Algorithms to Live By: The Computer Science of Human Decisions
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.
“A remarkable book... A solid، research-based book that’s applicable to real life. The algorithms the authors discuss are، in fact، more applicable to real-life problems than I’d have ever predicted.... It’s well worth the time to find a copy of Algorithms to Live By and dig deeper.” ―Forbes “By the end of the book، I was convinced. Not because I endorse the idea of living like some hyper-rational Vulcan، but because computing algorithms could be a surprisingly useful way to embrace the messy compromises of real، non-Vulcan life.” ―The Guardian (UK)
Hardcover: 368 pages Publisher: Henry Holt and Co. (April 19، 2016) Language: English Product Dimensions: 6.4 x 30.7 x 239.3 inches