Algorithms to Live By The Computer Science of Human Decisions (Pdf kindle) by Brian Christian – Epub, TXT and Kindle free


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Algorithms to Live By The Computer Science of Human Decisions

Rithms used by computers can also untangle very human uestions 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. An engaging conceptual tour of computationalnetworking 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 principlesconcepts 37% rule of optimal stopping when to stop scouting prospects and just commit exploreexploit tradeoff chance of finding a new gem vs certainty of enjoying a known fave LRU last recently used sorting as an efficient prophylactic for searching layered caches as metaphor for human memory brain fart as cache miss overfitting when interpreting data prefer simple accuracy to complex precision constraint relaxation as a techniue to address knotty problems buffer bloat when backlog is bad best to reject all incoming reuests until it clears exponential back off when head butts recur double your wait time before trying again computational kindness by reducing the options on the table we do people s brains a favor

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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 mindAll 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 act. 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 by computers I suspect the computer science label is to make it sexy than boring old mathematicsIf there is any danger that the M word would turn you off the book tends to skip over the mathematical workings concentrating on the outcomes and how they re relevant to the kind of decisions we make in everyday life and it s that application side that makes it particularly interesting helped by a good readable style from the co authors So for instance one of the earliest areas covered is the kind of decision where you are selecting between a number of options that arrive seuentially and where you have to make a decision on which is best for you part way through the seuence even though there may be better options in the future The classic examples for this are some kinds of job interviews house buying and finding a partner for lifeIt might seem there can be no sensible advice but mathematically it s very clear You wait until you ve got through 37% of the choices then pick the next one that s better than any you ve seen before It s not that this will necessarily deliver your best of all possible worlds More often than not it won t But it will give you a better result than any other mechanism for deciding when to go for a particular option Of course it s not always easy to apply For example unless it s something like an interview with closed applications how do you know when you are 37% of the way through the available options Luckily the authors point out that there are approximations to get around this which include that the approach can also apply to the amount of time available for the processAnd that s just the start Along the way you will discover the best way to sort the books on your shelves into alphabetic order something I confess I did last year using a sub optimal mechanism how to balance exploration for example trying out new restaurants with exploitation for example returning to tried and tested restaurants how the concept of caching can revolutionise your filing system and make that pile of papers on your desk that everyone mocks the sensible approach why Bayes theorem is so important and much I absolutely revelled in this bookThe content only fades a bit when the applications aren t about real world decisions So for instance there s some material about how the internet works that is very interesting if you like that kind of thing I do but hasn t got the same feeling of personal utility to it so lacks some of the bite of the other chapters This is even obvious in the section on randomness I would also have liked to see acknowledgement that most of the content was really from the area of study called operational operations in the US research a discipline that happens to make use of computers rather than true computer science but that s a specialist moanRealistically speaking I don t think much of the content of this book will truly change how any of us do things Interestingly the authors reveal than an expert in the field pretty much consciously ignored the mathematical approach in a particular case opting for of a feels right choice But that doesn t stop the whole business whether it s the relative simplicity of the 37% rule or the mind twisting possibilities of game theory from being both potentially practical and highly enjoyable as presented here Recommended Grass, Sky, Song undone in a day or a lifetime How much messiness should we accept What balance of new act. 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 Otter Chaos! (Otter Chaos use this in real life This often comes The Illusionists up with algebra which often is O Último Testamento (Maggie Costello, 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 by computers I suspect the computer science label is to make it sexy than boring old mathematicsIf there is any danger that the M word would turn you off the book tends to skip over the mathematical workings concentrating on the outcomes and how they re relevant to the kind of decisions we make in everyday life and it s that application side that makes it particularly interesting helped by a good readable style from the co authors So for instance one of the earliest areas covered is the kind of decision where you are selecting between a number of options that arrive seuentially and where you have to make a decision on which is best for you part way through the seuence even though there may be better options in the future The classic examples for this are some kinds of job interviews house buying and finding a partner for lifeIt might seem there can be no sensible advice but mathematically it s very clear You wait One for My Baby until you ve got through 37% of the choices then pick the next one that s better than any you ve seen before It s not that this will necessarily deliver your best of all possible worlds More often than not it won t But it will give you a better result than any other mechanism for deciding when to go for a particular option Of course it s not always easy to apply For example Paragon Walk (Charlotte & Thomas Pitt, unless it s something like an interview with closed applications how do you know when you are 37% of the way through the available options Luckily the authors point out that there are approximations to get around this which include that the approach can also apply to the amount of time available for the processAnd that s just the start Along the way you will discover the best way to sort the books on your shelves into alphabetic order something I confess I did last year We using a sub optimal mechanism how to balance exploration for example trying out new restaurants with exploitation for example returning to tried and tested restaurants how the concept of caching can revolutionise your filing system and make that pile of papers on your desk that everyone mocks the sensible approach why Bayes theorem is so important and much I absolutely revelled in this bookThe content only fades a bit when the applications aren t about real world decisions So for instance there s some material about how the internet works that is very interesting if you like that kind of thing I do but hasn t got the same feeling of personal The Moon Platoon (Space Runners, utility to it so lacks some of the bite of the other chapters This is even obvious in the section on randomness I would also have liked to see acknowledgement that most of the content was really from the area of study called operational operations in the US research a discipline that happens to make The Echo (The Anomaly Quartet, use of computers rather than true computer science but that s a specialist moanRealistically speaking I don t think much of the content of this book will truly change how any of The Asset (Wounded Warrior us do things Interestingly the authors reveal than an expert in the field pretty much consciously ignored the mathematical approach in a particular case opting for of a feels right choice But that doesn t stop the whole business whether it s the relative simplicity of the 37% rule or the mind twisting possibilities of game theory from being both potentially practical and highly enjoyable as presented here Recommended

Brian Christian · 6 Review

Ivities and familiar favorites is the most fulfilling These may seem like uniuely human uandaries 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 usIn a dazzlingly interdisciplinary work acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algo. 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 efficient by exploring the idea of human algorithm design searching for better solutions to the challenges people encounter every day The central thesis is that it s best to use shortcuts to improve your probability of success and remember that perfection is the enemy of the good The book s algorithms are intended to reduce time spent puzzling conserve energy for the things that matterWhen it comes to the first two categories computer science is shown to be a good guide to problems created by the fundamental structure of the world and by our limited capacities for processing information As with all the sciences before it computer science and data science are pretty effective in dealing with these issues And the computational approach seems to be a remarkably useful improvement in dealing with areas like self control or complex everyday decisionsIn this part of the book when we deal with Man vs Nature Man vs Self we mostly encounter well defined problems and potential algorithms to deal with them We have a nice variety of approaches hereFirst we are given a taste of the Optimal stopping problems which spring from the irreversibility and irrevocability of time How do you decide when to stop searching be it for a the perfect mate the perfect employee the perfect job or the perfect weekend movie The answer seems to be simple 37% you stop once 37% of your options have been checked out Much useful than it sounds this number is the output of an algorithm Whether it s an apartment a parking space or a spouse the right moment to stop searching and start choosing falls under the umbrella of problems called optimal stopping The general solution to optimal stopping problems reveals that you should spend 37 percent of your time gaining an impression of what s out there and the rest of the time selecting anything better than the average of what you observed thus far Need to rent an apartment in three weeks Simply take one week to observe and two weeks to pounce on the next best thing This means that you have a good sample of the options you have so you don t jump to early decision and miss out on the good choices that were just around the corner and at the same time you don t waste all your time only searching Then we are introduced to the exploreexploit dilemma springing from time s limited supply should we revisit favourite restaurants and places and ensure a good time exploit or should we explore bravely out to new experiences and places explore in the hope that we might stumble on something incredible If we don t explore we might miss out on a lot of YOLO stuff but if we only explore and do not exploit the good stuff we have already discovered a favourite dish a cared for home spouse close friends etc then we might me missing out on even SO how do we figure out an optimal ration between ExploreExploit Turns out computer scientists have been working on finding this balance for than fifty years They even have a name for it the exploreexploit tradeoff The exploreexploit tradeoff tells us how to find the balance between trying new things and enjoying our favourites The answer is to think about the time you have left the time you have the your strategy should shift So the young should explore and the elderly should exploit and wherever you are in that continuum you should ration the Es accordingly YOLO after allThere are Relaxation and randomization emerge as vital and necessary strategies for dealing with the ineluctable complexity of challenges like trip planning and vaccinations Sorting theory tells us how and whether to arrange our offices Caching theory tells us how to fill our closets Scheduling theory tells us how to fill the unforgiving minute well etcThen comes the next two categories Man vs Man and Man vs Society problems these are in effect the problems that we pose and cause each other Here the authors move away from computer science and enlists mathematics as well specifically and predictably game theory to help us out And the cross pollination between game theory and computer science gives us algorithmic game theory for tackling issues like investing bubble and even plain arguments The solutions are much less rigorous here with 1 the advice to change the game if the game threatens to go into less than optimal euilibriums and 2 an exhortation to be computationally kind to reduce the cognitive load of the participants emerging as the main algorithms to live by when it comes to living in society So as always the book would seem to be teaching us again that no matter how computationally adept we are dealing with each other is something that just can t be fitted into any algorithm formula or thumb rule We gotta wing it


10 thoughts on “Algorithms to Live By The Computer Science of Human Decisions

  1. says:

    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 timesThis book spoke volumes to

  2. says:

    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

  3. says:

    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 problemsThe book starts out describing the optimal stopping problem It is also sometimes called the secretary hiring problem and I have seen it applied to

  4. says:

    Okay I loved this book So what is it about?The big pictureWe 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

  5. says:

    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 computerBut perhaps out of train wreck curiousity I picked it up and took a look The first thing I noticed is that Alison Gopnik

  6. says:

    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 thr

  7. says:

    I really enjoyed this book It's a nice popular review of research in a style similar to Malcolm Gladwell It was f

  8. says:

    An engaging conceptual tour of computationalnetworking 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

  9. says:

    In this book the authors explain famous algorithms in real world context My notes from this book 1 Optimal Stopping2 Old people don't lose memory they have so much of it that it slows their system3 Procrastination can be seen as an efficient scheduling problem with wrong priority4 Predictive Models Gaussian Power Law Erlang5 Over

  10. says:

    So many great one liners in this bookStop on Tinder at 37%Use thick markers in brainstormingAll things being eual it'll last as long as it's lastedBut 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 W

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