Read The Formula: How Algorithms Solve all our Problems … and Create More by Luke Dormehl Online

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What if everything in life could be reduced to a simple formula? What if numbers were able to tell us which partners we were best matched with – not just in terms of attractiveness, but for a long-term committed marriage? Or if they could say which films would be the biggest hits at the box office, and what changes could be made to those films to make them even more succesWhat if everything in life could be reduced to a simple formula? What if numbers were able to tell us which partners we were best matched with – not just in terms of attractiveness, but for a long-term committed marriage? Or if they could say which films would be the biggest hits at the box office, and what changes could be made to those films to make them even more successful? Or even who out of us is likely to commit certain crimes, and when? This may sound like the world of science-fiction, but in fact it is just the tip of the iceberg in a world that is increasingly ruled by complex algorithms and neural networks.In The Formula, Luke Dormehl takes you inside the world of numbers, asking how we came to believe in the all-conquering power of algorithms; introducing the mathematicians, artificial intelligence experts and Silicon Valley entrepreneurs who are shaping this brave new world, and ultimately asking how we survive in an era where numbers can sometimes seem to create as many problems as they solve....

Title : The Formula: How Algorithms Solve all our Problems … and Create More
Author :
Rating :
ISBN : 9780753541685
Format Type : Hardcover
Number of Pages : 304 Pages
Status : Available For Download
Last checked : 21 Minutes ago!

The Formula: How Algorithms Solve all our Problems … and Create More Reviews

  • Rob Kitchin
    2019-06-05 14:19

    The Formula provides an overarching account of how algorithms are increasingly being used to mediate, augment and regulate everyday life. There’s much to like about the book -- it’s an engaging read, full of interesting examples, there’s an attempt to go beyond the hyperbole of many popular books about technology and society, and it draws on the ideas of a range of critical theorists (including Baudrillard, Deleuze, Marx, Virilio, Foucault, Descartes, Sennett, Turkle, etc). It’s clear that the discussion is based on a number of interviews with algorithm developers and academics. However, there are also some notable gaps in the analysis and the analysis itself generally lacks depth. There is no detailed discussion about the nature of algorithms or its formulation into pseudo-code or code, or even a brief potted history of the development of algorithms. There is a very short discussion concerning the negative side of algorithms and how they are used to socially sort, underpin anticipatory governance, regulate and control, which really needed to be expanded. The analysis points to various issues and suggests some interesting lines of enquiry but then skims over them, with one or two points from the varied selection of theorists being used to illustrate an idea but often in quite a superficial way. Given the book is designed to be a popular science text aimed at a lay readership getting the balance between accessibility, depth and critical reflection is tricky. Dormehl does a better job of balancing the two than some others I’ve read recently, but I would have still have preferred deeper analysis, especially on the nature of algorithms and the effects and consequences of algorithmic governance and automation.

  • Landon Rordam
    2019-06-17 13:24

    First of all, this is not a book about algorithms. The author does not spend any space talking about what algorithms are, how they work, or their history. Rather, he merely uses them as a stand-in for technology, listing example after exhausting example of things that computers and technology can do. Algorithms are given credit for (or blamed for) big data, data mining, statistics, social networking, the internet... the list goes on. Many of these things have algorithms in common, but the author spends no time actually breaking down where the algorithm comes in. It's almost a placeword, like magic.Not to mention the dizzying transition in this book between starry-eyed entrancement and hang-wringing despair. It seems that algorithms will both make everything in society perfect or come down and destroy us and our humanity. There is no real thesis, nor much actual real synthesis, as most of the book is simply book-review type summaries of articles and books. It gives algorithms far too much credit for everything. When a new topic arises with some silicon valley startup proclaiming the benefits of new technology, the author will invariably cite some instance where somebody wrote an algorithm wrong and something bad happened, and then make vague intimations about the danger of this technology. At one point he even suggested that cameras in bars would be able to tell whether the patrons had contracted STDs.A very disappointing book. I was very interested in learning how OKCupid algorithms worked, or how algorithms actually functioned in conjunction with the hardware of Google's driverless cars. Instead these technologies were merely mentioned, followed by a quotation from a Slate article that I had already read.

  • Gary
    2019-06-17 13:29

    Algorithms are a systematic set of rules for handling complex processes often using a recursive methodology (the routine calls itself). The author doesn't really define algorithm this way but he mostly appeals to examples that involve pattern recognition or some kind of sorting of subsets into their most common elements and associates the correlations between those subsets.He gives good examples on the state of algorithms in use today and how they aid us in our decision making (just think Google's search engine). He gives an example how the programmers got it wrong in creating an algorithm for social aid in Colorado. The program thought only homeless people deserved medical coverage for the poor and other such poor interruptions of policy.The author seems to think that "human intuition" can trump an algorithm. That just seems too naive and his examples in the book were never really convincing. Poor programming of misunderstood policy will lead to bad results, but the algorithm can be improved. A good algorithm can save lives and make better decisions (often with human interaction).Google knows what I want to search for before I do, and Amazon recommends books better than I can, their algorithms are very good. Humans have there place with their intuitions, but a good tool can be a priceless aid. They're not perfect, but they continually get better. Watson beat the best Jeopardy contestants in the country using its algorithm. As Ken Jennings said "I, for one, welcome our computer overlords" as he answered the final question while losing badly.A book about Algorithms should be keeping the listener on the edge of his seat. This book did no such thing. There wasn't really one thing in the book that I didn't already know (I lie. Will Smith uses patterns of recent Hollywood Blockbusters to determine his next movie is something I did not know. I don't care for Hollywood Blockbusters and that fact had escaped me).If you have any interest in Algorithms (and who among us doesn't?), I would recommend one of these three recent Audbile books that I have listen to instead, "Dataclysm", a book on big data, and big data allows for the pattern recognition and sorting that's mentioned in this book; "The Second Machine Age", tells what's really going on with algorithms now and how society is changing because of it; and one of my favorites, "Superintelligence", tells where we will end up because of the recursive algorithm.

  • Sarah
    2019-05-23 14:32

    I glowingly recommend The Formula. This book is for people who are concerned about the philosophical implications of computer algorithms being applied to those most human endeavors as love, law, art and autonomy of self. It is well written and researched. If you are interested in human rights, future work, and your shrinking sphere of information despite the information revolution then read this book. Certainly the potentials for systemic inadvertent discrimination should be widely, openly and publicly discussed. To be "informed" everyone should be aware of the way recommender algorithms are shaping our lives right now.I believe this book has an artificially low star rating because many people rate it based on their own mistaken ideas of what the book was intended to be about. Perhaps the publisher should find a way to indicate that this is a sociological book about human / technology interaction and not a technology guidebook, which seems to be the main cause of people's disappointment. I would usually not give a 5 star review, but I consider this book sufficiently eye opening and important to try and increase its appeal (according to those recommender algorithms of human behavior).

  • Kirsten Zirngibl
    2019-06-01 19:43

    This was a good overview for people wondering about the implications of Big Data in our society, especially how formulas for prediction can become self-fulfilling prophesies and about what it means to find meaning. However, I found it disappointing that the author didn't even try to properly describe algorithms beyond "a series of step by step instructions" or categorize them in any meaningful way. Yes, he warned that this is not "a computer science textbook" but the basics could still be explained using plain language, and I don't understand the author's unwillingness to do so. Give the laymen some credit!He also calls this a "history book" but doesn't spend much time on the pre-digital history of algorithms. It was still entertaining overall, at least.

  • Colleen
    2019-05-25 21:42

    It reads like someone took an undergraduate statistics class and drew some obvious comparisons. The phenomena of data mining and data analysis isn't shocking or surprising to anyone involved with that sort of thing. Sure, it can be done faster with computers and sure, there are a lot of practical applications. It's like the author was one of those people who thought math class was a waste of time and became shocked. SHOCKED! that it was everywhere. Also, the author's attempt to make "The Formula" a catch-phrase annoyed me. I fully admit to skimming big chunks in the back half of this book, mostly to see if it ever came around to a point. It didn't.

  • Brenda
    2019-06-11 14:19

    This is one of those rare longread magazine pieces expanded into a book that doesn't lose out in the expansion. The author is a tech journalist with a crateful of sociocultural concerns about the uses to which we put useful technologies. Way more questions than answers here, but they're the right questions.

  • Rick
    2019-06-11 13:43

    It is not really a technical book and does not describe how algorithms work. Instead, the writer gives brief examples, and explains what impact algorithms are having in society; both in a negative and positive way. The writer quotes many scientists, philosophers, politicians, and academics, so it is a useful source of references.

  • Mackie O'Hara
    2019-06-14 13:18

    Some reviewers are concerned by the use of the word "algorithm," but if you ignore that, this is a fascinating book could provoke thousands of discussions ethical, historical, theoretical, and mathematical.

  • Ron Yeo
    2019-06-16 19:27

    TO be fair, the author did provide a disclaimer in the foreword/introduction that its not a technical book on algorithm. Nevertheless, even discounting this, this book had nothing new in store with me. Felt like a collage of magazine articles to me.

  • BLACK CAT
    2019-06-17 19:29

    mix between algorithms, data science, internet of things, ethics and interesting applications: movie hit predictor, face recognition, medical diagnosis software, etc...

  • Kathryn
    2019-06-08 16:21

    I finished reading this non-fiction book about algorithms last night. It is about how algorithms are now being used for all kinds of uses, and how some of those uses are very problematical, and I very much enjoyed reading the book.An algorithm is defined as "a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer". As such, an algorithm is neither good or bad; it is the use made of them that can aid our lives immensely, or cause problems. In this book, the author explains how Wall Street uses algorithms to teach the computers when to buy or sell, how dating websites use algorithms to match up prospective suitors, how Facebook uses algorithms to determine what shows up in "Trending" for a given person, and how Google uses algorithms to tailor one's search request. Algorithms have also been used for frivolous purposes, as one developed to predict how long a given celebrity marriage might last.The major problems with algorithms is the concept of the "black box"; the part of the algorithm that is kept more or less secret (either for proprietary reasons, or because the computations are hideously complex), so that all one knows is that one puts input at one end and gets an output at the other end. There have been cases where bringing up a person's name on Google brings up only negative answers, or only positive answers, which raises the question of how the algorithm actually works; and Facebook recently tweaked its algorithms to limit the reach of people known to frequently blast out links to clickbait stories, sensationalist websites and misinformation. And anyone who shops online knows that if one buys green carmel widgets online (or shops for green caramel widgets), one will get a plethora of advertising mail or advertising on their usual sites related to green carmel widgets. The author quotes former Vice President Al Gore as saying, "The ability to code and understand the power of computing is crucial to success in today's hyper-connected world."I enjoyed reading this book, and recommend it to anyone wondering just how algorithms are affecting our everyday life.

  • Jim Razinha
    2019-06-01 15:36

    Seems like a lifetime ago, but there used to be a computer language called ALGOL...short for Algorithm Language (language names meant something back then). And mearly a lifetime ago, programmers - that's what coders where called, in the day - had to develop algorithms to generate pseudo-random numbers, quickly sort lists, compile programs (code) into the most efficient space given memory and operations per second limitations. This is not about those kinds of algorithms. What Dormehl does do is pull together - using at least one external reference, be it book or article, per page, and more than a smattering of pop culture drops - what big and little data mining are doing for and to your world. Online dating? Matching algorithms. Shopping? Please. Some Big Brothers aren't even trying to hide - surely you've noticed that if you hop over to social media after searching on Amazon that coincidentally, precisely what you were just searching for is right there! And less obvious, you feed is what BB thinks it should be sending you...not necessarily what you would be actually interested in.I don't use a Kindle, or the Kindle app, to read ebooks because I don't like the interface. But I also don't want Amazon trying to figure out how much time I spend reading a page, or whether I even bother with the Introduction. I have no allusions that CrApple is not sending my data to their payers, but theirs is not the only app I use.Where we need to worry, other than being herded to buy what they want us to buy, is whether entities and agencies are relying on these revolving, and artificially tweaked algorithms to make decisions that affect our lives and rights. Get tagged on a "no fly" list? The burden of proof is on the innocent.Good stuff that could have been lightened with less lightening. Use foot or end notes...it's okay, and gratuitous pop refs in an attempt to moisture the topics are distracting. Trust that your readers are a bit sharper than a news channel viewer.

  • DGG
    2019-05-21 17:40

    Given I was reading this book in 2017 I felt most topics are a bit dated. Coming from a computer science background, I had come to believe programmed or automated solutions lead to a more objective solution to real life problems. However, this book provided strong evidence to the contrary. From the very first chapter which talks about quantified self systems to the last chapter which talks about govt. systems using rule based systems to automate clerical work, the author spends a lot of time explaining the system and how there might be inherent biases in the system because of the team bringing in his's or her's bias while designing the system. I do feel the author brings a very strong arts and humanities background to his argument and does not feel the excitement in seeing the problem solving aspects of the problem. Given the fact that he has selection sort in his book cover I was surprised and expected a different approach. In particular he mentions solutions to problems as "tricks" and tries to drive home his point that "the why" to a solution is more important than "the how" to the problem. I feel more software engineers need to read this book as most engineers need to realize inherent biases that are being brought into the system. One particular example that really stuck with me was the bridge example in England specifically designed to block access to a park for people who did not own a car. The anthropologist Danah Boyd mentioned in one of her podcast how Facebook won over MySpace because Facebook had an invite only policy and had a lot of college students whereas MySpace networked a lot of artists and hence MySpace got a bad rap of being an unsafe place for teenagers.I would strongly recommend this book for anybody who is interested in the software profession especially programmers who build systems to solve real life problems. There are inherent biases which one brings into his daily life

  • Jim Beilstein
    2019-05-26 21:38

    Algorithms and Implications A solid read on how pervasive algorithms are becoming in our lives and the broad implications to society. I found the author to be very balanced in his view, showing both pros and cons of our society is becoming more and more algorithm-based over time. There are real and sometimes unpredictable implications of trusting our information to search algorithms and the author has done a very nice job exploring this space and what is seemingly an increased reliance on "black boxes" in our everyday lives. I doubt we're ever going to go back to the way things were, so opening your eyes to this modern reality is critical.

  • Edward B.
    2019-06-13 21:19

    Not great, but not bad.I didn't find the writing compelling, but it was fine, and the subject matter is reasonably important.The book looks at the idea of algorithmic solutions to questions/problems, historically and into the future. Where they are appropriate and where they aren't - and what can happen if applied where they aren't. Deep-learning AI as a Black Box that humans can't deconstruct in order to evaluate for errors, for example. Technical, legal, social implications of that.

  • Shonn Haren
    2019-05-22 17:47

    Also read for a research project. While Steiner's Automate This gave provided a good background for how algorithms were created and came to dominate our society, Dormehl does a better job of showing the effects of our reliance on algorithms, and why our assumption of their objectivity isn't always a good thing.

  • Manish Katyal
    2019-06-12 16:24

    This book does claim to explain algorithms - rather describes the use-cases - how businesses are leveraging algorithms.

  • Charlene
    2019-06-16 18:25

    The highlight of the book was the chapter about online dating. Fantastic. I cannot say the same for the rest of this book. While the author did seem to understand some of the biases inherent to algorithms, he seemed wholly unaware of the biases in criminology research. His chapter on predicting crime was horrible, truly horrible. His critical thinking ability seemed to have been on hold. In a different section, he wrote about the biases of judges when sentencing but never quite seemed to connect how bias affects predicting criminality. In America (or elsewhere), we don't do a very good job of predicting crime. If we don't know who the criminals are and we base algorithms on our faulty data, then those algorithms are faulty. If we use faulty algorithms to arrest and cage people, the outcome is not crime reduction. Instead it serves only make ourselves feel better. In America, we disproportionately target, arrest, convict, and cage black people. We label and treat them like criminals when, at the same time, we allow many white people to go free, even though they have engaged in the same actions. It is unjust. People like Dormehl contribute to the legitimacy of the awful and non-scientific practice of targeting, labeling, and taking the life (but execution, locking in a cage, or robbing them of an opportunity to seek employment, housing, or education) of a disproportionate number of black people and poor people in general. That is not ok. The worst part is, data about biases in crime prediction and prevention are *easily* found. Every intro to criminology/criminal justice textbook is clear on the problem of measuring crime. To be unaware of these very common problems is simply sloppy research. Dormehl chose to ignore the myriad data available. For that reason, I have to question his critical thinking ability in general. This makes me wonder about all of the research in this book, even the bits I enjoyed.

  • Rob
    2019-06-09 14:25

    I don't know why I continue to pick up these books - the tagline is interesting as well as the first 50 pages or so, but then I get bored by the repetitious nature of the material. The author does fine in bringing up all the different areas that you can see "The Formula" utilized so the content itself is different, but I struggle through the second half because to me it is just the same idea in different areas. I don't need more examples, I need something new. Anyway, I'm sure I will continue to grab books off the bookshelf like this one because I will enjoy the beginning of the book; hope that I will find one that keeps me engaged until the end.

  • Nathaniel
    2019-06-15 18:28

    Most of the anecdotes and technologies of which this book is comprised were already perfectly familiar to me from following tech news, and as a result there was very little new information for me in this book. A lot of the analysis and critique of these technologies were new, but they were presented in a disjointed, fragmentary manner with no cohesive theme and certainly no thesis with which one could agree or disagree in whole or in part. It was sort of like a random assemblage of things somebody said at some time or other about the events included in the book, without any real context or further explanation of why this or that excerpt from a book or journal was included. As a result, I found the thing alternately tedious and mystifying, wondering what on earth Dormehl himself thought of the quotes he was including--frequently at odds with each other and almost invariably relying on philosophical background that wasn't provided.There was a quite interesting section at the very end (once again an almost random patchwork of quotes from various sources) that happened to hit upon a hobby horse of mine (epistemic humility) and so--strictly in terms of research--that made this worth my while. But it certainly wasn't informative or enjoyable. Perhaps someone who doesn't follow tech and/or has no formal expertise in mathematical modeling might find it more satisfying, however.

  • Amy
    2019-05-27 14:39

    This book purports to be about how algorithms shape our world, but sadly there's not much detail about the algorithms themselves. It seems to be more about how data and the trends we find from them shape our lives, with occasional mentions of algorithms--which is a fabulous topic in and of itself. I really enjoyed this book, just wish it had a different subtitle. :) Here's a quote from the cover that I feel is fitting:"What if everything in life could be reduced to a simple formula? What if numbers were able to tell us which partners we were best matched with – not just in terms of attractiveness, but for a long-term committed marriage? Or if they could say which films would be the biggest hits at the box office, and what changes could be made to those films to make them even more successful? Or even who is likely to commit certain crimes, and when? This may sound like the world of science fiction, but in fact it is just the tip of the iceberg in a world that is increasingly ruled by complex algorithms and neural networks."I appreciate that this book talks about these trends in detail and explores the pros and cons of that. Do these types of algorithms potentially have the ability to prevent racist stereotypes from seeping in? Or is there MORE risk because somebody had to create the algorithm and those prejudices become ingrained. What about the ethics of all these algorithms being hidden, typically for proprietary reasons?

  • Elaine Ruth Boe
    2019-06-17 13:37

    This book is fascinating. Offering a glimpse into how pervasive algorithms are in the day-to-day living of the 21st century, Dormehl shares the myriad ways that algorithms influence our lives without offering his judgment. From the quantified self of health junkies to dating sites to crime management, the algorithm has shaped how we do everything, and from Dormehl's estimation, its influence will only grow with the upcoming years. Dormehl leaves us with a question: if the purpose of AI and algorithm technology is to become as humanlike as possible, how are we, as humans, supposed to differentiate humankind when computers become increasingly like us? What makes us different, what makes us better, than an algorithm? I'd like to think that there are things, like friendship and compassion, that it takes a heart to do best. However, Dormehl presents much evidence to the contrary, much to suggest that AI can do pretty much everything better than us. While somewhat unsettling in its projections for the future, THE FORMULA gives a thought-proving look into the many ways algorithms affect our lives.

  • Zacaro Caro
    2019-05-23 18:35

    I waited a while to write a review about this book because I wasn't sure how I liked it. I knew for sure I didn't love it. There was a chapter or so that I didn't care for. But in the end and after some time here's what I think. This book is not about writing formulas, or applying algorithms, this book is about technology analyzing large data, and the implications and applications of how that's been used. It provides interesting examples of how this data has been used to market to you, profile criminals, and otherwise change the world we live in... If that sounds interesting then this is a good book for you. If you are sort of hoping to learn more about what an algorithm is, how to write one, and apply it towards your problem, then this book may not b for you. Or if you're like me and you couldn't care less about how to write an algorithm. And are aware of its shortcomings you may like this book. But if your like me and do not wait excitedly when the day comes when algorithms are applied to the cars we drive and the prices we pay for goods purchased, then this book may also be good for you.

  • Lan Kang
    2019-06-12 14:29

    The book is about the interaction of technology and humanity, from pricing to policing, from marriage to arts. It provides a lucid overview of how algorithms are affecting our daily life. "Cogito ergo sum", or should we now say "I measure, therefore I exist"? There are a few interesting companies mentioned in the book: Gild, a recruiting company automating the discovery of talented programmers using algorithms; Knack, using a combination of gaming technology, machine learning algorithms and latest finding in behavioral science to measure people's potential; Quantcast, ranks among the top 5 companies in the world in terms of measuring audiences; Epagogix, a U.K. Startup using neural network to analyze a movie script to project box office figure; ... Algorithms can often provide an illusion of neutrality. Important questions that we have to remind ourselves: Would algorithms predict or dictate? While online profiling determines what we see, what are we missing? Instead of asking what algorithms are doing to us, what are they designed to do in the first place? AlphaGo is getting smarter, however " being a person is not a pad formula, but a quest, a mystery, a leap of faith".

  • Deana
    2019-05-25 16:29

    I listened to this on audiobook, mainly during my commute. Parts of this book were really interesting, but much of it failed to hold my attention. I'd find my mind drifting to the scenery or some work-related topic. At first, I'd rewind and listen again... but often found my mind had drifted again and I'd missed the same section. So I stopped doing that and just let my mind drift in and out of paying attention.The first chapter I think was the most interesting, about the guy who is monitoring every aspect of his health. The relationship chapter had a few interesting tidbits, but was surprisingly dry. As someone who works on these type of machine learning algorithms for a living, I guess I was expecting something else. I _did_ like that he brought up some of the moral issues and biases involved with these types of algorithms, especially when they are used for crime applications (determining where a crime is likely to occur, or how risky it is to grant parole to an individual, or who gets flagged for the no-fly-list).

  • Phil
    2019-06-15 18:29

    While this book is about series of mathematical calculations, it's not some dry, lifeless textbook. Instead, The Formula discusses how, at a more human level, algorithms are changing the way we live. This book discusses the way we use algorithms for everything from data to dealing with the death of loved ones. This book also raises to the forefront the observation once wisely stated by Jeff Goldbloom in Jurassic Park - "Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should." This applies to the new algorithms that can learn human behaviors and mannerisms, to create a virtual version of a loved one to help their survivors deal with their death. Overall, this book introduced me to some of the science behind online dating and the idea that at some point, algorithms become so complex that even their creators can no longer predict the result the algorithm will come up with. Very interesting, and slightly scary, stuff.

  • Andrew French
    2019-06-18 19:19

    70% of trades made on Wall Street are ran by algorithms. It took HBO 25 years to receive an Emmy nomination, Netflix did it in 6 months. Google and Amazon not only control what you see in your search results, but how much you pay for a product based on your world view. All of this is done faster than a human can blink, all thanks to something called the algorithm. Algorithms are automated programs, a type of primitive artificial intelligence, that influence our lives and the world we live in without us ever knowing they exist. They make hedge funds billions of dollars, they know what your political opinions are, they know who would make the best life partner for you, and they sometimes even know what you’re going to think before you think it. In our post-industrial age, this digital revolution of automated machines is only going to continue growing faster and smarter; until one day - we will have reached the singularity.

  • William Schram
    2019-05-28 19:19

    This book was pretty good. It describes the good and bad aspects of reducing everything to a set of data. Some of it is rather frightening in scope. Sure you've heard of self-driving cars, but would you need to have a non-self-driving car in an emergency of some kind? This book is merely a cursory introduction to algorithms and how they affect our lives. In some ways it could turn into some kind of nightmarish dystopia, but in others it can improve our way of life.The author presents a lot of examples of human bias getting in the way of reason, while at the same time acknowledging that there are many things that computers and algorithms can't do well. The biggest one could be object recognition. At the same time, it probably won't take too long for us all to be like those characters on Wall-E; fat and unemployed since all of the jobs are done by robots.

  • Tom Tresansky
    2019-05-23 18:32

    Makes some great points about some of the unforeseen consequences of the algorithmization of various industries and daily life. Unfortunately too much would be familiar to anyone who read Slashdot. Still, I imagine for many people these considerations would be dramatic. Doesn't try to point in any specific direction, it's more of a survey of issues which already affect and will only increasingly dominate people's lives and businesses.Too often frustrating in its over simplifications, it's best when it's at its most philosophical, and worst when it presents a shallow analysis of pop culture that reveals far too much ignorance about its subjects. Clearly not written by someone with a technical background, the conflation of technology in general, computers in particular, and specific algorithms is often infuriating.Squeaks into a low 3.