the costs of error against the costs of delay, and take chances.
 
These aren’t the concessions we make when we can’t be rational. They’re what being rational means.

A fascinating exploration of how computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian (who holds degrees in computer science, philosophy, and poetry, and works at the intersection of all three) and Tom Griffiths (a UC Berkeley professor of cognitive science and psychology) show how the simple, precise algorithms used by computers can 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 understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Sameer Vasta

If there's one thing I learned from reading Brian Christian and Tom Griffiths' 
  Algorithms To Live By
, it's that my mind does not operate like a computer, at all.

This, of course, is not necessarily a bad thing. While computers are excellent at finding the best possible answers for our most complex problems, they are (at least, not yet) able to imbue those solutions with context, empathy, and an understanding of the human emotional condition.

That said, using computer science to guide decisions in our lives can be useful, and Mr. Christian and Mr. Griffiths' book is illuminating in that respect. What 
  Algorithms To Live By
 offers, more than simply advice on how to live like a computer, is a deeper understanding of computer science as a practice, and why it is so important to the way we live today.

Despite working in the digital realm, my knowledge of how computers work is limited to very basic programming skills and a superficial understanding of hardware architecture. What I didn't realize until reading this book is that computer science isn't simply a way to find a correct answer, but a constantly-evolving process of finding the best answers to questions that have no perfect solution. Like humans, computers must make quick decisions; unlike humans, their capacity to process incredible amounts of information to drive those decisions is formidable.

My habits of sorting and filing, of making pro-and-con lists—these are all contrary to the way computer science would suggest I live my life. I am re-evaluating these habits after reading 
  Algorithms To Live By
, but more than simply taking the advice at face value, I am constantly asking myself, now: what would an algorithm do? I may not know the answer, or even like it, but this book has at least opened my eyes to a new way of thinking, and given me a new tool in my problem-solving kit.

(originally published on inthemargins.ca)

Lucas Coelho

I listened to this book on audible. 

Amazing book and really makes you think about how we can use simple algorithms to make our lifes simpler and better. 

Worth reading!

Luca Conti

Many decisions we take everyday are similar to how computer science solves problems. It's fascinating.

Dani

I really think I'd like this book in hard copy so I can fill it with post-it notes.

A fascinating exploration of how computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favourites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian (who holds degrees in computer science, philosophy, and poetry, and works at the intersection of all three) and Tom Griffiths (a UC Berkeley professor of cognitive science and psychology) show how the simple, precise algorithms used by computers can 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 understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Algorithms to Live By The Computer Science of Human Decisions

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